Faecal occult blood testing for population health screening May 2004

Faecal occult blood 

testing for 

population health 

screening 

May 2004 

MSAC reference 18 

Assessment report

© Commonwealth of Australia 2004 

ISBN 0 642 82545 9 

ISSN (Print) 1443-7120 

ISSN (Online) 1443-7139 

First printed October 2004 

This work is copyright. Apart from any use as permitted under the Copyright Act 1968 no part 

may be reproduced by any process without written permission from AusInfo. Requests and 

inquiries concerning reproduction and rights should be directed to the Manager, Legislative 

Services, AusInfo, GPO Box 1920, Canberra, ACT, 2601. 

Electronic copies of the report can be obtained from the Medical Service Advisory Committee’s Internet site 

at: 

http://www.msac.gov.au/ 

Hard copies of the report can be obtained from: 

The Secretary 

Medical Services Advisory Committee 

Department of Health and Ageing 

Mail Drop 107 

GPO Box 9848 

Canberra ACT 2601 

Enquiries about the content of the report should be directed to the above address. 

The Medical Services Advisory Committee is an independent committee which has been established to 

provide advice to the Commonwealth Minister for Health and Ageing on the strength of evidence available 

on new and existing medical technologies and procedures in terms of their safety, effectiveness and costeffectiveness. 

This advice will help to inform Government decisions about which medical services should 

attract funding under Medicare. 

MSAC recommendations do not necessarily reflect the views of all individuals who participated in the 

MSAC evaluation. 

This report was prepared by the Medical Services Advisory Committee with the assistance of Mr Lachlan 

Standfield, Dr Suzanne Dyer, Mr Dominic Tilden, Mr Paul Mernagh and Dr Patrick Fitzgerald from 

M-TAG Pty Ltd. 

Publication approval number: 3533

Contents 

Executive summary................................................................................................. ix 

Introduction .............................................................................................................1 

Background ............................................................................................................ 2 

Faecal occult blood testing............................................................................................. 2 

Description of the technology and the procedure............................................ 2 

Intended purpose .................................................................................................. 3 

Clinical need/burden of disease .................................................................................... 4 

Incidence of colorectal cancer............................................................................. 5 

Mortality due to colorectal cancer....................................................................... 5 

Existing procedures......................................................................................................... 5 

Reference standard .......................................................................................................... 6 

Comparator....................................................................................................................... 6 

Marketing status of the technology............................................................................... 6 

Current reimbursement arrangement ........................................................................... 7 

Approach to assessment .......................................................................................... 8 

Review of literature ......................................................................................................... 8 

Search strategy ....................................................................................................... 8 

Selection criteria................................................................................................... 10 

Quality assessment .............................................................................................. 12 

Additional searches ............................................................................................. 12 

Expert advice.................................................................................................................. 13 

Results of assessment .............................................................................................14 

Faecal occult blood testing........................................................................................... 14 

Available evidence............................................................................................... 14 

Is it safe?.......................................................................................................................... 16 

Adverse events associated with faecal occult blood tests.............................. 16 

Adverse events associated with colonoscopy, sigmoidoscopy and 

double contrast barium enema.......................................................................... 16 

Psychiatric morbidity associated with colorectal cancer screening .............. 17 

Safety data reported in the FOBT studies ....................................................... 17 

Is it effective? ................................................................................................................. 18 

Diagnostic performance..................................................................................... 18 

Participation ......................................................................................................... 22 

Change in clinical management and clinical outcomes.................................. 22 

Results................................................................................................................... 22 

Faecal occult blood testing iii

What are the economic considerations?..................................................................... 33 

Assessment of value for money of population health screening for 

colorectal cancer .................................................................................................. 33 

Results of the economic model......................................................................... 48 

Sensitivity analyses............................................................................................... 54 

Discussion ............................................................................................................ 58 

Conclusions ...........................................................................................................61 

Safety ............................................................................................................................... 61 

Effectiveness .................................................................................................................. 61 

Cost-effectiveness.......................................................................................................... 62 

Summary of outcomes ........................................................................................... 65 

Appendix A MSAC terms of reference and membership..................................... 67 

Appendix B Advisory panel .................................................................................. 69 

Appendix C Studies included in the review...........................................................71 

Appendix D Literature searches ........................................................................... 74 

Appendix E Excluded references ......................................................................... 77 

Appendix F Positive predictive values ................................................................. 96 

Appendix G Diagnostic odds ratios.....................................................................102 

Appendix H Quality scoring ................................................................................105 

Appendix I Participation in FOBT screening rates...........................................106 

Appendix J Relative cost-effectiveness of Hemoccult versus Fecatwin 

Sensitive/ Feca EIA........................................................................108 

Appendix K Sensitivity analysis of Hemoccult versus HemeSelect ................... 112 

Abbreviations ........................................................................................................ 114 

References ......................................................................................................... 116 

iv Faecal occult blood testing

Tables 

Table 1 Hierarchy of evidence ............................................................................................ 12 

Table 2 Head-to-head studies of FOBT in screening populations................................ 14 

Table 3 Characteristics of the head-to-head FOBT studies performed in a 

screening population .............................................................................................. 20 

Table 4 Meta-analyses of sensitivity for carcinoma from FOBT head-to-head 

studies....................................................................................................................... 27 

Table 5 Meta-analyses of specificity for carcinoma from FOBT head-to-head 

studies....................................................................................................................... 28 

Table 6 Meta-analyses of relative TPR for carcinoma from main FOBT headto-head 

studies......................................................................................................... 30 

Table 7 Meta-analyses of relative FPR for carcinoma from main FOBT headto-head 

studies......................................................................................................... 31 

Table 8 Disease prevalence in the eligible screening population at program 

entry. ......................................................................................................................... 38 

Table 9 Distribution of CRC by Dukes’ stage classification in the eligible 

screening population at program entry................................................................ 38 

Table 10 Prevalence used for individuals entering the economic model........................ 39 

Table 11 Incidence of CRC ................................................................................................... 39 

Table 12 Incidence of progressive adenomas, age-adjusted ............................................. 40 

Table 13 Incidence of all adenomas, age-adjusted ............................................................. 40 

Table 14 Mean duration of undiagnosed cancerous and precancerous health 

states prior to progression..................................................................................... 40 

Table 15 Distributional spread of known CRC, by stage.................................................. 41 

Table 16 Probability of individual with CRC presenting as symptomatic, by 

stage .......................................................................................................................... 41 

Table 17 Five-year survival rates for CRC, by stage .......................................................... 42 

Table 18 Quarterly probability of death from diagnosed CRC........................................ 42 

Table 19 Probability of positive result using Hemoccult and HemeSelect..................... 43 

Table 20 Probability of positive result using Hemoccult Sensa and HemeSelect.......... 44 

Table 21 Probability of positive result using Hemoccult and Fecatwin 

Sensitive/Feca EIA ................................................................................................ 44 

Table 22 Detection rates associated with colonoscopy..................................................... 45 

Table 23 Cost of FOBT per invited individual................................................................... 45 

Table 24 Cost of FOBT per participant .............................................................................. 46 

Table 25 Cost of colonoscopy without polyp removal ..................................................... 46 

Table 26 Cost of colonoscopy with polyp removal ........................................................... 46 

Table 27 Lifetime CRC treatment costs, from time of diagnosis .................................... 47 

Faecal occult blood testing v

Table 28 Compliance with FOBT screening rates used in the economic model .......... 47 

Table 29 Life-expectancy from the beginning of the economic model .......................... 49 

Table 30 Relative cost-effectiveness of Hemoccult Sensa over HemeSelect ................. 51 

Table 31 Life-expectancy from the beginning of the economic model .......................... 53 

Table 32 Relative cost-effectiveness of Hemoccult over HemeSelect ............................ 54 

Table 33 The effect of increasing the frequency of screening to annual testing 

on relative cost-effectiveness: Hemoccult Sensa versus HemeSelect ............. 55 

Table 34 The effect of lowering the eligible age to 50 years on relative costeffectiveness: 

Hemoccult Sensa versus HemeSelect.......................................... 56 

Table 35 The effect of increasing the eligible age to 80 years on relative costeffectiveness: 

Hemoccult Sensa versus HemeSelect.......................................... 56 

Table 36 The effect of increasing the frequency of screening to annual testing 

on relative cost-effectiveness: Hemoccult versus HemeSelect ........................ 57 

Table 37 The effect of lowering the eligible age to 50 years on relative costeffectiveness: 

Hemoccult versus HemeSelect..................................................... 58 

Table 38 The effect of increasing the eligible age to 80 years on relative costeffectiveness: 

Hemoccult versus HemeSelect..................................................... 58 

Table 39 Relevant studies identified..................................................................................... 71 

Table 40 FOBT Medline search strategy (1966 to February week 3 2004) .................... 74 

Table 41 FOBT EMBASE search strategy (1980 to 2004 week 09) ............................... 75 

Table 42 Meta-analyses of PPV for carcinoma from FOBT head-to-head 

studies....................................................................................................................... 98 

Table 43 Meta-analyses of PPV for neoplasms (carcinoma or adenoma) from 

FOBT head-to-head studies................................................................................ 100 

Table 44 Meta-analyses of diagnostic odds ratios for carcinoma from FOBT 

head-to-head studies............................................................................................. 103 

Table 45 Quality scoring scale for FOBT comparative screening studies.................... 105 

Table 46 Round 1 participation with FOBT screening ................................................... 106 

Table 47 Participation data from Jorgensen et al (2002)................................................. 106 

Table 48 Later-round participation with FOBT screening for those who 

participated in round 1......................................................................................... 107 

Table 49 Proportion of new participants after the first screening round ..................... 107 

Table 50 Life-expectancy from the beginning of the economic model in the 

Hemoccult versus Fecatwin Sensitive/Feca EIA analysis.............................. 109 

Table 51 Incremental cost-effectiveness of Hemoccult versus Fecatwin 

Sensitive/Feca EIA .............................................................................................. 111 

Table 52 The effect of selecting alternative sensitivity and specificity values for 

Hemoccult: Hemoccult versus HemeSelect...................................................... 112 

vi Faecal occult blood testing

Figures 

Figure 1 Reasons for exclusion of published studies of FOBT identified by the 

literature search ....................................................................................................... 11 

Figure 2 Simplified natural history of CRC used in the economic model ..................... 36 

Figure 3 Screening pathway used in the economic model................................................ 37 

Figure 4 Component costs of FOBT screening – Hemoccult Sensa versus 

HemeSelect .............................................................................................................. 49 

Figure 5 Pattern of neoplasm detection in the Hemoccult Sensa versus 

HemeSelect screening analysis.............................................................................. 50 

Figure 6 Method of neoplasm detection in the Hemoccult Sensa versus 

HemeSelect analysiss.............................................................................................. 51 

Figure 7 Component costs of FOBT screening – Hemoccult versus 

HemeSelect .............................................................................................................. 52 

Figure 8 Pattern of detection in the Hemoccult versus HemeSelect screening 

analysis...................................................................................................................... 53 

Figure 9 Method of neoplasm detection in the Hemoccult versus HemeSelect 

analysis...................................................................................................................... 54 

Figure 10 Summary receiver-operating characteristic curve for Hemoccult 

versus HemeSelect sensitivity analyses .............................................................. 104 

Figure 11 Component costs in the Hemoccult versus Fecatwin Sensitive/Feca 

EIA analysis........................................................................................................... 109 

Figure 12 The pattern of detection in the Hemoccult versus Fecatwin 

Sensitive/Feca EIA .............................................................................................. 110 

Figure 13 Method of CRC/cancerous adenoma detection in the Hemoccult 

versus Fecatwin Sensitive/Feca EIA analysis................................................... 110 

Faecal occult blood testing vii

Executive summary 

The procedure 

Faecal occult blood tests (FOBTs) are used to detect blood in faeces that is not obvious 

by general inspection (ie, occult blood). This technology has been utilised for both 

diagnostic and screening purposes; however, the purpose of this review is to investigate 

the relative performance of different FOBTs for population health screening. The review 

was undertaken to provide support to the Australian Government Bowel Cancer 

Screening Pilot Program (the pilot). 

There are two types of FOBTs in common use: the long-established guaiac tests and the 

newer immunochemical tests. ‘Two-tiered’ combinations of these tests have also been 

developed. 

Guaiac FOBTs 

The guaiac FOBTs act by detecting the intact haem molecule from haemoglobin. These 

tests are simple to perform colorimetric tests, often conducted in the home. Two small 

samples from stools obtained on three consecutive days are applied to a piece of paper 

impregnated with guaiac gum. Upon application of a developing solution, the presence of 

trace amounts of haem results in a blue colour change due to the pseudo-peroxidase 

actions of haem. Guaiac FOBTs are able to detect bleeding originating anywhere 

between the mouth and anus. However, the sensitivity of guaiac FOBTs for detecting 

upper gastrointestinal (GI) bleeding is less than for the lower GI tract. The accuracy of 

guaiac FOBTs can be affected by several factors including medications, diet and 

excessive amounts of reducing agents in faecal samples (eg, vitamin C). 

The guaiac FOBTs include brand names such as: Hemoccult, Hemoccult II, Hemoccult 

Sensa, Hemo FEC, Coloscreen, Fecatest (discontinued) and Shionogi B. The two 

versions of the Hemoccult test (Hemoccult and Hemoccult II) differ only with regard to 

their configuration, therefore this document will refer to both versions simply as 

Hemoccult, without differentiation. 

Immunochemical FOBTs 

The immunochemical FOBTs involve the use of an anti-human monoclonal antibody, 

targeted at intact human blood-borne proteins (usually haemoglobin). These tests 

therefore have the theoretical advantage of not being affected by haem, peroxidases or 

anti-oxidases in the diet. In addition, immunochemical tests will not detect proximal 

bleeds, since in this case haemoglobin will be digested before being passed in the faeces. 

However, these tests are generally more complex and expensive than the guaiac tests and 

often require laboratory processing. 

The immunochemical FOBTs include brand names such as: HemeSelect (discontinued) 

and Immudia-HemSp (international equivalents), FlexSure OBT (discontinued), 

Quicktest, DIMA FOB-10, Bayer Detect, Magstream HemSp, !nSure, !nForm and 

Faecal occult blood testing ix

BM-Test Colon Albumin. HemeSelect and Immudia-HemSp are reverse passive 

haemagglutination (RPHA) tests. 

Two-tier tests 

The ‘two-tier’ approach has been developed in response to the high positivity rates of 

some guaiac FOBTs. By following positive results from a highly sensitive guaiac test with 

an immunochemical test, there should be an increase in specificity and a reduction in the 

otherwise high rates of unnecessary diagnostic follow-up. Studies using Hemoccult Sensa 

and HemeSelect in such a two-tier approach have been conducted (Allison et al 1996; 

Rae and Cleator 1994). 

Fecatwin Sensitive/Feca EIA was an example of the combination of a guaiac and 

immunochemical test performed in two-tiers. Samples were initially screened with the 

Fecatwin Sensitive guaiac test and then positive samples were tested with the Feca EIA 

immunochemical test. This test is no longer commercially available. 

Medical Services Advisory Committee – role and approach 

The Medical Services Advisory Committee (MSAC) is a key element of a measure taken 

by the Commonwealth Government to strengthen the role of evidence in health 

financing decisions in Australia. MSAC advises the Commonwealth Minister for Health 

and Ageing on the evidence relating to the safety, effectiveness and cost-effectiveness of 

new and existing medical technologies and procedures, and under what circumstances 

public funding should be supported. 

A rigorous assessment of the available evidence is thus the basis of decision-making 

when funding is sought under Medicare. Medical Technology Assessment Group Pty Ltd 

(M-TAG) was contracted to undertake a systematic review and economic evaluation of 

FOBTs for population health screening. An advisory panel with appropriate expertise 

then evaluated this evidence and provided advice to MSAC. 

MSAC’s assessment of faecal occult blood testing for population 

health screening 

Clinical need 

Colorectal cancer (CRC) is the most common type of cancer in Australia apart from nonmelanocytic 

skin cancer, with 12,405 cases being diagnosed in 2000 (Australian Institute 

of Health and Welfare (AIHW) and Australasian Association of Cancer Registries 

(AACR) 2003). Of these, 6863 patients were men, equating to an age-standardised rate of 

80.2/100,000, and the remaining 5542 were women, equating to an age-standardised rate 

of 53.8/100,000. Hence, the incidence of CRC in 2000 was second only to prostate 

cancer in Australian men and to breast cancer in Australian women (again, excluding 

non-melanocytic skin cancer). 

Early stage disease usually responds well to surgery. However, the prognosis for 

metastatic disease is poor. Approximately 4718 people died from CRC in Australia in 

x Faecal occult blood testing

Safety 

2000, making it second only to lung cancer as a cause of cancer deaths nationally in 2000 

(AIHW and AACR 2003). Approximately five per cent of Australians develop CRC 

during their lifetime; half of these people die from the disease within five years of 

diagnosis. 

FOBTs are used as a screening test for the identification of CRC. This is based on the 

use of faecal occult blood as a marker for CRC. However, an inherent problem with the 

technology is that many other non-neoplastic disease processes can cause GI bleeding. 

Therefore, the sensitivity and specificity of a test for the detection of blood will not 

necessarily translate into equivalent accuracy for the detection of CRC in a population 

health screening setting. Positive FOBT results due to other GI diseases will give a 

reduction in the expected specificity of the technique as a CRC screening measure. 

Immunochemical tests are expected to be less susceptible than guaiac tests to this effect, 

since only lower GI bleeding is detected. 

FOBTs are non-invasive and therefore unlikely to cause adverse events. However, the 

use of FOBTs in a screening setting is likely to increase the number of colonoscopies, 

sigmoidoscopies and barium enemas performed in the screened population. Therefore, 

the increased numbers of adverse events associated with these procedures are important. 

A 1997 review of six prospective studies estimated that around 1 in 1000 patients suffer 

perforation, 3 in 1000 suffer major haemorrhage and between 1 and 3 in 10,000 die as a 

result of colonoscopy (Winawer et al 1997). A 1989 review of nine studies of diagnostic 

colonoscopy gives a slightly higher figure of around 1.7 in 1000 patients suffering 

perforation and similar figures for haemorrhage and death (Habr-Gama and Waye 1989). 

The risk of perforation and haemorrhage increases with the performance of 

polypectomy. There are also other occasional serious complications associated with 

bowel preparation prior to colonoscopy or the use of sedation in conjunction with this 

procedure. 

Perforation rates associated with sigmoidoscopy appear low and occur in less than 2 

cases per 10,000 examinations (National Health and Medical Research Council 

(NHMRC) 1999). Serious complications associated with double contrast barium enema 

(DCBE) also appear rare and have been estimated at 3 per 10,000 tests, with a death rate 

of 3 in 100,000 tests (Winawer et al 1997). 

The Minnesota (US) randomised controlled trial (RCT) of FOBT screening for CRC 

reported a perforation rate of 0.03% (4/12,246) and a rate of serious bleeding of 0.09% 

(11/12,246) in association with colonoscopy (Mandel et al 1993). The Nottingham (UK) 

FOBT trial reported a rate of 0.5% (7/1474) for colonoscopy complications and no 

complications of DCBE, from a total of 1778 subjects receiving follow-up (Robinson et 

al 1999). There were no colonoscopy related deaths reported in either trial. 

Concern has also been expressed about the psychological impact of CRC screening, and 

this is an important issue. However, detailed exploration of this would require a 

dedicated systematic review and a cost-effectiveness comparison incorporating qualityof-life 

measures, which is beyond the scope of this review. 

Faecal occult blood testing xi

The head-to-head studies examining the relative performance of different FOBTs 

identified in this assessment did not report any safety data. Therefore, the performance 

of alternative FOBTs for population health screening cannot be assessed on the basis of 

safety data. 

Effectiveness 

Three head-to-head studies estimated the sensitivity and specificity of various FOBTs 

using the interval cancer rate (ie, the number of cancers that are detected during intervals 

between screening) as a proxy for the false negative rate. This allowed calculation of the 

relative sensitivities and specificities for each of the FOBTs included in these studies. 

Slightly more studies reported data that enabled calculation of the relative true positive 

rate (TPR) and the relative false positive rate (FPR) (ie, the ratio of one test’s TPR or 

FPR to the other) of the FOBTs compared. There were no studies of a suitable quality 

available to enable assessment of the relative accuracy of the different FOBTs for the 

detection of adenomas. 

On the basis of two of these studies, HemeSelect was found to be significantly more 

sensitive than Hemoccult in detecting carcinoma (77.1% vs 30.0%, respectively; risk 

difference (RD) 0.46; 95% confidence interval (CI): 0.231, 0.631). In contrast, the 

Hemoccult test was significantly more specific than HemeSelect (97.8% vs 93.5%, 

respectively; RD –0.043; 95% CI: –0.070, –0.026). This finding was maintained in a 

sensitivity analysis incorporating a study conducted in a population with a high 

proportion of subjects that were at increased risk. Similarly, the TPR was significantly in 

favour of RPHA (HemeSelect and Immudia-HemSp pooled) rather than Hemoccult 

(relative TPR 0.59; 95% CI: 0.39, 0.88), whereas the FPR of Hemoccult was lower than 

that for RPHA (relative FPR 0.53; 95% CI: 0.33, 0.87). Therefore, HemeSelect was more 

effective than Hemoccult at detecting patients with CRC but was not as effective at 

excluding participants without the disease. The practical impact of this trade-off cannot 

be determined by the sensitivity and specificity values alone and has been investigated via 

the use of an economic model in the cost-effectiveness section of this assessment report. 

In a single study, the sensitivity of Hemoccult and Fecatwin Sensitive/Feca EIA were 

not significantly different (50.0% vs 83.3%, respectively; RD 0.33; 95% CI: –0.166, 

0.832). However, Hemoccult was significantly more specific than Fecatwin 

Sensitive/Feca EIA (97.1% vs 92.2%, respectively; RD –0.049; 95% CI: –0.066, –0.032). 

This means that at this time there is no statistically significant evidence to suggest that 

Hemoccult or Fecatwin Sensitive/Feca EIA are better at identifying patients with CRC. 

However, there is statistically significant evidence to suggest that Hemoccult is superior 

at excluding participants without the disease. Similarly, the TPR was not significantly 

different when Hemoccult was compared to Fecatwin Sensitive/Feca EIA (relative TPR 

0.60; 95%CI: 0.14, 2.51). However, the FPR of Hemoccult was significantly lower than 

Fecatwin Sensitive/Feca EIA (relative FPR 0.35; 95% CI: 0.24, 0.51). Therefore, based 

on these limited data, Hemoccult was statistically more accurate than Fecatwin 

Sensitive/Feca EIA, when used for population health screening. It should be noted, 

however, that the subjects in this study were not required to adhere to the dietary 

restrictions generally recommended with the use of a guaiac FOBT. 

The sensitivity of Hemoccult Sensa and HemeSelect were not significantly different 

(79.4% vs 68.8%, respectively; RD –0.107; 95% CI: –0.317, 0.103), based on data from a 

single study. In contrast, HemeSelect proved to be significantly more specific than 

xii Faecal occult blood testing

Hemoccult Sensa (94.4% vs 86.7%, respectively; RD 0.077; 95% CI: 0.068, 0.086). These 

results were maintained in a sensitivity analysis incorporating a study conducted in a 

population with a high proportion of subjects that were at increased risk. Similarly, the 

TPR was not significantly different when Hemoccult Sensa was compared with 

HemeSelect (relative TPR 1.07; 95%CI: 0.70, 1.62). However, the FPR of HemeSelect 

was lower than that of Hemoccult Sensa (relative FPR 2.23; 95% CI: 1.14, 4.37). This 

means that at this time there is no statistically significant evidence to suggest that 

Hemoccult Sensa or HemeSelect are better at identifying patients with CRC. However, 

there is statistically significant evidence to suggest that HemeSelect is superior at 

excluding participants without the disease. Therefore, based on these limited data, 

HemeSelect was statistically more accurate than Hemoccult Sensa, when used for 

population health screening. 

Newer immunochemical tests are currently commercially available. Other FOBTs with 

similar technical characteristics (ie, in vitro diagnostic accuracy for the detection of 

haemoglobin) may provide similar outcomes to those of HemeSelect. However, there is 

currently a lack of evidence for this and the performance of other immunochemical tests 

in the context of population health screening for CRC remains to be determined. 

It is important to note that the measures of the sensitivity and specificity of the FOBTs 

for the detection of CRC varied considerably between studies conducted in different 

populations. In addition, estimates of these measures differed significantly between 

different tests of the same class. Therefore, relative findings for any individual pairs of 

guaiac and immunochemical tests cannot be generalised across comparisons and findings 

for any individual test do not represent all tests of that class. 

A modelled economic evaluation was used to determine the effectiveness and costeffectiveness 

of the different tests in a population screening setting. This model was built 

upon the sensitivity and specificity data summarised above and was able to determine the 

broader population-wide impact of the sensitivity and specificity of these tests. 

Cost-effectiveness 

An economic model was designed to assess the relative cost-effectiveness of various 

FOBTs used to detect CRC in a population health screening setting. Consequently, headto-head 

comparisons between FOBTs are made. It is not intended that decision-makers 

compare tests not compared head-to-head within the economic model. The base-case 

scenario assumes biennial screening in individuals aged 55–74 years. 

The economic model indicates that FOBTs with greater sensitivity for colorectal 

neoplasia detection will offer better overall survival outcomes. A key driver of the 

difference in the total cost associated with the FOBTs is the specificity. Tests with lower 

specificities are associated with higher diagnostic follow-up costs due to the increased 

levels of resource wastage. The model attempts to present the trade-off between these 

values in an economic context by providing estimates of the incremental cost per lifeyear 

gained for each pair of tests compared. 

The incremental cost per life-year gained of HemeSelect was $3172 in a comparison 

against Hemoccult, and $21,533 for Hemoccult Sensa in a comparison against 

HemeSelect. These findings should, however, be constrained to the context of the headto-head 

data upon which they are based. That is, the magnitude of the difference in the 

Faecal occult blood testing xiii

sensitivity between tests contains a level of uncertainty. This is particularly due to the low 

prevalence of CRC in the populations tested in the FOBT studies and the scarcity and 

poor quality of data providing estimates of the sensitivity for adenoma detection. 

Consequently, use of these data in the economic model may render the results of the 

economic model equally uncertain. 

However, the absolute estimates of the difference in specificity between tests are more 

reliable than the estimates of the sensitivity. Similarly, the results concerning costs of the 

FOBTs, inclusive of diagnostic follow-up and treatment, are more reliable than the 

modelled life-expectancy, due to the quality of the estimates that they are based upon. 

Therefore, the tests associated with the higher specificity were shown to be less costly 

overall, with the impact of sensitivity upon effectiveness of uncertain magnitude. This 

implies that the most promising tests in an economic sense may be those associated with 

a high specificity. 

The results of these analyses for the immunochemical tests used may reflect those for 

FOBTs with similar technical characteristics (ie, in vitro diagnostic accuracy for the 

detection of haemoglobin). However, there is currently a lack of suitable comparative 

evidence for the performance of other immunochemical FOBTs in the context of 

population health screening for CRC. 

Other important findings of the economic model include the following. 

• There was no apparent class effect in determining the relative cost-effectiveness of 

different FOBTs. 

• Increasing participation will lead to increased cancer detection and an increase in 

the effectiveness of any screening program. Participation will not, however, have a 

major impact upon the relative cost-effectiveness between different FOBTs as a 

change in participation will shift both costs and effectiveness in the same direction, 

thus having a minimal effect on the incremental cost per life-year gained. 

• Altering key variables endogenous to the screening program generally yielded little 

difference in the relative cost-effectiveness between FOBTs. However, these 

sensitivity analyses did demonstrate consistent trends which provide insight into 

methods that may maximise the cost-effectiveness of screening in comparison with 

no-screening. 

• Increasing the screening frequency from biennial to annual increases both costs 

and effectiveness. Within the context of the main analyses, it appears that annual 

FOBT screening is not cost-effective compared with biennial screening. 

• Changing the minimum eligible screening age from 55 to 50 years appears to offer 

benefits in terms of cost-effectiveness. 

• Increasing the maximum screening age from 75 to 80 years does not appear to 

offer the same degree of benefit. 

It is important to note that the reliability of the above findings is dependent upon the 

reliability of the clinical data available to make head-to-head comparisons between the 

xiv Faecal occult blood testing

FOBTs. An improvement in the quantity, quality and external validity of head-to-head 

study data is required to validate the findings of the economic model. 

Summary of outcomes 

The MSAC considers that faecal occult blood testing is useful for population health 

screening to reduce CRC mortality. 

The available evidence indicated that there was no apparent class effect of the guaiac 

versus immunochemical FOBTs with regard to their effectiveness or cost-effectiveness. 

Different brands of FOBTs possess different sensitivities and specificities for the 

detection of CRC within an average risk screening population setting. The specificity of 

the FOBTs was a major determinant of the total associated costs of FOBT screening, 

inclusive of diagnostic follow-up and treatment. 

An economic model indicated that biennial screening was more cost-effective than 

annual screening, within the context of the main analysis. Lowering the minimum eligible 

screening age from 55 to 50 years offered benefits in terms of cost-effectiveness. 

Increasing the maximum screening age from 75 to 80 years did not offer the same degree 

of benefit. 

The immunochemical tests included in the assessment are no longer available and they 

have been replaced by newer assays. There was no available evidence suitable for the 

assessment of the comparative performance of currently available immunochemical tests 

within an average risk population health screening setting. However, the results of the 

analyses of the immunochemical tests used may reflect those for FOBTs with similar 

technical characteristics (ie, in vitro diagnostic accuracy for the detection of haemoglobin). 

Therefore, it is suggested that currently available and new immunochemical tests with 

promising technical characteristics be evaluated against established FOBTs within the 

context of an ongoing screening program. 

Faecal occult blood testing xv

Introduction 

The Medical Services Advisory Committee (MSAC) has undertaken a review to provide 

advice on the use of different commercially available faecal occult blood tests (FOBTs) 

for population screening in Australia. 

MSAC evaluates new and existing health technologies and procedures for which funding is 

sought under the Medicare Benefits Scheme in terms of their safety, effectiveness and costeffectiveness, 

while taking into account other issues such as access and equity. MSAC 

adopts an evidence-based approach to its assessments, based on reviews of the scientific 

literature and other information sources, including clinical expertise. 

MSAC’s terms of reference and membership are at Appendix A. MSAC is a 

multidisciplinary expert body, comprising members drawn from such disciplines as 

diagnostic imaging, pathology, surgery, internal medicine and general practice, clinical 

epidemiology, health economics, consumer health and health administration. 

This review was undertaken to provide support to the Australian Government Bowel 

Cancer Screening Pilot Program (the pilot). The primary aim of the pilot is to provide 

information about the feasibility, acceptability and cost-effectiveness of FOBT screening 

amongst the Australian population in both rural and urban areas. The results of the pilot 

will inform decisions about whether, and how, to introduce a national bowel cancer 

screening program. 

This report summarises the assessment of the relative performance and costeffectiveness 

of commercially available FOBTs for population health screening. This 

report also provides suggestions as to the most promising FOBTs available at this time 

and the most cost-effective setting for FOBT screening. 

Faecal occult blood testing 1

Background 

Faecal occult blood testing 

Description of the technology and the procedure 

Faecal occult blood tests (FOBTs) are used to detect blood in faeces that is not obvious 

by general inspection (ie, occult blood). This technology has been utilised for both 

diagnostic and screening purposes; however, the purpose of this review is to investigate 

the relative performance of different FOBTs for population health screening. 

In general, FOBTs involve sample preparation prior to colorimetric visualisation. This 

may be conducted in the home, clinician’s office or a pathology laboratory. The most 

accepted regimen for faecal occult blood testing involves testing two faecal samples from 

each of three stools over three consecutive days. There are several alternative sampling 

methods associated with faecal occult blood testing. These include utilising either a 

wooden spatula or a brush, methods which involve a different degree of stool handling. 

The samples are then usually transferred onto a sample card which can be delivered by 

post to the appropriate location for development and interpretation. A single positive 

sample in the series is counted as a positive result. A high roughage diet is sometimes 

recommended prior to conducting the tests, in order to uncover lesions that bleed 

intermittently. FOBTs should not be conducted whilst the subject is experiencing 

menstrual or peri-anal bleeding. 

There are two types of FOBTs in common use: the long established guaiac tests and the 

newer immunochemical tests. 

Guaiac FOBTs 

The guaiac FOBTs act by detecting the intact haem molecule from haemoglobin. These 

tests are simple-to-perform colorimetric tests, often conducted in the home. Two small 

samples from stools obtained on three consecutive days are applied to a piece of paper 

impregnated with the guaiac gum. Upon application of a developing solution, the 

presence of trace amounts of haem results in a blue colour change due to the pseudoperoxidase 

actions of haem. Guaiac FOBTs are able to detect bleeding originating 

anywhere between the mouth and anus. However, the sensitivity of guaiac FOBTs for 

detecting upper gastrointestinal (GI) bleeding is less than for the lower GI tract. 

The accuracy of guaiac FOBTs can be affected by medications (eg, non steroidal antiinflammatory 

drugs (NSAIDs), anticoagulants, iron supplements), contamination of the 

sample with toilet water, time delay between sample collection and developing, and 

dietary factors (eg, haem in meat or peroxidases or catalases in many fresh fruits or 

vegetables or rare red meat). Since the tests are dependent upon the pseudo-peroxidase 

activity of haem, false negative tests will arise from excessive amounts of reducing agents 

in faecal samples (eg, vitamin C). Hydration of faecal samples is also known to increase 

test sensitivity with a loss of specificity. Delaying the development of the test for a few 

days after the collection of the sample minimises the effects of dietary peroxidases on 

test results; however, this may also diminish the chance of detecting a weak positive 

result. 

2 Faecal occult blood testing

The guaiac FOBTs include brand names such as: Hemoccult, Hemoccult Sensa, Hemo 

FEC, Coloscreen, Fecatest (discontinued) and Shionogi B. 

Immunochemical FOBTs 

The immunochemical FOBTs involve the use of an anti-human monoclonal antibody, 

targeted at intact human blood-borne proteins (usually haemoglobin). These tests 

therefore have the theoretical advantage of not being affected by haem, peroxidases or 

anti-oxidases in the diet. In addition, immunochemical tests will not detect proximal 

bleeds, since in this case haemoglobin is digested before being passed in the faeces. 

However, these tests are generally more complex and expensive than the guaiac tests and 

often require laboratory processing. 

The immunochemical FOBTs include brand names such as: HemeSelect (discontinued) 

and Immudia-HemSp (international equivalents) (Young 1998), FlexSure OBT 

(discontinued), Magstream HemSp, Bayer Detect, Quicktest, DIMA FOB-10, !nSure, 

!nForm and BM-Test Colon Albumin. HemeSelect and Immudia-HemSp are reverse 

passive haemagglutination (RPHA) tests. These RPHA tests use chicken-erythrocytes 

coated with antibodies to human haemoglobin. The coated chicken-erythrocytes are 

agglutinated in the presence of haemoglobin in human faecal samples. HemeSelect, 

Immudia-HemSp, !nSure and FlexSure OBT utilise an anti-human monoclonal antibody 

to haemoglobin. BM-Test Colon Albumin utilises an antibody specific for human 

albumin. 

Two-tier tests 

There have been suggestions of using a “two-tier” approach to faecal occult blood 

testing, where a guaiac and then an immunochemical test are used in sequence for 

colorectal cancer (CRC) screening. This approach has been developed in response to the 

high positivity rates of some guaiac FOBTs. Following positive results from a highly 

sensitive guaiac test with an immunochemical test should increase specificity and reduce 

the associated high rates of unnecessary diagnostic follow-up. Studies using Hemoccult 

Sensa and HemeSelect in such a two-tier approach have been conducted (Allison et al 

1996; Rae and Cleator 1994). 

Fecatwin Sensitive/Feca EIA was a combination of a guaiac and immunochemical test 

performed in two-tiers. Samples were initially screened with the Fecatwin Sensitive guaiac 

test and then positive samples were tested with the Feca EIA immunochemical test. This 

test is no longer commercially available. 

Intended purpose 

For diagnostic purposes, the use of both a guaiac and an immunochemical test together 

has been suggested, to differentiate between upper and lower GI tract bleeding. 

However, the purpose of this review is to investigate the relative effectiveness of 

different commercially available FOBTs when used for population health screening. The 

diagnostic use of FOBTs would need to be examined in a separate review. 

FOBTs are used as a screening test for the identification of CRC. This is based on the 

use of faecal occult blood as a marker for CRC. However, an inherent problem with the 

technology is that many other non-neoplastic disease processes can cause GI bleeding. 

Therefore, the sensitivity and specificity of a test for the detection of blood will not 


necessarily translate into equivalent accuracy for the detection of CRC in a population 

health screening setting. Positive FOBT results due to other GI diseases will give a 

reduction in the expected specificity of the technique as a CRC screening measure. 

Immunochemical tests are expected to be less susceptible than guaiac tests to this effect, 

since only lower GI bleeding will be detected. Therefore, the key issue to be addressed in 

this review is the relative performance of guaiac versus immunochemical FOBTs when 

used for population health screening. 

GI bleeding, particularly from the upper GI tract, may be caused or exacerbated by the 

intake of medications such as NSAIDs and anticoagulants. Pathophysiological causes of 

GI bleeding are diverse in nature and may include: ulcers and erosions; haemorrhoids; 

fissures (perianal disease); colitis; diverticulitis; vascular ectasia/angiodysplasia; radiation 

mucosal injury; previous gastric surgery; inflammation; polyps; and cancer of the colon. 

The most common sources of occult bleeding detected by FOBTs are colonic adenomas 

≥ 1 cm (12−14%), peptic ulcer disease (7−10%), oesophagitis (6−9%), colon carcinoma 

(5−6%) and angiodysplasia (3−13%) (Zuckerman et al 2000). Fifteen to 20 per cent of 

peptic ulcer patients experience bleeding, particularly in association with the use of 

NSAIDs and Helicobacter pylori infection (Kurata et al 1982; Hawkey 2000). In a series of 

reflux oesophagitis patients, 8.2 per cent experienced bleeding, primarily in those with 

severe disease (Costa et al 2001). In elderly patients, a major source of lower GI bleeding 

is angiodysplasia; however, rare types of congenital or hereditary vascular ecstasia also 

occurs in younger patients (Sharma and Gorbien 1995). Haemorrhoids are not readily 

detected by FOBTs and it was suggested that this was due to bleeding being intermittent 

or not adherent to the particular region of sample used for testing (Nakama et al 1997). 

Studies have estimated that 50–60 per cent of CRCs are likely to bleed. Overall, 11 per 

cent of adenomatous polyps have a propensity to bleed with larger adenomas (≥ 1.5 cm) 

the most likely to bleed (Foutch et al 1998; Simon 1985). Therefore, the use of FOBTs as 

a screening measure to detect early colorectal neoplasia has been widely investigated. 

A meta-analysis of mortality results from randomised controlled trials (RCTs) showed 

that people allocated to FOBT screening (Hemoccult, a guaiac test) had a relative risk 

reduction in CRC mortality of 16 per cent (relative risk 0.84; 95% confidence interval 

(CI): 0.77, 0.89) (Towler et al 1998). A comprehensive discussion of many of the issues 

surrounding the use of FOBT as a CRC population health screening test has recently 

been published by Allison (2003). 

Clinical need/burden of disease 

Colorectal polyps may be hyperplastic or adenomatous. Hyperplastic polyps do not 

develop into carcinomas. However, a proportion of adenomatous polyps (adenomas) will 

become malignant. Approximately 10 per cent of adenomas greater than 1 cm in size will 

become cancerous within 10 years, and a lesser proportion of smaller adenomas (Stryker 

et al 1987). The majority of CRC develops from adenomas. Therefore, detection and 

resection of neoplasms at this precancerous stage would effectively reduce the incidence 

of CRC (Winawer et al 1993). 


Classification of CRC may be by one of several staging systems. The first well described 

and widely used staging system was Dukes’ staging of the extent of tumour spread. 

Dukes’ stages A–D correspond to a localised tumour, a localised tumour which has 

spread beyond the muscularis propria, a localised tumour associated with lymph node 

involvement and a tumour associated with metastases, respectively. The pathological 

staging system (pTNM) designates four stages I–IV, which differs from Dukes’ staging 

only in regard to the fact that classification as stage IV is not dependent upon the 

presence of tumour in a line of resection. 

Incidence of colorectal cancer 

CRC is the most common type of cancer in Australia, aside from non-melanocytic skin 

cancer, with 12,405 cases being diagnosed in 2000 (Australian Institute of Health and 

Welfare (AIHW) and Australasian Association of Cancer Registries (AACR) 2003). Of 

these, 6863 patients were men, equating to an age-standardised rate of 80.2/100,000, and 

the remaining 5542 were women, equating to an age-standardised rate of 53.8/100,000. 

Hence, the incidence of CRC in 2000 was second only to prostate cancer in Australian 

men and to breast cancer in Australian women (again, excluding non-melanocytic skin 

cancer). 

Mortality due to colorectal cancer 

Early stage disease usually responds well to surgery. However, the prognosis for 

metastatic disease is poor. Approximately 4718 people died from CRC in Australia in 

2000, making it second only to lung cancer as a cause of cancer deaths nationally in 2000 

(AIHW and AACR 2003). Approximately 5 per cent of Australians develop CRC during 

their lifetime and half of these people die from the disease within five years of diagnosis. 

Existing procedures 

Many procedures are available to detect malignancies in the colon and rectum. These 

include: colonoscopy, sigmoidoscopy, double contrast barium enema (DCBE) and more 

recently, virtual colonoscopy (thin-section helical computerised tomography). The ‘goldstandard’ 

diagnostic procedure for the investigation of CRC is colonoscopy, which 

enables examination of the full length of the colon by endoscopy under sedation. 

Sigmoidoscopy is used for examination of the rectum and sigmoid (descending) colon, 

but not the ascending or transverse colon. Flexible sigmoidoscopy allows examination of 

a greater extent of the bowel than rigid sigmoidoscopy and is superior in terms of patient 

comfort. DCBE does not visualise the rectum and rectosigmoid region well and is more 

likely to miss a Dukes’ A cancer than colonoscopy (National Health and Medical 

Research Council (NHMRC) 1999). Virtual colonoscopy uses computed tomography 

scanning to obtain two-dimensional images, which are reconstructed into threedimensional 

images with the use of advanced software. The resulting images simulate the 

endoluminal view of the colorectum seen at colonoscopy without the need for an 

invasive procedure. 

In general, these diagnostic modalities are more accurate than the FOBTs. However, 

these procedures are less practical options for use in a population-screening program due 

to their high level of invasiveness, their acceptability to the general public, and their cost. 


Reference standard 

It is mandatory that any positive FOBT be investigated by an appropriate diagnostic 

procedure. The ‘gold-standard’ diagnostic procedure and the procedure of choice for this 

investigation is colonoscopy. If the colonoscopy is ‘incomplete’, then a DCBE is 

generally used to ensure complete visualisation of the colon (NHMRC 1999). A DCBE 

plus flexible sigmoidoscopy may replace the colonoscopy if there are difficulties with 

local availability or expertise, or if the patient prefers (NHMRC 1999). 

Comparator 

Since this report focuses on the relative effectiveness of different commercially available 

FOBTs and not the absolute effectiveness of these tests, the comparators identified for 

this evaluation are the other FOBTs that have been or are currently commercially 

available. 

Marketing status of the technology 

The guaiac FOBTs include brand names such as: Hemoccult (Beckman Coulter Inc, 

USA), Hemoccult Sensa (Beckman Coulter Inc, USA), Hemo FEC (Roche Diagnostics, 

Switzerland), Coloscreen (Helena Laboratories, USA), Fecatest (Nordic Products, 

Scandinavia) and Shionogi B (Shionogi Pharmaceutical Co, Japan). SmithKline and 

French Laboratories first produced the Hemoccult brand in 1970, and the currently 

marketed version of this product is Hemoccult II, produced by Beckman Coulter Inc. 

The two versions of this test differ only with regard to their configuration (Mandel et al 

1989), therefore this document will refer to both versions simply as Hemoccult, without 

differentiation. Hemoccult Sensa was produced in 1982 by the same company as an 

enhanced Hemoccult product and is currently marketed as Hemoccult II Sensa. 

Beckman Coulter Inc. has also recently marketed the Hemoccult II Sensa elite FOBT. 

Fecatest does not appear to be currently commercially available. 

The immunochemical FOBTs include brand names such as: HemeSelect, Immudia- 

HemSp, Bayer Detect and Magstream HemSp (Fujirebio Inc, Japan); FlexSure OBT 

(Beckman Coulter Inc., USA); Quicktest (Laboratory Diagnostics, Australia); DIMA 

FOB-10 (Asquith Laboratories, Australia); !nSure (Enterix Inc., USA); !nForm (Enterix 

P/L, Australia) and BM-Test Colon Albumin (Boehringer Mannheim, Germany). 

Immudia-Hem Sp was originally developed and marketed in Japan. HemeSelect 

(discontinued) is the international equivalent of Immudia-Hem Sp (Young 1998). 

FlexSure OBT was previously available commercially; however, sales have been 

discontinued. BM-Test Colon Albumin is now produced by Roche Diagnostics. 

The two-tiered FOBT, Fecatwin Sensitive/Feca EIA (Nordic Products) does not appear 

to be currently commercially available. 


Current reimbursement arrangement 

FOBTs are currently reimbursed on the Medicare Benefits Scheme (MBS). 

The current wording of the listing of FOBTs on the MBS for item number 66764 is: 

“Examination for faecal occult blood (including tests for haemoglobin and its 

derivatives in the faeces) by: (a) an immunological method; and (b) a chemical 

method (except reagent strip or dip stick); with a maximum of 3 examinations 

on specimens collected on separate days in a 28-day period - 1 examination by 

both methods.” 

Item numbers 66767 and 66770 cover two and three examinations (respectively) 

by both methods described in item 66764, performed on separately collected and 

identified specimens. 

The current wording for item number 73809 is: 

“Chemical tests for occult blood in faeces by reagent stick, strip, tablet or similar 

method.” 


Approach to assessment 

It has been argued that determining person-centred outcomes (eg, mortality) is the 

ultimate purpose of performing a test, and that the strongest evidence should come from 

randomised controlled trials (RCTs). Therefore, the important effects of the range of 

available faecal occult blood tests (FOBTs) should ideally be measured in a series of 

person-centred outcomes in RCTs. Level I evidence (ie, a systematic review of all 

relevant RCTs) shows that people allocated to FOBT screening (Hemoccult, a guaiac 

test) have a relative risk reduction in colorectal cancer (CRC) mortality of 16 per cent 

(relative risk 0.84; 95% confidence interval (CI): 0.77, 0.89) (Towler et al 1998). However, 

it is unlikely that every new FOBT will be included in an RCT, or that patient-centred 

outcomes will be collected for each test. 

Therefore, this assessment report focuses on the review of head-to-head studies of 

FOBTs in ‘average risk’ general population subjects. These studies usually report 

outcomes such as the number of patients detected with CRC or adenoma(s) rather than 

CRC mortality. These studies are likely to provide the most robust estimate of the 

relative performance of commercially available FOBTs for population health screening 

(Cochrane Methods Group on Systematic Review of Screening and Diagnostic Tests 

1996). 

Review of literature 

Search strategy 

The medical literature was searched to identify relevant studies and reviews for the 

period to February 2004. Searches were conducted via the following primary databases: 

• Medline 1966 to current 

• Embase 1980 to current 

• Econlit 1969 to current. 

The search terms used included the following: 

• occult blood; faecal blood; faecal haemoglobin; faecal globin; faecal haem 

• fobt; hemeoccult; haemoccult; fecatwin; colocare; okokit; hemofec; flexsure; 

hemeselect; feca-eia; iatrohemcheck; imdiahem; hemochaser; monohaem; hemodia; 

hemoglobin; annual bowel check; haptoglobin; guaiac; immunochemical test; elisa; 

inform 

• mass screening 

• colorectal neoplasms. 

Complete details of the literature searches performed using the Medline and Embase 

databases are presented in Appendix D. 


Searches of the following secondary databases/sites were also performed: 

• British Columbia Office of Health Technology Assessment 

• Canadian Coordinating Office for Health Technology Assessment (CCOHTA) 

• Centre for Health Program Evaluation (Monash University, Australia) 

• Cochrane Library database 

• Danish Centre for Evaluation and Health Technology Assessment (DACEHTA) 

• Health Economics Research Group (Brunel University, UK) 

• Health Information Research Unit (HIRU) internal database (McMaster University, 

Canada) 

• International Standard Randomised Controlled Trial Number (ISRTCN) register 

(BioMed Central) 

• National Cancer Control Initiative (NCCI) publication list 

• National Health and Medical Research Council (NHMRC) Australia publication list 

• National Health Service Centre for Reviews and Dissemination databases (NHS 

CRD), including the Database of Abstracts of Reviews and Effects (DARE), the 

National Health Service Economic Evaluation Database (NHSEED) and the Health 

Technology Assessment (HTA) database (University of York, UK) 

• National Information Center on Health Services Research and Health Care 

Technology, the Health Services Technology Assessment Texts (HSTAT) database 

(US) 

• Swedish Council on Technology Assessment in Health Care (SBU) 

• US Preventative Services Task Force (USPSTF). 

Other information sources used to gain relevant data included: 

• market assessments and economic evaluation reports 

• Therapeutic Goods Administration (TGA) 

• content experts. 


Selection criteria 

The ideal study design for a study of the accuracy of diagnostic tests is that in which each 

test being compared is performed in all individuals. In addition, for the generalisability 

and external validity of studies being assessed to apply to the Australian population, 

studies must be performed in a screening population, rather than a hospital-based highrisk 

population. For this reason the inclusion and exclusion criteria were as follows. 

Inclusion criteria 

• All human head-to-head studies comparing at least two FOBTs that have been, or 

are currently, commercially available. 

• Population health screening studies. 

• Use of an appropriate reference standard (eg, colonoscopy and/or double contrast 

barium enema (DCBE) where colonoscopy is incomplete or contra-indicated). 

Exclusion criteria 

• Trials with fewer than 100 patients. 

• Non-systematic reviews and opinion pieces. 

• Non-comparative studies. 

The flow chart in Figure 1 summarises the exclusion of studies from the safety and 

effectiveness review of FOBTs. A total of 1214 references were identified by the search, 

of which 30 met the criteria to be considered as evidence in the effectiveness review. A 

complete list of the citations identified in the literature search, identified as FOBT studies 

and later excluded at higher levels is included in Appendix E, together with reasons for 

exclusion from the review. 

Publications that duplicated all or some of the patient data were included in the first 

instance. They were then reviewed, and excluded if necessary. Publications that failed to 

report outcomes adequately (eg, sensitivity, specificity, true positive rates, false positive 

rates, positive predictive value) were also excluded after review. 


Identified by the search 

(n = 1214) 

Original studies 

(n = 726) 

Original in vivo human studies 

(n = 714) 

Original in vivo human studies of 

FOBT 

(n = 229) 


FOBT in population health 


(n = 177) 



screening with appropriate 

reported outcomes 

(n = 123) 



screening in ≥100 individuals 

(n = 123) 

Original in vivo human 

head-to-head studies of FOBT 

in population health screening 

in ≥ 100 individuals 

(n = 30) 

Figure 1 Reasons for exclusion of published studies of FOBT identified by the literature search 

Abbreviations: FOBT, faecal occult blood test. 

Excluded if a nonsystematic 

review, editorial, 

letter, news article, note, 

survey, opinion piece or 

economic analysis 

(n = 488) 

Excluded if non-human or 

in vitro study 

(n =12) 

Excluded if the study was 

not of FOBT 

(n = 485) 

Excluded if the study was 

not a population health 

screening study 

(n = 52) 

Excluded if inappropriate 

FOBT usage or outcomes 

(n = 54) 

Excluded if < 100 screened 

individuals 

(n = 0) 

Excluded if not a 

head-to-head study of 

two different FOBTs 

(n = 93) 

Available 

evidence initially 

included in the 

the review of 

comparative 

FOBT 

effectiveness 

(n = 30) 


Quality assessment 

The evidence presented in the selected studies was assessed and classified using the 

hierarchy of evidence for screening tests defined by the New Zealand Health Technology 

Assessment group (NZHTA) (Broadstock 2000). The designations of the hierarchy of 

evidence are shown in Table 1. 

Table 1 Hierarchy of evidence 

Level of 

evidence 

1 All tests done on each person (within-subjects design) 

Study design 

2a Different tests done on randomly allocated individuals (between subjects design, randomised controlled trial) 

2b Different tests done on randomly allocated groups (between-subjects design) 

3a Different tests done on different individuals, not randomly allocated, and recruited concurrently (between 

subjects design) 

3b Different tests done on different individuals, not randomly allocated, with historical cohort (between subjects 

design) 

Source: Broadstock (2000). 

A more detailed assessment of study quality was undertaken using a modification of the 

diagnostic-specific checklist published by the Cochrane Screening and Diagnostic Tests 

Methods group (Cochrane Methods Group on Systematic review of Screening and 

Diagnostic Tests 1996). Where a study contained one or more components, the 

assessment of quality was only of the component used in this assessment. Two 

evaluators independently scored each of the included studies, with discrepancies resolved 

by discussion and consensus. This enabled a quality score to be assigned to each study. 

Details of the checklist and scoring are provided in Appendix H. 

Other important information that was assessed included: 

• appropriateness of screening population to proposed population 

• appropriateness of the test to proposed indication (eg, timing of FOBT) 

• appropriateness of screening method/intervention used 

• appropriateness of outcome measurement (eg, sensitivity specificity, etc.) 

• strength and magnitude of screening effect. 

Additional searches 

Additional searches were conducted to examine the following: 

• psychological impact of faecal occult blood testing 

• economic evaluations of FOBTs 

• information required for the modelled economic evaluation. 


Expert advice 

An advisory panel with expertise in epidemiology, gastroenterology, pathology and 

gastrointestinal surgery was established to evaluate the evidence and provide advice to 

the Medical Services Advisory Committee (MSAC) from a clinical perspective. In 

selecting members for advisory panels, the MSAC’s practice is to approach the 

appropriate medical colleges, specialist societies and associations and consumer bodies 

for nominees. Membership of the advisory panel is provided at Appendix B. 


Results of assessment 

Faecal occult blood testing 

Available evidence 

Head-to-head studies 

Table 2 shows the 30 head-to-head studies of faecal occult blood tests (FOBTs) 

performed in a screening setting that were identified in the literature search. Five of these 

studies described duplicate data and were excluded from further analysis (Armitage and 

Hardcastle 1987; Castiglione et al 1996; Hardcastle et al 1986; Robinson et al 1995; 

Walter et al 1991). One study could not be obtained (Aisawa et al 1988). One study did 

not utilise an appropriate reference standard (Vaananen and Tenhunen 1988). Four other 

studies were excluded due to inadequate data separation (Cole et al 2003; Lee and 

Costello 1982; Li et al 2000; Winawer et al 1980a). One study was excluded because a 

large portion of the included patient population was symptomatic (Rae and Cleator 

1994). One study was excluded as the immunochemical test studied was never 

commercially produced (Frommer et al 1988). Three other studies were excluded from 

the assessment as data enabling calculation of a suitable outcome measure were not 

reported (Kettner et al 1990; St John and Young 2003; Verne et al 1993). Fourteen headto-head 

studies remained for evaluation of the effectiveness of faecal occult blood 

testing. 

Table 2 Head-to-head studies of FOBT in screening populations 

Trial Trial design Reviewed for 

effectiveness 

assessment 

Reviewed for 

safety 

assessment 

Aisawa et al 1988 Unavailable x x 

Allison et al 1996b Prospective, single group, with each participant receiving 

multiple FOBTs 

� � 

Armitage et al 1985 Prospective, parallel-arm, patients randomly assigned to two 

sequential FOBTs or control group 

Armitage and 

Hardcastle 1987 

Barrison and 

Parkins 1985a 

Castiglione et al 

1996 

Castiglione et al 

1997 

Prospective, parallel-arm, patients randomly assigned to two 

sequential FOBTs or control group (cohort of large RCT) 

Prospective, single group, with each participant receiving 

multiple FOBTs (GP group) 





Cole et al 2003 Prospective, parallel arm, patients randomly assigned to one 

of three FOBTs 

Frommer et al 1988 Prospective, single group, with each participant receiving 


� � 

x � 

� � 

x � 

� � 

x � 

x � 

Fujita et al 1992 Parallel arm, with historical cohort � � 

Hardcastle et al 

1986 

Prospective, parallel-arm, patients randomly assigned to two 

sequential FOBTs or control group (group 2, cohort of large 

RCT) 

x � 


Trial Trial design Reviewed for 

effectiveness 

assessment 

Iwase 1992 Prospective, single group, with each participant receiving 


Kettner et al 1990 Prospective, single group, with each participant receiving 


Lee and Costello 

1982 


multiple FOBTs (groups 1 & 2) 

Levin et al 1997 Prospective, single group, with each participant receiving 


Li et al 2000 Prospective, single group, with each participant receiving 


Petrelli et al 1994 Prospective, single group, with each participant receiving 


Rae and Cleator 

1994 

Robinson et al 

1995 

Robinson et al 

1996 


multiple FOBTs (arm 2) 




multiple FOBTs (study 1) 

Rozen et al 1995 Prospective, single group, with each participant receiving 






St John et al 1993 Prospective, single group, with each participant receiving 


St John and Young 

2003 

Vaananen and 

Tenhunen 1988 

Prospective, randomised, with cross-over between dietary 

restriction and no dietary restriction, with each participant 

receiving multiple FOBTs 


multiple FOBTs (healthy subject group) 

Verne et al 1993 Prospective, parallel-arm, patients randomly assigned to one 

of three FOBTs with or without dietary restriction 

Walter et al 1991 Prospective, single group, with each participant receiving 


Winawer et al 

1980b 

Prospective, pseudo randomised to control or intervention 

groups, with different FOBTs received over different times 

periods 

Zappa et al 2001 Different tests performed on non-randomly allocated 

individuals, with the likelihood of receiving different tests 

changing over time as immunochemical tests are introduced 

Abbreviations: GP, general practice; FOBT, faecal occult blood test; RCT, randomised controlled trial. 

Reviewed for 

safety 

assessment 

� � 

x � 

x � 

� � 

x � 

� � 

x � 

x � 

� � 

� � 

� � 

� � 

� � 

x � 

x � 

x � 

x � 

x � 

� � 


Is it safe? 

Adverse events associated with faecal occult blood tests 

FOBTs are non-invasive and therefore unlikely to cause adverse events. However, the 

use of FOBTs in a screening setting is likely to increase the number of colonoscopies, 

sigmoidoscopies and barium enemas performed in the screened population. Therefore, 

the increased numbers of adverse events associated with these procedures are important. 

The rates of adverse events associated with colonoscopy, sigmoidoscopy and double 

contrast barium enema (DCBE) are discussed below. 

Adverse events associated with colonoscopy, sigmoidoscopy and double contrast 

barium enema 

Colonoscopy is performed as a day-case procedure and generally requires sedation. In a 

study of colonoscopy data over a five-year period, diagnostic colonoscopy was associated 

with a complication rate of 0.14 per cent, compared with a rate of 1.8 per cent for 

therapeutic colonoscopy (Reiertsen et al 1987). In a 1997 review of six prospective 

studies it was estimated that around 1 in 1000 patients suffer perforation, 3 in 1000 suffer 

major haemorrhage and between 1 and 3 in 10,000 die as a result of colonoscopy 

(Winawer et al 1997). A 1989 review of nine studies of diagnostic colonoscopy gives a 

slightly higher figure of around 1.7 in 1000 patients suffering perforation and similar 

figures for haemorrhage and death (Habr-Gama and Waye 1989). The risk of perforation 

and haemorrhage increased with the performance of polypectomy. There are also other 

occasional serious complications associated with bowel preparation prior to colonoscopy 

or the use of sedation in conjunction with this procedure (National Health and Medical 

Research Council (NHMRC) 1999). 

Perforation rates associated with sigmoidoscopy are low and occur in fewer than 2 cases 

per 10,000 examinations (NHMRC 1999). Sedation is not generally used during 

sigmoidoscopy. 

DCBE is performed as an outpatient procedure. Sedation is not used. Serious 

complications are rare and include bowel perforation and cardiac complications. The 

complication rate of DCBE has been estimated at 3 per 10,000 tests, with a death rate of 

3 in 100,000 tests (Winawer et al 1997). 

The Minnesota (US) randomised controlled trial (RCT) of FOBT screening for colorectal 

cancer (CRC) reported safety outcomes relevant to population health screening. This 

study utilised the Hemoccult test in combination with appropriate dietary restrictions. 

A perforation rate of 0.03% (4/12,246) and a rate of serious bleeding of 0.09% 

(11/12,246) were reported in association with colonoscopy (Mandel et al 1993). All 

four instances of perforation, and three of the eleven cases of serious bleeding, required 

surgery. 

The Nottingham (UK) FOBT trial reported complication rates in a smaller sample 

of colonoscopies. This study also used the Hemoccult test in combination with 

dietary restrictions. In this study, a rate of 0.5% complications of colonoscopy and 

no complications of DCBE from a total of 1778 subjects receiving follow-up was 


eported (Robinson et al 1999). Of the seven patients experiencing complications 

associated with colonoscopy (7/1474), six required surgery. There were no colonoscopyrelated 

deaths reported in either study. 

Psychiatric morbidity associated with colorectal cancer screening 

Concern has been expressed about the psychological impact of CRC screening, 

particularly for the group of participants that return false positives results. A recent 

publication by Parker et al (2002) investigated the psychiatric morbidity associated with 

CRC screening in an RCT. The RCT aimed to determine: (a) whether the offer of faecal 

occult blood testing caused increased, sustained anxiety; (b) whether the existence of 

psychiatric morbidity was a factor in the decision to accept or refuse screening; and (c) 

the anxiety levels of participants returning positive FOBTs at screening, clinical 

investigation and follow up. 

The study found that participation in a faecal occult blood screening program for CRC 

did not cause sustained anxiety or psychiatric morbidity. The study also showed that a 

positive screening result caused short-term anxiety in most subjects, but this returned to 

a lower level one month after clinical investigation (anxiety was measured on the 

Spielberger anxiety inventory). Similarly, the study showed no sustained anxiety in 

participants returning false positive results. This is important, as it has been suggested 

that the high false positive rate in faecal occult blood screening will undermine public 

confidence in the screening programs. In fact, when questioned one month after 

investigation, 85 per cent of participants stated that they would accept screening if it was 

offered again in 2 years. 

Another trial that investigated the experiences of participants receiving false positive 

results from CRC screening found that 26 per cent were quite distressed or very 

distressed from the initial false positive result (Mant et al 1990). The remaining 74 per 

cent of patients were slightly distressed or not at all distressed regarding the false positive 

FOBT result. A total of 98.1 per cent of the participants returning false positive results in 

this study believed that it was worthwhile having the test. 

This is an important issue; however, exploration of this in detail would required a 

dedicated systematic review and exploration via a cost-effectiveness comparison 

incorporating quality-of-life measures, which is beyond the scope of this review. 

Safety data reported in the FOBT studies 

The head-to-head studies examining the relative performance of different FOBTs 

identified in this assessment did not report any safety data. 


Is it effective? 

Diagnostic performance 

This assessment report focuses on the relative effectiveness of the different commercially 

available FOBTs in the screening setting. Table 3 presents the characteristics of the 14 

head-to-head studies of FOBT identified in the literature search and subsequently 

determined as suitable for inclusion. Each study was rated according to a hierarchy of 

evidence for screening tests as described by the New Zealand Health Technology 

Assessment (NZHTA) group (Broadstock 2000). Each trial was evaluated for quality 

using a quality-scoring checklist based on the recommendations of the Cochrane 

collaboration (see Appendix H). 

Five studies compared Hemoccult to HemeSelect (Allison et al 1996; Castiglione et al 

1997; Petrelli et al 1994; Robinson et al 1996; Rozen et al 1997). Four studies compared 

Hemoccult Sensa to HemeSelect (Allison et al 1996; Petrelli et al 1994; Rozen et al 1997; 

St John et al 1993). One study compared Hemoccult to Fecatwin (guaiac) (Barrison and 

Parkins 1985) and another to Fecatwin Sensitive/Feca EIA (Armitage et al 1985). Single 

studies were also identified that compared: Hemoccult with Flexsure OBT (Rozen et al 

1997); Hemoccult Sensa with Flexsure OBT (Rozen et al 2000); Hemoccult with 

Immudia-HemSp (Iwase 1992); Shionogi B with Immudia-HemSp (Fujita et al 1992); 

Hemoccult Sensa with BM-Test Colon Albumin (Rozen et al 1995); Hemoccult with 

Hemoccult Sensa (Levin et al 1997) and; Hemoccult with RPHA tests (Zappa et al 2001). 

Twelve studies represented level 1 evidence according to the evidence hierarchy designed 

for the assessment of studies of screening tests (Broadstock 2000). Two studies were 

rated as level 3b evidence and were excluded from further review due to poor study 

quality (Fujita et al 1992; Zappa et al 2001). Since the key issue to be addressed in this 

review is the relative performance of guaiac versus immunochemical FOBTs when used 

for population health screening, studies that made comparisons between different types 

of guaiac tests were also excluded from further review (Barrison and Parkins 1985; Levin 

et al 1997). In addition, a single study that examined the use of rehydrated Hemoccult 

was excluded from the analysis (Castiglione et al 1997). Nine studies remained for review. 

Studies conducted in screening populations that included a high proportion of patients at 

increased risk were included in sensitivity analyses of estimates of test sensitivity, 

specificity and positive predictive value (Rozen et al 1995; Rozen et al 1997; Rozen et al 

2000; St John et al 1993). 

In accordance with the inclusion criteria, all studies were head-to-head studies conducted 

in ‘average risk’ general population subjects which utilised an appropriate reference 

standard. The included studies all used a within-subjects design. Outside of these 

parameters, many of the included studies had quality limitations. All of the studies had 

received industry support in some form. All of the studies included in the main analyses 

were prospectively designed. However, it is unclear whether or not the studies by Rozen 

et al, which are included in the sensitivity analyses, were prospectively designed (Rozen et 

al 1995; Rozen et al 1997; Rozen et al 2000). 

An inherent problem with screening studies, including all of the studies in this 

assessment, is the issue of verification bias. In studies of screening tests it is generally 


unacceptable and unethical to subject asymptomatic people with a negative test to what 

may be a battery of invasive, time-consuming, and costly clinical investigations. 

Therefore, the use and measurement of the reference standard was not independent of 

the test results. In only one of the studies (Allison et al 1996) were results of the different 

FOBTs determined in a blinded fashion. In addition, the selection of subjects in the 

included trials was not reported to be random in any of the studies. In two of the studies 

in the sensitivity analyses the selection of subjects was consecutive (Rozen et al 1997; 

Rozen et al 2000). In all of the studies in the main analyses, external validity was good; 

however, the external validity was reduced in the sensitivity analyses where studies with a 

high proportion of patients at increased risk were included. 


Table 3 Characteristics of the head-to-head FOBT studies performed in a screening population 

Long-term followup 

Randomisation / 

multiple tests in a 

single patient 


FOBTs compared 

Population (ITS) 

Study 

QS/12 

LoE 

Yes, 2 years review 

of insurance records 

for neoplasms (96% 

of subjects) 

Multiple tests 

Positive FOBT: colonoscopy; 

Hemoccult Sensa positive: FSa Yes, 1 year review of 

hospital pathology 

records for 

neoplasms 

(Hardcastle et al 

1986) 

Yes, 2 years 

follow-up for 

colonic symptom 

presentation to GP 


• Hemoccult 

• Hemoccult Sensa 

• HemeSelect 

• Hemoccult Sensa + 

Hemeselect 

• Hemoccult (no dietary 

restriction) 

• Fecatwin Sensitive/ 

Feca EIAb Members of non-profit US health 

insurer electing health appraisal, > 

50 years; N = 10,702 

Allison et al 

1996 

7 

1 


Positive: history, exam, RS and 60 cm 

fibreoptic sigmoidoscopy, then if 

carcinoma: DCBE; adenoma: 

colonoscopy; no neoplasms: DCBE 

If negative follow-up: repeat FOBT 

If positive, gastroscopy 

Positive: history, exam, RS, sample 

obtained on exam tested with Haemostix 

If positive or pathology suspected: full 

investigation 

If negative: repeat FOBT after 3 months 

Individuals from GP registers (UK), 

45–75 years; N = 3225; excluded 

known large bowel disease patients 

Armitage et al 

1985 

6 

• Hemoccult (no dietary 

restriction) 

• Fecatwin (guaiac) 

GP patient attendees (UK), 

> 40 years; N = 640 (group 1) 

Barrison and 

Parkins 1985 

Excl 

Yes, 2 year repeat 

FOBT screening in 

25% of subjects 

20 Faecal occult blood testing 


No 


Positive HO and/or positive/borderline 

HemeSelect: pancolonoscopy or left 

Colonoscopy plus DCBE when 

pancolonoscopy not possible 

All: FS 

Positive: DCBE or colonoscopy 


(rehydrated) 


General population (Italy), 

40–70 years; N = 24,282 

Castiglione 

et al 1997 

Excl 


• Immudia–HemSp 

Individuals presenting for health 

care examination (Japan), most 50– 

59 years (mean 52 years); N = 6437 

Iwase 1992 

5 

No 


Positive: full colonoscopy or FS + DCBE 

No 


Positive: mixed, including exam, repeat 

FOBT, DCBE, sigmoidoscopy, 

colonoscopy or an upper gastrointestinal 

barium series. 70% had DCBE or 

colonoscopy 


(unhydrated) 


(rehydrated) 





General population (US, distribution 

through pharmacies and community 

groups following media campaign), 

≥ 50 years; N = 85,931 

Levin et al 1997 

Excl 

General population (US, distribution 

through selected pharmacies 

following media campaign), > 30 

years; N = 39,000 

Petrelli et al 

1994 

5

Long-term follow-up 

Randomisation/ 

multiple tests in 

a single patient 


FOBTs 

compared 


Study 

QS/ 

12 

LoE 

Yes, median 35 months by GP 

information and review of hospital 

pathology records for neoplasms 


Positive: exam, 

sigmoidoscopy and 

colonoscopy/FS & DCBE 



No 


No 


All had endoscopy, FS 

(41%) or total colonoscopy 

(59%, including FOBT 

positive) 

All had endoscopy, 59% at 

time of study 


• BM-Test Colon 

Albumin 

Individuals from GP registers (UK), 

50–75 years; N = 4018. Known colorectal 

neoplasia, advanced visceral malignancy or 

unfit for further investigation excluded 

Consecutive attendees at CRC screening 

service (95% asymptomatic) (Israel); N = nr 

(527 screened) 

Robinson et 

al 1996 

6 

1 

Rozen et al 

1995 

4 

Yes, > 2 years clinical follow-up in 

4 subjects with positive FOBT who 

refused colonoscopy 


All had full colonoscopy or 

FS, 48% at time of study 



• FlexSure OBT 



• FlexSure OBT 




Rozen et al 

1997 

5 

Faecal occult blood testing 21 

No 


Positive: colonoscopy 






Participants in screening program (individuals 

with FH CRC (80%) and community 

volunteers) (Australia), 45–79 years; N = nr 


Rozen et al 

2000 

5 

St John et al 

1993 

5 

None available 


No 


Excl 

2a 

2b 

3a 

3b 

Parallel arms with 

historical cohort 

Positive, symptomatic or 

FH CRC: exam, FS and 

DCBE 

• Shionogi B 

• Immudia-HemSp 

Mass screening (Japan), > 40 years; 

N = 18,497 

Fujita et al 

1992 

Yes, cancer registry data over 

5 years and negative FOBTs 

rescreened in 2.5 years 

Parallel arms, nonrandomised 

Total colonoscopy or 

colonoscopy & DCBE 


• RPHA 

(HemeSelect; 

Immudia–HemSp 

General population (Italy), 50–70 years; 

N = nr (41,744 screened) 

Zappa et al 

2001 

Excl 

Abbreviations: CRC, colorectal cancer; DCBE, double contrast barium enema; Excl, excluded from further review; FH, family history; FOBT, faecal occult blood test; FS, flexible sigmoidoscopy; GP, general practice; HO, Hemoccult; 

LoE, level of evidence; nr, not reported; QS, quality score ; RPHA, reverse-passive haemagglutination; RS, rigid sigmoidoscopy. 

aDue to the unacceptably high number of patients whose only positive test was Hemoccult Sensa and whose colonoscopic examinations revealed no colorectal carcinoma, patients were advised to first undergo flexible sigmoidoscopy 

and repeated Hemoccult testing at 6 and 12 months. Colonoscopy was offered to anyone who was found to have a colorectal neoplasm on sigmoidoscopy; bFecatwin Sensitive = Fecatwin/Feca EIA.

Participation 

An important component of any population based screening program is the participation 

rate of those targeted for screening. There are many reasons for non-participation in 

FOBT screening programs including: intercurrent illness; the lack of appreciation of the 

concept of asymptomatic illness; the fear of further tests and surgery; the unpleasantness 

of the stool collection procedure and the fear of cancer itself (Hynam et al 1995). 

Non-participation in the targeted population negatively impacts on the cost and 

effectiveness of the screening program. Since participation may vary between FOBTs 

(eg, due to the need to adhere to dietary restrictions), it is important that estimates of the 

relative participation rates associated with each FOBT are incorporated into any 

assessment of cost-effectiveness. Estimates of the likely participation rates of guaiac 

versus immunochemical FOBTs in an Australian population health screening program 

were obtained from a study conducted in an Australian average risk population (Cole et 

al 2003) and data from the Australian Government Bowel Cancer Screening Pilot 

Program (the pilot). The effects of participation rates on the relative cost-effectiveness of 

different FOBTs are discussed in the economic section of this report. 

Change in clinical management and clinical outcomes 

Results 

The identification of early stage disease or potential precursors of disease by FOBTs and 

subsequent curative procedures such as preventative polypectomy and surgery can 

significantly reduce CRC morbidity and mortality. FOBT screening for CRC in the 

general population has been shown to reduce CRC mortality in a number of large 

randomised and non-randomised controlled trials. A systematic review and meta-analysis 

of RCTs performed by the Cochrane Collaboration has shown that screening for CRC in 

asymptomatic patients using a FOBT (Hemoccult) can reduce the relative risk of CRC 

mortality by around 16 per cent (relative risk 0.84; 95% CI: 0.77, 0.89) (Towler et al 

1998). 

Diagnostic performance 

The accepted methodology for investigating the accuracy of new diagnostic tests is to 

compare the diagnosis made with the new test with the true disease status. However, it is 

often not feasible to determine the disease status of a patient unequivocally. Therefore, in 

many disease states a proxy measure, such as another diagnostic test or clinical 

judgement, must be used. The best available measure of disease is called the reference 

standard. Both the test result and the comparator result must be independently compared 

with the reference standard to assess sensitivity, specificity and accuracy. However, in 

studies of screening tests it is often unacceptable and unethical to subject asymptomatic 

people with a negative test to what may be a battery of invasive, time-consuming, and 

costly clinical investigations. 


Three different methods are used to circumvent this problem and investigate the relative 

performance of the FOBTs identified in this assessment. An explanation of these 

methods and their limitations are listed below. 

1. The relative sensitivity and specificity of each of the FOBTs were estimated using the 

interval cancer rate (ie, the number of cancers that are detected during intervals 

between screening) as a proxy for the false negative rate (FNR). 

The sensitivity of a test is a measure of how good the test is at picking up people 

who have the condition: 

True positive/(True positive + False negative). 

The specificity of a test is a measure of how good the test is at correctly excluding 

people without the condition: 

True negative/(True negative + False positive). 

The diagnostic odds ratio is a measure of test accuracy combining sensitivity and 

specificity measures: 

(True positive × True negative)/(False negative × False positive)]. 

These data are reported in Appendix G. 

2. A useful measure of the relative performance of screening tests, where sensitivity and 

specificity data are not available, is the relative true positive rate (TPR) and the 

relative false positive rate (FPR). These values provide a measure of the relative 

performance of the tests, when both tests are conducted in each person and negative 

screening test results are not followed-up with an appropriate reference standard 

(Chock et al 1997). 

The actual measure of TPR and FPR will depend on the disease prevalence within 

the study population. However, the relative TPR and the relative FPR provide a 

useful and unbiased measure of comparative FOBT performance. 

The TPR of a test is: 

The number of true positive results (confirmed by the reference 

standard)/the number of participants with disease confirmed by the 

reference standard. 

The FPR of a test is: 

The number of false positive results (excluded by the reference standard)/the 

number of participants without disease, confirmed by the reference standard. 

These values are unknown in screening studies where negative test results are not 

followed up with the reference standard. 

The relative TPR is the ratio of the TPR of one test to the TPR of the other. The 

relative FPR is the ratio of the FPR of one test to the FPR of the other. These ratios 

can be determined without knowing the total number of patients with the disease. 


3. The positive predictive value (PPV) for each FOBT was also determined; these data 

are reported in Appendix F, for completeness. 

The PPV is the probability that if a person tests positive that they actually have the 

condition: 

True positive/(True positive + False positive). 

Meta-analyses 

This project required separate meta-analyses of various outcomes measuring the 

efficacy of the test being examined. The analyses were also carried out for various 

populations. 

Typically, each set of trial results consisted of two or more observed proportions, one for 

each test used. For each trial, the tests were usually repeated on the same set of patients. 

These circumstances, in general, preclude the use of classical meta-analyses methods for 

summary data, as these methods were developed for two-arm trials with independent sets 

of subjects in each arm. 

In addition, there was usually a small number of trials involved in each meta-analysis. 

Classical random-effects meta-analysis (Der Simonian and Laird 1986) implicitly assumes 

that a between-studies variance estimate used in the calculation of the weights for the 

method is known with precision, and this is not likely to be true for a small number of 

trials. 

A further source of variability may be that diagnostic test results are sensitive to the 

threshold set for the test, which may vary between studies (see Lijmer et al 2002 for 

details). 

The circumstances outlined above suggest that a more sophisticated random-effects 

analysis is required, and a Bayesian approach was deemed to provide a more appropriate, 

conservative approach (Higgins and Whitehead 1996; Smith et al 1995). The analyses 

were carried out using Markov Chain Monte Carlo (MCMC) simulation as implemented 

in the statistical package WinBUGS (version 1.3, Spiegelhalter et al 2000). 

The method is based on fitting logistic regression models incorporating random effects. 

A random intercept model of the form was adopted: 

logit(p ij) = α + b i + β j × x ij, 

where, 

• p ij = prob(Y ij = 1) is the probability that the event occurs 

• α is an intercept, interpreted as the log-odds for the event occurring in a 

reference category, in this case the guaiac test group 

• b i is a random effect for the i th study, which is common across all categories of 

interest 


• β j is a fixed effect which is the deviation, on the log-odds scale, of the event rate 

in the j th category from that of the reference category, and 

• x ij is an indicator for the j th category in study i. 

The random study effects were assumed to be normally distributed with 0 mean and 

2 2 

variance σb , and it was also assumed that 1/σb , also known as the (between-studies) 

“precision” parameter, has a gamma distribution (Smith et al 1995). The parameters were 

chosen so that the prior distribution (gamma(0.001,0.001)) was “uninformative”, which 

2 

leads to a conservative posterior distribution for 1/σb . 

Uninformative normal prior distributions (N(0,10 6 )) were set for the fixed parameters (α 

and β). 

The results given below include the median estimate of the fixed effects, together with 

95% credibility intervals, which are the range of estimated values that lie between 2.5% 

and 97.5% percentiles of the values which make up the posterior distribution for each 

parameter of interest. 

The difference between effects of any pair of diagnostic measures for different tests can 

be obtained by taking the difference between the estimated β’s corresponding to the 

various diagnostic test groups. 

For the relative true positive and false positive rates, frequentist meta-analysis methods 

were used, with inverse-variance weighting (Whitehead and Whitehead 1991). The 

standard heterogeneity test based on the (Cochran’s)“Q” statistic was used to choose 

between results from fixed- and random-effects variants. 

Sensitivity and specificity 

Three studies estimated the sensitivity, specificity and accuracy of various FOBTs using 

the interval cancer rate as a proxy for the FNR (Allison et al 1996; Armitage et al 1985; 

Robinson et al 1996). The analyses of the sensitivity and specificity data from these 

studies constitute the main analyses reported in Table 4 and Table 5, respectively. The 

sensitivity is the proportion of all patients with CRC who test positive. That is, how good 

the test is at picking up participants who have the condition. The specificity is the 

proportion of all patients without CRC who test negative. That is, how good the test is at 

correctly excluding people without the condition. 

Another three studies estimated the sensitivity and specificity of various FOBTs in 

screening populations with a high proportion of participants who were at higher risk of 

disease, by subjecting all participants to the endoscopic examination (Rozen et al 1995; 

Rozen et al 1997; Rozen et al 2000). However, in these studies the endoscopic 

examination had been performed up to several years previously in a proportion of the 

patients testing negative with FOBT. In addition, some of the subjects with a negative 

FOBT had received flexible sigmoidoscopy rather than colonoscopy. Therefore, these 

studies were still subject to verification bias. These studies have been included only in a 

sensitivity analyses. These studies also provided the only estimates of sensitivity and 

specificity of various FOBTs for adenoma detection. Therefore, there were no data of a 

suitable quality available to assess relative accuracy of the tests for the detection of 

adenomas. 


HemeSelect was found to be significantly more sensitive than Hemoccult (77.1% vs 

30.0%, respectively). The odds ratio (OR) and risk difference (RD) for this comparison 

was 7.88 (95% confidence interval (CI): 3.09, 21.47) and 0.46 (95% CI: 0.231, 0.631), 

respectively. These differences were maintained in the sensitivity analysis. No statistically 

significant difference was identified in any of the other comparisons performed. The 

level of heterogeneity was relatively low in all of the analyses performed. 

The Hemoccult test was significantly more specific than HemeSelect (97.8% vs 93.5%, 

respectively). The OR and RD for this comparison was 0.33 (95% CI: 0.28, 0.39) and 

–0.043 (95% CI: –0.070, –0.026), respectively. This difference was maintained in the 

sensitivity analysis. 

The specificity of Hemoccult was significantly greater than that for Fecatwin 

Sensitive/Feca EIA (97.1% vs 92.2%, respectively). The OR and RD for this comparison 

was 0.35 (95% CI: 0.24, 0.51) and –0.049 (95% CI: –0.066, –0.032), respectively. 

The HemeSelect test proved to be significantly more specific than Hemoccult Sensa 

(94.4% vs 86.7%, respectively). The OR and RD for this comparison was 2.58 (95% CI: 

2.29, 2.91) and 0.077 (95% CI: 0.068, 0.086), respectively. Again, this difference was 

maintained in the sensitivity analysis. 

In a study with a large portion of high-risk patients, the immunochemical test Flexsure 

OBT did not have a significantly different specificity to that of Hemoccult (96.7% vs 

94.7%, respectively). In another study in a similar patient population, the specificity of 

Flexsure OBT was significantly greater than that of Hemoccult Sensa (98.5% vs 94.9%, 

respectively). The OR and RD for this comparison was 3.51 (95% CI: 2.14, 5.74) and 

0.036 (95% CI: 0.023, 0.040), respectively. 

Similarly, in a study with a large portion of high-risk patients, the immunochemical test 

BM-Test Colon Albumin also had a significantly greater specificity than Hemoccult 

Sensa (89.5% vs 83.7%, respectively). The OR and RD for this comparison was 1.65 

(95% CI: 1.15, 2.38) and 0.057 (95% CI: 0.016, 0.099), respectively. 


Table 4 Meta-analyses of sensitivity for carcinoma from FOBT head-to-head studies 

Heterogeneity 

(p) 

RD 

pooled results 

(95% CI) 

OR 


(95% CI) 

Immunochemical 

pooled 

sensitivity (%) 

Guaiac pooled 

sensitivity (%) 

Sensitivity n/N 

(true +ve/total 

carcinoma) 

(%) 

FOBT 

Studies 

FOBT comparison 

Main guaiac to immunochemical comparisons 

13/35 (37.1) 

22/32 (68.8) 

0.011 

(0.0001–5.98) 

0.46 

(0.231 – 0.631) 

7.88 

(3.09 – 21.47) 

HemeSelect 

77.1 

HO 

30.0 

– 

0.33 

(–0.166 – 0.832) 

5.0 

(0.344 – 72.78) 

Fecatwin 

83.3 

– 

–0.107 

(–0.317 – 0.103) 

0.57 

(0.186 – 1.745) 

HemeSelect 

68.8 

HO 

50.0 

HO Sensa 

79.4 

1/11 (9.1) a 

11/11 (100) 

3/6 (50.0) 

5/6 (83.3) 

27/34 (79.4) 

22/32 (68.8) 

HO 

HemeSelect 

HO 

HemeSelect 

HO 

FecaTwin 

HO Sensa 

HemeSelect 

HO vs HemeSelect 

Allison 1996 

Robinson 1996 

HO vs Fecatwin 

Armitage 1985 b 

HO Sensa vs HemeSelect 

Allison 1996 

0.009 

(0.00009–2.00) 

0.44 

(0.255 – 0.580) 


0.012 

(0.00009–5.99) 

–0.355 

(–1.428 – 0.701) 

– 

0.20 

(–0.354 – 0.754) 

– 

0.0 

(–0.518 – 0.518) 

– 

0.20 

(–0.354 – 0.754) 

13/35 (37.1) 

22/32 (68.8) 

1/11 (9.1) HO 

HemeSelect 

7.07 

33.6 

78.1 

(3.00 – 17.67) 

HO Sensa 

HemeSelect 

1.23 

77.5 

70.7 

(0.110 – 2.408) 

HO 

Flexsure 

2.67 

60.0 

80.0 

(0.158 – 45.143) 

HO Sensa 

Flexsure 

1.0 

42.9 

42.9 

(0.120 – 8.307) 

HO Sensa 

Colon Albumin 

2.67 

60.0 

80.0 

(0.158 – 45.143) 

a 

Sensitivity analyses 


HO 

Allison 1996 

HemeSelect 

HO 

Robinson 1996 

HemeSelect 

11/11 (100) 

HO 

3/5 (60.0) 

Rozen 1997 

HemeSelect 

4/5 (80.0) 


HO Sensa 

27/34 (79.4) 

Allison 1996 

HemeSelect 

22/32 (68.8) 

HO Sensa 

3/5 (60.0) 

Rozen 1997 

HemeSelect 

4/5 (80.0) 

HO vs Flexsure OBT 

HO 

3/5 (60.0) 

Rozen 1997 

Flexure 

4/5 (80.0) 

HO Sensa vs Flexsure OBT 

HO Sensa 

3/7 (42.9) 

Rozen 2000 

Flexsure 

3/7 (42.9) 

HO Sensa vs BM-Test Colon 

HO Sensa 

3/5 (60.0) 

Albumin 

Rozen 1995 

BM-Test Colon Albumin 4/5 (80.0) 

Abbreviations: CI, confidence interval; HO, Hemoccult; HO Sensa, Hemoccult Sensa; Fecatwin, Fecatwin Sensitive/Feca EIA; FOBT, faecal occult blood test; OR, odds ratio; RD, risk difference. 

aAssumes that the patient developing cancer during follow-up for adenoma initially tested negative with Hemoccult; bData from Hardcastle et al 1986.

Table 5 Meta-analyses of specificity for carcinoma from FOBT head-to-head studies 

Heterogeneity 

(p) 

RD 


(95% CI) 

OR 


(95% CI) 


pooled 

specificity (%) 

Guaiac pooled 

specificity (%) 

Specificity n/N 

(True –ve/Total 

no Carcinoma) 

(%) 

FOBT 

Studies 



0.033 

(0.0004–2.517) 

–0.043 

(–0.070 – –0.026) 

0.33 

(0.28 – 0.39) 

HemeSelect 

93.5 

HO 

97.8 

– 

–0.049 

(–0.066 – –0.032) 

0.35 

(0.24 – 0.51) 

Fecatwin 

92.2 

– 

0.077 

(0.068 – 0.086) 

2.58 

(2.29 – 2.91) 

HemeSelect 

94.4 

HO 

97.1 

HO Sensa 

86.7 

7845/8030 (97.7) 

7043/7461 (94.4) 

1462/1478 (98.9) 

1344/1478 (90.9) 

1261/1298 (97.2) 

1197/1298 (92.2) 

6824/7870 (86.7) 

7043/7461 (94.4) 

HO 

HemeSelect 

HO 

HemeSelect 

HO 

FecaTwin 

HO Sensa 

HemeSelect 


Allison 1996 

Robinson 1996 


Armitage 1985 a 


Allison 1996 

0.033 

(0.0004–2.517) 

–0.038 

(–0.045 – –0.031) 


0.342 

(0.029–12.48) 

0.054 

(0.024 – 0.121) 

– 

0.020 

(–0.008 – 0.048) 

– 

0.036 

(0.023 – 0.049) 

– 

0.057 

(0.016 – 0.099) 



HO 

7845/8030 (97.7) 

Allison 1996 

HemeSelect 

7043/7461 (94.4) 

HO 

1462/1478 (98.9) 

HO 

HemeSelect 

0.36 

Robinson 1996 

HemeSelect 

1344/1478 (90.9) 

97.8 

94.0 

(0.31 – 0.42) 

HO 

377/398 (94.7) 

Rozen 1997 

HemeSelect 

390/398 (98.0) 


HO Sensa 

6824/7870 (86.7) 

Allison 1996 

HemeSelect 

7043/7461 (94.4) HO Sensa 

HemeSelect 

2.62 

HO Sensa 

366/398 (92.0) 

90.8 

96.3 

(2.33 – 2.95) 

Rozen 1997 

HemeSelect 

390/398 (98.0) 


HO 

377/398 (94.7) 

HO 

Flexsure 

1.64 

Rozen 1997 

Flexure 

385/398 (96.7) 

94.7 

96.7 

(0.81 – 3.34) 

HO Sensa vs Flexsure OBT 

HO Sensa 

1332/1403 (94.9) HO Sensa 

Flexsure 

3.51 

Rozen 2000 

Flexsure 

1382/1403 (98.5 

94.9 

98.5 

(2.14 – 5.74) 

HO Sensa vs BM-Test Colon 

HO Sensa 

437/522 (83.7) 

HO Sensa 

Colon Albumin 

1.65 

Albumin 

Rozen 1995 

BM-Test Colon Albumin 467/522 (89.5) 

83.7 

89.5 

(1.15 – 2.38) 

Abbreviations: CI, confidence interval; HO, Hemoccult; HO Sensa, Hemoccult Sensa; Fecatwin, Fecatwin Sensitive/Feca EIA; FOBT, faecal occult blood test; OR, odds ratio; RD, risk difference. 

aData from Hardcastle et al 1986.

Relative true positive rate and relative false positive rate 

Screening tests are usually compared in a sequential “within-subject” design, with only 

positive test results being verified with the reference standard. The actual measure of 

TPR and FPR will depend on the disease prevalence within the study population. 

However, the relative TPR and the FPR (ie, the ratio of one test’s TPR or FPR to the 

other) provide a useful and unbiased measure of comparative FOBT performance. 

Table 6 and Table 7 present meta-analyses of relative TPR and relative FPR data from 

the head-to-head studies of FOBTs. 

Table 6 shows that the TPR of Hemoccult to reverse-passive haemagglutination 

(RPHA) tests (HemeSelect and Immudia-HemSp pooled) for detecting carcinoma was 

significantly higher for HemeSelect (relative TPR 0.59; 95% CI: 0.39, 0.88). The TPR was 

not significantly different when Hemoccult was compared to Fecatwin Sensitive/Feca 

EIA (relative TPR 0.60; 95% CI: 0.14, 2.51) or when Hemoccult Sensa was compared 

with HemeSelect (relative TPR 1.07; 95% CI: 0.70, 1.62). 

Table 7 shows that the FPR of Hemoccult was superior to RPHA (relative FPR 0.53; 

95% CI: 0.33, 0.87). Similarly, the FPR of Hemoccult was superior to Fecatwin 

Sensitive/Feca EIA (relative FPR 0.35; 95% CI: 0.24, 0.51). The FPR of HemeSelect was 

superior to Hemoccult Sensa (relative FPR 2.23; 95% CI:1.14, 4.37). There was 

significant heterogeneity in the meta-analyses for Hemoccult versus RPHA and 

Hemoccult Sensa versus HemeSelect; however, this may well be due to the small number 

of included studies. 


Table 6 Meta-analyses of relative TPR for carcinoma from main FOBT head-to-head studies 

Heterogeneity 

p 

Pooled relative TPR 

guaiac:immunochemical 

Guaiac relative TPR 

True positives 

n 

FOBT 

Studies 


p (95% CI) 

13 

HO 

Allison 1996 a 

0.59 

HO vs RPHA (pooled 

HemeSelect and Immudia) 

22 

HemeSelect 

8 

HO 

Iwase 1992 

0.50 

0.35 

0.59 (0.39–0.88) 

FEM 

16 

Immudia d 

16 

HO 

Petrelli 1994 b 

0.76 

21 

HemeSelect 

1 

HO 

Robinson 1995 c 

0.11 

9 

HemeSelect 

3 

HO 

Armitage 1985 



- 

0.60 (0.14–2.51) 

0.60 

5 

Fecatwin 

27 

HO Sensa 



1.23 

0.48 

1.07 (0.70–1.62) 

FEM 

22 

HemeSelect 

19 

HO Sensa 


0.90 

21 

HemeSelect 

Abbreviations: CI, confidence interval; HO, Hemoccult; HO Sensa, Hemoccult Sensa; Fecatwin, Fecatwin Sensitive/Feca EIA; FEM, fixed effects method; FOBT, faecal occult blood test; RPHA, reverse-passive 

haemagglutination; TPR, true positive rate. 

aThe total number of tests performed differs slightly between test type, as both test were not performed in 100% of patients. To simplify the analyses, it was assumed that the reason for any test not being done was independent 

of test type and outcome, so that the missing data could be treated as ignorable. bTotal positives calculated from number of patients screened and percentage positivity rate as reported; c Data from Robinson et al (1996) are not 

used due to slight discrepancies between the publications and a degree of uncertainty surrounding the data. dOver 3 days.

Table 7 Meta-analyses of relative FPR for carcinoma from main FOBT head-to-head studies 

Heterogeneity 

p 

Pooled relative FPR 

guaiac:immunochemical 

Guaiac relative FPR 

False positives 

n 

FOBT 

Studies 


p (95% CI) 

185 

HO 


0.44 

HO vs RPHA (pooled 

HemeSelect and Immudia) 

418 

HemeSelect 

402 

HO 

Iwase 1992 

1.07 

< 0.0001 

0.53 (0.33–0.87) 

REM 

375 

Immudia d 

440 

HO 


1.06 

417 

HemeSelect 

16 

HO 

Robinson 1995 c 

0.12 

136 

HemeSelect 

37 

HO 

Armitage 1985 



- 

0.35 (0.24–0.51) 

0.35 

106 

Fecatwin 

1046 

HO Sensa 



2.50 

0.006 

2.23 (1.14–4.37) 

REM 

418 

HemeSelect 

830 

HO Sensa 


1.99 

417 

HemeSelect 

Abbreviations: CI, confidence interval; HO, Hemoccult; HO Sensa, Hemoccult Sensa; Fecatwin, Fecatwin Sensitive/Feca EIA; FOBT, faecal occult blood test; FPR, false positive rate; REM, random effects method; RPHA, 

reverse-passive haemagglutination. 

aThe total number of tests performed differs slightly between test type, as both test were not performed in 100% of patients. To simplify the analyses, it was assumed that the reason for any test not being done was independent 

of test type and outcome, so that the missing data could be treated as ignorable. bTotal positives calculated from number of patients screened and percentage positivity rate as reported; c Data from Robinson 96 is not used due to 

slight discrepancies between the publications and a degree of uncertainty surrounding the data. dOver 3 days.

Summary of diagnostic performance of FOBTs 

Three head-to-head studies estimated the sensitivity and specificity of various FOBTs for 

CRC detection using the interval cancer rate as a proxy for the FNR. This allowed the 

calculation of the relative sensitivities and specificities for each of the FOBTs included in 

these studies. The relative TPR and the relative FPR (ie, the ratio of one test’s TPR or 

FPR to the other) provide a useful and unbiased measure of comparative FOBT 

performance (Chock et al 1997). 

On the basis of two of these studies, HemeSelect was found to be significantly more 

sensitive than Hemoccult (77.1% vs 30.0%, respectively; RD 0.46; 95% CI: 0.231, 0.631). 

In contrast, the Hemoccult test was significantly more specific than HemeSelect (97.8% 

vs 93.5%, respectively; RD –0.043; 95% CI: –0.070, –0.026). Therefore, HemeSelect is 

more effective at detecting patients with CRC but is not as effective at excluding 

participants without the disease. The relative TPR for detecting carcinoma was 

significantly in favour of RPHA rather than Hemoccult (relative TPR 0.59; 95% CI: 0.39, 

0.88), whereas the FPR of Hemoccult was lower than for RPHA (relative FPR 0.53; 95% 

CI: 0.33, 0.87). Therefore, these measures are not adequate to determine which of these 

tests is more accurate. The practical impact of this trade-off has been investigated via the 

use of an economic model in the cost-effectiveness section of this assessment report. 

The sensitivities of Hemoccult and Fecatwin Sensitive/Feca EIA were not significantly 

different (50% vs 83.3%, respectively; RD 0.33; 95% CI: –0.166, 0.832). However, 

Hemoccult was significantly more specific than Fecatwin Sensitive/Feca EIA (97.1% vs 

92.2%, respectively; RD –0.049; 95% CI: –0.066, –0.032). This means that at this time 

there is no statistically significant evidence to suggest that Hemoccult or Fecatwin 

Sensitive/Feca EIA are better at identifying patients with CRC. However, there is 

statistically significant evidence to suggest that Hemoccult is superior at excluding 

participants without the disease. The TPR for detecting carcinoma was not significantly 

different when Hemoccult was compared to Fecatwin Sensitive/Feca EIA (relative TPR 

0.60; 95% CI: 0.14, 2.51). However, the FPR of Hemoccult was lower than Fecatwin 

Sensitive/Feca EIA (relative FPR 0.35; 95% CI: 0.24, 0.51). This would imply that, based 

on the available data, Hemoccult is statistically the more accurate test. It should be noted 

that the subjects in this study were not required to adhere to the dietary restrictions 

generally recommended with the use of a guaiac FOBT. 

The sensitivity of Hemoccult Sensa and HemeSelect were not significantly different 

(79.4% vs 68.8%, respectively; RD –0.107; 95% CI: –0.317, 0.103). In contrast, 

HemeSelect proved to be significantly more specific than Hemoccult Sensa (94.4% vs 

86.7%, respectively; RD 0.077; 95% CI: 0.068, 0.086). This means that at this time there 

is no statistically significant evidence to suggest that Hemoccult Sensa or HemeSelect are 

better at identifying patients with CRC. However, there is statistically significant evidence 

to suggest that HemeSelect is superior at excluding participants without the disease. The 

TPR was not significantly different when Hemoccult Sensa was compared with 

HemeSelect (relative TPR 1.07; 95% CI: 0.70, 1.62). However, the FPR of HemeSelect 

was lower than that of Hemoccult Sensa (relative FPR 2.23; 95% CI: 1.14, 4.37). This 

would imply that, based on these data, HemeSelect is statistically the more accurate test. 

Only three head-to-head studies estimated the sensitivity and specificity of various 

FOBTs for adenoma detection. These studies were all conducted in screening 

populations with a high proportion of participants who were at higher risk of disease, by 

subjecting all participants to endoscopic examination. In addition, these studies were 

32

subject to verification bias due to the large time lapse between performing the 

endoscopic examination and the FOBT in many patients with a negative FOBT result. 

Therefore, there were no data of a suitable quality to assess relative accuracy of the tests 

for the detection of adenomas. 

The relative cost-effectiveness of pairs of FOBTs based on the sensitivity and specificity 

data as derived from these head-to-head studies of FOBTs is explored below. Therefore, 

the available data have determined the economic comparisons which can be performed. 

The relative cost-effectiveness of Hemoccult versus HemeSelect; Hemoccult Sensa 

versus HemeSelect; and Hemoccult versus Fecatwin Sensitive/Feca EIA are examined 

utilising data from the main analyses of sensitivity and specificity. Due to concerns of 

external validity, where the only data available for a head-to-head comparison are from a 

population at increased risk (Hemoccult versus FlexSure OBT, Hemoccult Sensa versus 

FlexSure OBT, and Hemoccult Sensa versus BM-Test Colon Albumin comparisons), this 

is not extended to an economic analysis. 

What are the economic considerations? 

The cost-effectiveness of population-based FOBT screening for CRC has been 

established repeatedly in the health economics literature (Wagner et al 1996; Khandker et 

al 2000; Salkeld et al 1996; Bolin et al 1999; O’Leary et al 2004). Given this, the economic 

model developed for this assessment seeks to determine the most promising FOBT 

within a screening setting. To this end, the relative performance and cost-effectiveness of 

a variety of FOBTs in a number of settings is determined. In particular, key 

characteristics of the screening program – such as the age of the screening population 

and the interval between screening rounds – are altered to determine which option yields 

the best value for money for the Australian healthcare system. 

Assessment of value for money of population health screening for 

colorectal cancer 

Why an economic model is required 

Economic models of health care interventions have a range of advantages and limitations 

compared with observational studies and other prospectively designed data collection 

experiments. The costs of an FOBT screening program for the detection of CRC are 

expected to be partially offset by longer-term benefits in terms of both costs and health 

outcomes. Consequently, an economic model is required to quantify these offsets 

accurately. In addition, in order to compare alternative FOBTs, an economic model is 

required to measure the cost-effectiveness of various screening options under different 

conditions. 

A decision-analytic model with Markov processes was developed to estimate the 

downstream costs associated with an FOBT screening program. A Monte Carlo 

simulation is used as it allows individuals to be tracked through time. Consequently, the 

Markov model allows individuals to cycle through the screening program until the 

detection of colorectal cancer, ineligibility for screening or death from any cause. It 

should be noted, however, that the reliability of any model is dependent upon the 

uncertainty surrounding the clinical data and the key model assumptions. 


Key assumptions used in the economic model 

• The economic model is designed to assess the relative cost-effectiveness of various 

FOBTs used to detect CRC in a screening population. Consequently, head-to-head 

comparisons between FOBTs are made. It is not intended that decision-makers 

compare tests not appearing directly alongside one another. 

• The natural progression of CRC is defined such that patients with undiagnosed 

cancer pass sequentially through each clinical stage after an appropriate time interval. 

Patients do not ‘skip’ stages in the sequential sequence. 

• Individuals with diagnosed CRC are at greatest risk of mortality for the first 5 years 

following diagnosis. These individuals are assumed to revert to a ‘normal’ lifeexpectancy 

if they survive their first 5 years with diagnosed cancer. 

• The likelihood of CRC detection with FOBT, or procedures used later in the 

diagnostic work-up, is assumed to be independent of the stage of cancer. 

• It is assumed that the presence or absence of dietary restrictions is the key 

determinant of differences in participation rates for the two classes of FOBTs 

(guaiac and immunochemical). 

• Participation in a screening program is assumed to remain constant despite 

arguments that the increased community awareness associated with a general 

population health screening program may lead to improved participation. 

• Participation in a screening program is assumed to be dependent on past behaviour. 

That is, future patterns of participation are affected by behaviour in previous rounds. 

• Individuals with increased risk of CRC, through family history for example, are not 

treated as part of the screening population. Similarly, symptomatic patients are 

treated as external to the general screening population. These individuals are treated 

as external due to the different diagnostic pathway they are subject to. 

• All individuals in the economic model are treated as having a maximum lifeexpectancy 

of 100 years. 

• For simplicity, indirect/societal costs are not included in the economic model, as 

they are likely to be negligible in the context of the total cost of the screening 

program. This assumption is consistent with other models in the literature. 

• The results of the economic model are presented in terms of the incremental cost 

per life-year gained with one screening program over another. 

• A discount rate of 5% per annum was applied to all costs and health outcomes. 

34

The literature on FOBT screening for colorectal cancer 

FOBT has been repeatedly shown to be a cost-effective screening option for CRC in the 

general population (Wagner et al 1996; Khandker et al 2000; Salkeld et al 1996; Bolin et 

al 1999; O’Leary et al 2004). Although studies in the literature utilise a wide range of 

assumptions and screening populations, the majority of studies favour FOBT screening 

over no screening. 

There are a limited number of studies that have been conducted within the Australian 

setting. Again, these tend to show FOBT to be a cost-effective method in screening for 

CRC. In these Australian studies, Salkeld et al (1996) estimate the cost-effectiveness of 

annual FOBT screening as $24,660 per life-year gained, Bolin et al (1999) estimate the 

cost-effectiveness of annual FOBT screening as $36,132 per life-year gained and O’Leary 

et al (2004) give an estimate of $46,900. Note that while the methodologies and 

assumptions used in these studies vary greatly, the results provide good evidence of 

FOBT being a cost-effective method of CRC screening. 

Studies to date have focused on the incremental cost-effectiveness of FOBT screening 

versus no screening and a comparison between the available FOBTs has not yet been 

conducted. 

Patient population used in the economic model 

Individuals from the general population are invited to be screened for CRC under the 

proposed program. They are selected based on age alone and other risk factors do not 

play a role. Individuals identified as being at heightened risk (possibly due to a family 

history of CRC), are not included in the screening program and will instead undergo a 

separate diagnostic work-up. The age of the eligible population is treated as exogenous in 

the economic model. Annual and biennial screening intervals are tested and the most 

cost-effective alternative is recommended based on the results. 

Structure of the economic model 

A Markov model with Monte Carlo simulations is used to follow a sample of 20,000 

patients through the FOBT screening program from the first invitation for screening 

until either death or ineligibility due to age. The timing of the first invitation to screening 

is dependent on the characteristics of the screening program and is to be determined by 

the results of the economic model, as is the interval between screening rounds. 

The model consists of two modelled components: 

• the natural history of CRC (see Figure 2), which determines how patients progress 

through various health states; and 

• the screening pathway (see Figure 3), which aims to intercept the natural 

progression of CRC in such a way that treatment can be initiated and life-expectancy 

increased. 

Individuals in the model are advanced through the Markov process in 3-monthly cycles 

until death. 


Figure 2 Simplified natural history of CRC used in the economic model 

Abbreviations: CRC, colorectal cancer. 

As illustrated in Figure 2, individuals eligible for screening are classified as either ‘well’, 

having an adenoma(s), or having CRC. The model categorises cancer according to 

Dukes’ stages, defining the health state as either undiagnosed or diagnosed. Undiagnosed 

CRC progresses through the various stages according to defined distributions, whereas 

diagnosis of CRC is treated as a terminal endpoint in the model. Upon diagnosis (which 

can occur via the screening pathway or after an individual presents with symptoms 

outside of the screening program), the life-expectancy of the individual is calculated 

according to the five-year survival rate of the relevant cancer stage and, beyond that, the 

‘normal’ life-expectancy of an individual of that age. Individuals who are either ‘well’ or 

have premalignant adenoma(s) are only able to exit the model via non-CRC death. 

The screening pathway used in the economic model is illustrated in Figure 3. This is a 

simplified representation outlining the key stages of the screening process. It illustrates 

how important issues such as participation and diagnostic follow-up play a role in the 

final patient outcomes. As Figure 3 shows, the eligible population is invited to be 

screened, at which stage individuals choose either to participate or not to participate. If 

an individual chooses to participate, he/she can receive either a positive or negative 

FOBT result. This result is dependent upon the diagnostic accuracy of the particular test 

used. If an individual tests negative, he/she is invited for re-screening after an 

appropriate interval (to be determined by the economic model). If a positive result is 

given, the individual receives a diagnostic work-up and will either receive treatment if 

CRC is confirmed or be re-invited into the screening program after five years. 

36 

Well 

Adenoma 

Other death 

Undiagnosed 

Dukes’ A 

Undiagnosed 

Dukes’ B 

Undiagnosed 

Dukes’ C 

Undiagnosed 

Dukes’ D 

Diagnosed 

Dukes’ A 

Diagnosed 

Dukes’ B 

Diagnosed 

Dukes’ C 

Diagnosed 

Dukes’ D 

Other death 

CRC death

Figure 3 Screening pathway used in the economic model 



Variables used in the economic model 

Clinical variables 

As individuals from the eligible patient population enter the economic model, they are 

assigned to one of seven health states: 

• patient is free of disease (well) 

• patient has non-progressive adenoma(s) present 

• patient has progressive adenoma(s) present (though undetected) 

• patient has Dukes’ A stage CRC (which has not been diagnosed) 

• patient has Dukes’ B stage CRC (which has not been diagnosed) 

• patient has Dukes’ C stage CRC (which has not been diagnosed) 

• patient has Dukes’ D stage CRC (which has not been diagnosed). 

The likelihood of individuals entering the economic model in each of these states has 

been calculated from CRC and adenoma prevalence data reported in an Australian 

flexible sigmoidoscopy screening trial (Collett et al 2000). These data have been 

distributed by Dukes’ stage according to data from a colonoscopy screening study 

(Lieberman et al 2000). These calculations are presented in Table 8–Table 10. 

Table 8 Disease prevalence in the eligible screening population at program entry. 

Row Health state Prevalence Reference for data source 

A Adenoma(s) present 0.1351 Collett et al (2000) 

B CRC present 0.0054 Collett et al (2000) 


Table 9 Distribution of CRC by Dukes’ stage classification in the eligible screening population at 

program entry 

Row Stage of CRC Prevalence Reference for data source 

A Dukes’ stage A 0.5000 Lieberman et al (2000) 

B Dukes’ stage B 0.2330 Lieberman et al (2000) 

C Dukes’ stage C 0.2000 Lieberman et al (2000) 

D Dukes’ stage D 0.0670 Lieberman et al (2000) 



Table 10 Prevalence used for individuals entering the economic model 

Row Stage of CRC Prevalence Reference 

A Adenoma(s) present 0.1351 A = Table 8 Row A 

B Dukes’ stage A 0.0027 B = Table 8 Row B × Table 9 Row A 

C Dukes’ stage B 0.0013 C = Table 8 Row B × Table 9 Row B 

D Dukes’ stage C 0.0011 D = Table 8 Row B × Table 9 Row C 

E Dukes’ stage D 0.0004 E = Table 8 Row B × Table 9 Row D 

F Patient is ‘well’ 0.8595 F = 1 – (A + B + C + D + E) 


Following entry into the economic model, individuals are assigned a probability of 

progressing to other health states. Prior to detection of either adenomas or CRC, 

progression must occur sequentially from ‘well’ to adenoma(s) present to each of the 

cancer stages in order of severity. Patients cannot skip stages of CRC prior to diagnosis 

and treatment. 

The probability of progression is calculated on a quarterly basis. 

The probability of an individual developing an adenoma is derived by tracking the 

incidence of CRC back to the likely time of adenoma development and adjusting for the 

proportion of adenomas that undergo malignant transformation (estimated by Stryker et 

al 1987, to be 24%). A duration of 20 years between the onset of a progressive adenoma 

and clinical diagnosis was assumed (Loeve et al 2000). Age-adjusted incidence figures 

were used to trace CRC incidence back to the time of onset of the adenoma. These rates 

are presented in Table 11–Table 13. 

Table 11 Incidence of CRC 

Row Age (years) Incidence per 100,000 

individualsa Incidence 

A 50–54 56.9 0.0006 

B 55–59 107.2 0.0011 

C 60–64 166.5 0.0017 

D 65–69 239.7 0.0024 

E 70–74 316.4 0.0032 

F 75–79 378.3 0.0038 

G 80–84 410.0 0.0041 

H 85+ 454.1 0.0045 


aGender-adjusted rates. 

Source: Cancer In Australia 1999, Table 20 (AIHW). 


Table 12 Incidence of progressive adenomas, age-adjusted 

Row Age (years) Incidence Reference 

A 50–54 0.0032 A = Table 11 Row E 

B 55–59 0.0038 B = Table 11 Row F 

C 60–64 0.0041 C = Table 11 Row G 

D 65–69 0.0045 C = Table 11 Row H 

E 70–74 0.0045 D = Table 11 Row H 

F 75–79 0.0045 E = Table 11 Row H 

G 80–84 0.0045 F = Table 11 Row H 

H 85+ 0.0045 G = Table 11 Row H 


Table 13 Incidence of all adenomas, age-adjusted 

Row Age (years) Incidence Reference 

A 50–54 0.0132 A = Table 12 Row A/24% a 

B 55–59 0.0158 B = Table 12 Row B/24% a 

C 60–64 0.0171 C = Table 12 Row C/24% a 

D 65–69 0.0189 C = Table 12 Row D/24% a 

E 70–74 0.0189 D = Table 12 Row E/24% a 

F 75–79 0.0189 E = Table 12 Row F/24% a 

G 80–84 0.0189 F = Table 12 Row G/24% a 

H 85+ 0.0189 G = Table 12 Row H/24% a 


a24% assumed from Stryker et al (1987). 

Once patients have progressed from undiagnosed adenoma(s) to Dukes’ stage A CRC, 

the probability of moving through the stages of cancer is governed by an exponential 

distribution using a unique mean duration for each of the cancer stages. These 

distributions are taken from the literature whereby the estimated average duration of 

undiagnosed CRC is given. The durations used in establishing these distributions are 

presented in Table 14. 

Table 14 Mean duration of undiagnosed cancerous and precancerous health states prior to 

progression 

Health state Mean duration (years) Reference 

Adenoma 16.4a Loeve et al (1999) 

Undiagnosed Dukes’ stage A 2.0 Loeve et al (1999) 

Undiagnosed Dukes’ stage B 1.0 Loeve et al (1999) 

Undiagnosed Dukes’ stage C 1.5 Loeve et al (1999) 

Undiagnosed Dukes’ stage D 0.8 Loeve et al (1999) 

aDuration between onset of a progressive adenoma and clinical detection (20 years) minus average duration of undiagnosed CRC (assumed 

from Loeve et al (1999) to be 3.6 years. 

Alternatively, individuals may circumvent screening altogether if they present with 

symptoms. The probability of this occurring is based on current incidence data, since in 

the absence of a general screening program individuals are generally only diagnosed once 

they become symptomatic. It is assumed that individuals will not present with symptoms 

at the adenoma stage, only once they have developed CRC. 


Table 15 and Table 16 outline the calculations for the likelihood of individuals 

presenting by stage of CRC. The proportion of individuals with CRC whose cancer is 

classified as either Dukes’ stage C or D is taken from NSW stage of spread data as 

regional cancer and metastatic cancer, as reported in Bell et al (1996). The proportion of 

those whose cancer is classified as either Dukes’ A or B is calculated using the 

information in Bell et al (1996) for localised CRC and distributed into these Dukes’ 

stages according to the distribution from the no-screening arm of the Nottingham FOBT 

trial (Mapp et al 1999). 

Table 15 Distributional spread of known CRC, by stage 

Row Dukes’ stage Proportion of patients with Dukes stage 

cancer at diagnosis 

Reference 

A Dukes’ stage A 0.0910 Bell et al (1996) and Mapp et al (1999) 

B Dukes’ stage B 0.2680 Bell et al (1996) and Mapp et al (1999) 

C Dukes’ stage C 0.4880 Bell et al (1996) 

D Dukes’ stage D 0.1540 Bell et al (1996) 


Table 16 Probability of individual with CRC presenting as symptomatic, by stage 

Row Dukes’ 

stage 

Probability of 

presenting as 

symptomatic 

A Dukes’ A 0.0910 Table 15 Row A 

Reference 

B Dukes’ B 0.2948 B = Table 15 Row B/(1 – Table 15 Row A) 

C Dukes’ C 0.7613 C = Table 15 Row C/(1 – Table 15 Row A – Table 15 Row B) 

D Dukes’ D 1.0000 D = Table 15 Row D/(1 – Table 15 Row A – Table 15 Row B – Table 15 Row C) 


Note that detection of CRC with FOBT screening reduces the number of individuals 

presenting with symptoms. For example, in a population not subject to screening, the 

probabilities appearing in Table 16 apply to the entire population. Alternatively, 

detection via FOBT participation lowers the number of individuals these probabilities 

apply to. Consequently, the total number of individuals presenting with symptoms will be 

lower in the screening arms of the economic model. 

Once an individual has been diagnosed with CRC, either through FOBT screening or 

otherwise, he/she is treated as remaining in that health state until death. At this point, 

the life-expectancy of the individual is calculated and CRC treatment costs accrue. In 

calculating the life-expectancy of these individuals, five-year survival rates from a 

Victorian Cancer registry study of CRC surgical patients have been used (McLeish et al 

2002), with exponential interpolation adopted over the five-year period. Whilst survival 

rates may currently be higher than those reported in this study, different survival rates 

will not affect the outcome of the relative performance of the different FOBTs. These 

five-year survival rates are presented in Table 17, whereas the probabilities of death per 

quarter are presented in Table 18. 


Table 17 Five-year survival rates for CRC, by stage 

Row Cancer stage Five-year survival rate Reference 

A Dukes’ stage A 0.8913 McLeish et al (2002) 

B Dukes’ stage B 0.7948 McLeish et al (2002) 

C Dukes’ stage C 0.3478 McLeish et al (2002) 

D Dukes’ stage D 0.0000 McLeish et al (2002) 


Table 18 Quarterly probability of death from diagnosed CRC 

Row Cancer stage Probability of death used in the 

economic model 

A Dukes’ stage A 0.0057 Calculated a 

B Dukes’ stage B 0.0114 Calculated a 

C Dukes’ stage C 0.0514 Calculated a 

D Dukes’ stage D 0.2057 Calculated a 


aProbability = 1 – (1 – 5-year survival rate) [1/(5 years/4)] = 1 – (5-year mortality rate) [1/(5 years/4)] 

Reference 

If an individual with diagnosed CRC survives the initial five-year period, he/she is 

assumed to continue with a ‘normal’ life-expectancy. This assumption is based on expert 

opinion and supported by a cursory comparison of 5- and 10-year survival data in the 

Victorian Cancer registry study of CRC surgical patients (McLeish et al 2002). 

‘Normal’ life-expectancy takes the form of non-CRC death. The probabilities used are 

calculated by removing the mortality from CRC (Australian Institute of Health and 

Welfare (AIHW) 2002) from Australian life tables. Exponential interpolation is used to 

convert this to a quarterly probability of death. 

Diagnostic variables 

Due to the aim of the economic model – to find the most promising test and screening 

setting for a population health based screening program for CRC – the cost-effectiveness 

of a number of FOBTs is investigated using the model. The systematic review and metaanalyses 

in the effectiveness section of this report has been used as the source for the 

diagnostic accuracy of the various FOBTs. These data have been derived from head-tohead 

comparisons of guaiac versus immunochemical FOBTs. Specifically, the following 

comparisons are made: 

• Hemoccult (guaiac) versus HemeSelect (immunochemical) 

• Hemoccult Sensa (guaiac) versus HemeSelect (immunochemical) 

• Hemoccult (guaiac) versus Fecatwin sensitive/Feca EIA (two-tiered combination of 

guaiac and immunochemical). 

Due to the lack of an estimate of accuracy for the detection of adenomas, and the lack of 

dietary restrictions imposed during the study, the last comparison of Hemoccult versus 

Fecatwin sensitive/Feca EIA appears in a sensitivity analysis contained in Appendix J, 

rather than in the main body of this report. 


Relevant sensitivity and specificity rates have been determined from the effectiveness 

section of this report. Since estimates of sensitivity and specificity will be dependent 

upon the population prevalence and spectrum of disease in the population in each study, 

different values for the same FOBT appear in different head-to-head comparisons. As a 

result, it is inappropriate to draw conclusions outside of individual head-to-head 

comparisons. Conclusions can only be drawn regarding the relative cost-effectiveness of 

one test over another within the head-to-head comparisons. Sensitivity and specificity 

data for adenoma have been derived from a study conducted in a screening population 

with a high proportion of participants who were at higher risk of disease, by subjecting 

all participants to the reference standard (Rozen et al 1997). 

It is important to note that the external validity of the data available for estimating the 

sensitivity and specificity of adenoma detection is of concern. The only studies providing 

estimates of test accuracy for the detection of adenoma were those conducted in a 

population with a high proportion of subjects at increased risk. In addition, in these 

studies the endoscopic examination had been performed up to several years previously in 

a proportion of the patients testing negative with FOBT. Therefore these studies were 

subject to significant verification bias. 

The probability of a positive FOBT result in each of the comparisons is presented in 

Table 19– Table 21. Note that it is assumed that the probability of detection of CRC is 

the same regardless of the stage to which the cancer has progressed. This assumption is 

necessary due to the limitations of the available data. 

The data presented in Table 19 for Hemoccult are varied in a sensitivity analysis based 

on a summary receiver-operating characteristic curve derived from data presented in the 

efficacy section of this report (see Appendix K). 

Table 19 Probability of positive result using Hemoccult and HemeSelect 

True health state 


detection using 

Hemoccult HemeSelect 

Reference 

Well a 0.022 0.065 1 – specificity (0.978 for Hemoccult and 0.935 for HemeSelect) b 

Adenoma present 0.190 0.190 Rozen (1997) 

Dukes’ stage A CRC 0.300 0.771 Table 4 Sensitivity 

Dukes’ stage B CRC 0.300 0.771 Table 4 Sensitivity 

Dukes’ stage C CRC 0.300 0.771 Table 4 Sensitivity 

Dukes’ stage D CRC 0.300 0.771 Table 4 Sensitivity 


aFalse positive rate for CRC/adenoma. 

bSpecificity taken from systematic assessment of effectiveness in this document (Table 5). 


Table 20 Probability of positive result using Hemoccult Sensa and HemeSelect 





Sensa 

Reference 

Wella 0.133 0.056 1 – specificity (0.867 for Hemoccult Sensa and 0.944 for 

HemeSelect) b 

Adenoma present 0.238 0.190 Rozen (1997) 








Table 21 Probability of positive result using Hemoccult and Fecatwin Sensitive/Feca EIA 




Hemoccult Fecatwin 

Reference 

Well a 0.029 0.078 1 – specificity (0.971 for Hemoccult and 0.922 for Fecatwin) b 

Adenoma present 0.000 0.000 Assumption c 





Abbreviations: CRC, colorectal cancer; Fecatwin, Fecatwin Sensitive/Feca EIA. 



cAssumption necessary due to absence of data. By assuming that no adenomas are detected with either test, the relative cost-effectiveness is 

undistorted. 

Note that it has been necessary to assume a zero detection rate for adenomas in the 

Hemoccult versus Fecatwin Sensitive/Feca EIA analysis. This is due to an absence of 

data. Consequently, the results of this head-to-head analysis appear in a sensitivity 

analysis in Appendix J, as there are limitations placed on the effectiveness captured. 

Diagnostic follow-up is assumed to take the form of complete colonoscopy. Within the 

pilot, complete colonoscopy has accounted for almost 80% of all diagnostic follow-up to 

date. Consequently, the diagnostic accuracy of complete colonoscopy is used in the 

economic model as the default for diagnostic follow-up. For the purposes of the 

economic model, the differences between the accuracy of complete colonoscopy and 

other methods is unlikely to have a significant effect. 

Complete colonoscopy is assumed to have a 95% sensitivity (assumption based on 

NHMRC (1999)). The sensitivity of colonoscopy in the detection of adenomas is 85% 

(Loeve et al 1999). Complete colonoscopy is assumed to have a 100% specificity. This 

assumption eliminates the need to model outcomes resulting from false positive results. 

These probabilities are presented in Table 22. 


Table 22 Detection rates associated with colonoscopy 

Parameter Value Reference 

Sensitivity associated with detecting CRC 0.95 Assumption based on NHMRC (1999) 

Specificity associated with detecting CRC 1 Assumption 

Sensitivity associated with detecting adenoma 0.85 Loeve et al (1999) 

Specificity associated with detecting adenoma 1 Assumption 

Abbreviations: CRC, colorectal cancer; NHMRC, National Health and Medical Research Council. 

Colonoscopy is associated with a 0.0041 probability of an adverse event (Winawer et al 

1997). This rate incorporates the risk of perforation, severe haemorrhage and death. 

Cost variables 

The cost of establishing a screening program has been omitted on the basis that it is a 

negligible cost on a per invited individual basis. The cost will be distributed across all 

individuals invited to screening over the entire life of the screening program. This will 

result in a negligible individual cost which will have virtually no effect on the relative 

cost-effectiveness of the different FOBTs. 

The primary cost associated with a population based screening program is the cost of the 

FOBT itself. This cost can, however, be broken down into its components – that is the 

cost that applies to all invited members of the eligible patient population and the cost 

that applies only to those who participate in screening. This separation is necessary as the 

screening program is designed such that a FOBT kit is mailed to each individual invited 

to participate in the screening program. If an individual chooses to participate, they 

return the completed kit at the expense of the program for pathology testing. The latter 

cost, therefore, only arises in the case of participation. The relevant costs are illustrated in 

Table 23 and Table 24. 

Table 23 Cost of FOBT per invited individual 

Test Cost 

Hemoccult $2.30 

Hemoccult Sensa $3.77 

HemeSelect $6.30 a 

Fecatwin Sensitive/Feca EIA $5.35b Abbreviations: FOBT, faecal occult blood test. 

aHemeSelect is currently unavailable. This estimate is based on the cost of another immunochemical FOBT that uses a similar methodology. 

bCost calculation based on prices for other guaiac and immunochemical tests. All participants receive the guaiac component and 25% receive 

the immunochemical component and no dietary restriction. Calculation is based on the expected cost of these two tests. Transport cost was 

not included in cost provided and has been assumed to be $5.50. 


Table 24 Cost of FOBT per participant 

Test Cost 

Hemoccult $23.93 

Hemoccult Sensa $16.50 

HemeSelect $24.20 a 

Fecatwin Sensitive/Feca EIA $21.18 a 


aTransport cost was not included in cost provided and has been assumed to be $5.50. 

Further diagnostic work-up, assumed to take the form of complete colonoscopy, is 

priced depending on whether abnormalities are detected or not. In the case of 

abnormalities present at colonoscopy, participants will receive a polypectomy, thereby 

increasing the cost of colonoscopy. Cost increases are due to the polypectomy itself and 

the pathology testing associated with it. 

All colonoscopies, however, attract a cost for the service, for anaesthetic and for other 

associated costs (including day theatre charges, pharmaceuticals, etc.). The costs of 

colonoscopy with and without polyp removal are presented in Table 25 and Table 26. 

Associated costs have been sourced from Weller et al (1995) and converted to 2002 

prices using the AIHW total health price index (AIHW 2003). 

Table 25 Cost of colonoscopy without polyp removal 

Procedure Cost Reference 

Colonoscopy $277.80 MBSa Item no. 32090 

Anaesthetic $99.00 MBSa Item no 20810 and 23023 

Associated costs $606.35 Weller et al (1995) and AIHW total health price index (2003) 

Total cost $983.15 

aMedicare Benefits Schedule, November 2003. 

Table 26 Cost of colonoscopy with polyp removal 

Procedure Cost Reference 

Colonoscopy + polypectomy $389.90 MBS a Item no. 32093 

Pathology $109.30 MBS a Item no 72823 and 73903 

Anaesthetic $99.00 MBS a Item no 20810 and 23023 

Associated costs $606.35 Weller et al (1995) and AIHW total health price index (2003) 

Total cost $1204.55 

aMedicare Benefits Schedule, November 2003. 

The pathology cost quoted in Table 26 assumes that more than one polyp is found and 

removed. This assumption is biased against the screening program. 

Colonoscopy is additionally associated with a risk of an adverse event. As perforation is 

the most common of these, for costing purposes it is assumed that all adverse events 

take this form. This cost has been calculated by updating the cost found in Salkeld et al 

(1996) to 2002 prices. The 2002 cost of treating a perforation is assumed to be 

$15,010.46. 


Following diagnosis of CRC, patients accrue treatment costs. Lifetime costs have been 

used in the economic model, capturing all costs of treatment following diagnosis and 

disease progression. These costs are illustrated in Table 27. 

Table 27 Lifetime CRC treatment costs, from time of diagnosis 

Cancer stage Cost (2002 prices) Reference 

Dukes’ stage A CRC $15,808.18 O’Leary et al (2004) and AIHW total health price index (2003) 

Dukes’ stage B CRC $30,757.73 O’Leary et al (2004) and AIHW total health price index (2003) 

Dukes’ stage C CRC $23,757.67 O’Leary et al (2004) and AIHW total health price index (2003) 

Dukes’ stage D CRC $5775.07 O’Leary et al (2004) and AIHW total health price index (2003) 


Characteristics of the screening program 

Participation is an integral part of any screening program and is a driver of overall costeffectiveness 

in comparison with no screening, by affecting the way costs are distributed 

amongst those invited to be screened. In the economic model, the difference in 

participation rates between tests comes into play at the point of the initial invitation for 

screening and in later rounds when an individual’s participation is treated as a function of 

previous participation. 

Participation is assumed to vary between tests, based on the type of test being used. 

Guaiac tests, for instance, have a lower rate of participation due to the dietary restrictions 

that are imposed. Participation rates have been calculated from a number of sources, 

including preliminary estimates from the pilot. These calculations appear in detail in 

Appendix I. The participation rates used in the economic model are presented in 

Table 28. Note that there is scope for individuals who have previously not participated 

in screening to begin participating after the first round. This feature is based on expert 

advice indicating that the number of individuals picked up in later rounds is roughly 

equivalent to the number lost. 

Table 28 Compliance with FOBT screening rates used in the economic model 

Patient population Probability of 

compliance with 

guaiac FOBT 

Eligible population invited for screening 

in first round 

Those who have complied with initial 

invitation for screening (later rounds) 

Those who have not complied with 

previous invitations for screening (later 

rounds) 



compliance with 

immunochemical 

FOBT 

Reference 

0.3483 0.4540 Calculated – see Appendix I 



Additionally, compliance is an issue for individuals recommended for diagnostic followup. 

The model assumes 92.4% of individuals comply with follow-up, once 

recommended. This figure is taken from available information from the pilot. It captures 

compliance with colonoscopy (complete or incomplete but adequate) or DCBE. 


In addition to participation and compliance issues, the relative cost-effectiveness of the 

various FOBTs is likely to be linked to both the age of the population eligible for 

screening and the interval between screening rounds for individuals. 

In the base-case scenario of biennial screening, it is assumed that the eligible population 

consists of all individuals aged 55–74 years who are not considered to be at increased risk 

of CRC. Other ages considered in the sensitivity analyses include: 

• individuals aged between 50 and 74 years 

• individuals aged between 55 and 79 years. 

Although this is not an exhaustive list of options, it does give an impression of the 

sensitivity of the relative cost-effectiveness of the FOBTs investigated to variations in the 

age of eligibility for screening. 

The screening interval is assumed to be 2 years. In a sensitivity analysis, annual screening 

is also tested as an alternative. These two options are the most common in the literature. 

Results of the economic model 

The purpose of the economic model is to compare the various FOBTs within the 

context of head-to-head studies. As previously outlined, comparisons cannot be made 

outside these studies. The discussion of the results of the model will reflect this. 

The base-case scenario assumes biennial screening in individuals aged 55–74 years. The 

effect of varying these assumptions (frequency of screening and age of screening 

population), as well as other assumptions such as participation rates, is also examined and 

discussed briefly in relation to relative cost-effectiveness. 

It is worth noting that the model accurately replicates true disease incidence and 

prevalence. This is highlighted in a number of the figures below (Figure 5 on page 50 

and Figure 8 on page 53, for example), which illustrate the number of individuals in 

each stage of disease from a sampled pool of 20,000. 

In addition, it should be noted that there are substantial differences between the 

economic model analyses results and published FOBT RCT data. In particular, the 

model follows a cohort of individuals entering the model at the lowest eligibility age 

throughout the life of the program, whereas trial data will present findings for rounds of 

screening of individuals distributed across a spectrum of ages in the population entering 

a screening program. 

Hemoccult Sensa versus HemeSelect 

Costs 

The Hemoccult Sensa test is associated with higher costs overall, an average of $1532 per 

individual invited to screening versus $1428 for the HemeSelect test. This difference is 

largely driven by more frequent use of colonoscopy in the Hemoccult Sensa arm of the 

economic model, leading to a higher average cost of colonoscopy per eligible individual. 


In the case of Hemoccult Sensa, colonoscopy accounted for 22% of all costs, whereas they 

accounted for 13% of HemeSelect total costs. A graphic breakdown of costs appears below 

in Figure 4. 

Cost per individual invited to screening 

$1,600 

$1,400 

$1,200 

$1,000 

$800 

$600 

$400 

$200 

$0 

Hemoccult Sensa HemeSelect 

Type of FOBT 

Figure 4 Component costs of FOBT screening – Hemoccult Sensa versus HemeSelect 


Cancer treatment 

Colonoscopy 

FOBT 

For both FOBTs, the cost of treating cancer is lower than under the current no screening 

scenario. The model estimates that the average cost of cancer treatment on a per eligible 

participant basis is $1187. This cost is reduced to $1084 and $1101 in the Hemoccult 

Sensa and HemeSelect arms of the model, respectively. The lower cost is the result of 

earlier detection of cancer, thereby reducing lifetime treatment costs, and detection of 

adenomas, which can be treated before the chance of malignant transformation. 

Outcomes 

As expected from the relatively similar participation rates, invitees in the Hemoccult 

Sensa and HemeSelect arms of the economic model received, on average, a similar 

number of screening tests, that is 5.6 and 6.4, respectively. The difference is driven by the 

differing participation rates. Therefore, a greater difference in participation rates would 

create a greater difference between tests. Although both tests yield higher lifeexpectancies 

for individuals, the difference between Hemoccult Sensa and HemeSelect is 

marginal (Table 29). 

Table 29 Life-expectancy from the beginning of the economic model 

Patient group Life-expectancy from the 

beginning of the model (years) 

Patients screened with Hemoccult Sensa 15.497 

Incremental life-expectancy from 

the beginning of the model (years) 

Patients screened with HemeSelect 15.492 0.005 


The positive difference in life-expectancy between screening and no screening is largely 

driven by earlier detection. In the case of Hemoccult Sensa versus HemeSelect, the most 

important driver of this difference is the difference in the number of adenomas detected. 

This is, in turn, driven by the different sensitivity rates for adenoma detection associated 

with each FOBT. Improved detection of Dukes’ A stage CRC also plays a role in 

improving the life-expectancy of individuals in the screening arms of the economic model. 

The pattern of detection is highlighted in Figure 5. 

Number detected from 20,000 invited individuals 

600 

500 

400 

300 

200 

100 

0 

Total 

cancers 

detected by 


Adenoma Dukes' A Dukes' B Dukes' C Dukes' D 

Hemoccult Sensa 

HemeSelect 

Figure 5 Pattern of neoplasm detection in the Hemoccult Sensa versus HemeSelect screening analysis 

Note that adenoma detection illustrated includes detection of all adenomas, whether premalignant or otherwise. 

Earlier detection of cancer improves the chances of survival, due to better chances of 

successful treatment. For example, 89% of patients detected with Dukes’ A survive five 

years of disease before moving on to have a ‘normal’ life-expectancy. This contrasts with 

a zero chance of survival for patients detected with Dukes’ D stage CRC (Table 17). 

FOBT screening consistently detects a greater number of cancers in patients at early 

stages. This is to be expected, given that CRC will be detected before patients are 

symptomatic. Importantly, screening detects substantially more cancers at Dukes’ stage 

A, thereby increasing the life-expectancy of the screening population. 

As shown in Figure 5, screening with either FOBT also detects a significant number of 

adenomas, premalignant or otherwise. Through the detection of adenomas, and their 

consequent removal, the incidence of CRC can be markedly reduced. In turn, this 

increases the life-expectancy of those undergoing screening and reduces potential costs. 

Detection of adenomas through screening with either FOBT will prevent the 

development of CRC in approximately 2.2–2.5% of the invited population. It is 

important to note, however, that this figure is correlated with the participation rate of the 

invited population. By assumption, patients not undergoing screening do not have 

adenomas detected, as they remain asymptomatic. Therefore, a greater difference in 

participation rates would create a greater difference between tests. 


Of the two tests, Hemoccult Sensa detects more adenomas and early-stage cancers via 

screening than HemeSelect, due to better test sensitivity for the detection of CRC. 

The distribution of stage of neoplasm detection for this analysis is presented in Figure 6. 


3000 

2500 

2000 

1500 

1000 

500 

0 

Total adenomas 

detected by 


Total cancers 

detected by 


Total cancers 

presenting 

symptomatically 

Total cancers 

undetected at death 

Figure 6 Method of neoplasm detection in the Hemoccult Sensa versus HemeSelect analysis 

Hemoccult Sensa 

HemeSelect 

No screening 


The available evidence indicates that each of the tests offer acceptable value-for-money 

against the current practice of no screening. Incremental costs are low, with a net benefit 

in terms of life-expectancy. Additionally, adverse events arising from the screening 

program are minimal. 

More importantly, based on the current data, Hemoccult Sensa appears to offer benefits 

over HemeSelect at what would normally be considered a reasonable price premium. 

Specifically, Hemoccult Sensa is associated with an extra cost of $21,534 per additional 

life-year gained (Table 30). Hemoccult Sensa thus appears to offer acceptable value-formoney 

over HemeSelect in a general population biennial FOBT screening program for 

CRC in patients aged between 55 and 74 years. However, the difference in lifeexpectancy 

between the tests is marginal. 

Table 30 Relative cost-effectiveness of Hemoccult Sensa over HemeSelect 

Hemoccult Sensa HemeSelect Incremental 

Total cost associated with screening option $1531.88 $1427.84 $104.04 

Life-expectancy from the beginning of the model 15.497 15.492 0.005 

Incremental costs per life-year gained $21,533.72 


Hemoccult versus HemeSelect 

Costs 

In a head-to-head comparison of Hemoccult and HemeSelect, HemeSelect is the more 

costly alternative. HemeSelect is associated with an average cost of $1449 per individual 

invited to screening. This compares to an average of $1334 in the Hemoccult arm of the 

economic model. The average cost of colonoscopy per eligible individual (driven by the 

frequency of colonoscopy) is a key driver in this differential, with colonoscopy costs 

representing 14% of costs in the HemeSelect arm and 7% in the Hemoccult arm. 

Cancer treatment costs, however, are lower in the HemeSelect arm, due to the greater 

sensitivity for detection. Earlier detection of CRC and adenomas means that lifetime 

treatment costs are reduced. These costs are lower in both of the screening arms than 

they are in the non-screening arm, for the same reason. 

A breakdown of the estimated costs associated with the use of Hemoccult versus 

HemeSelect in a population health screening program appears in Figure 7. 

Cost per individual invited to screening 

$1,600 

$1,400 

$1,200 

$1,000 

$800 

$600 

$400 

$200 

$0 


Type of FOBT 

Figure 7 Component costs of FOBT screening – Hemoccult versus HemeSelect 



Colonoscopy 

FOBT 

Outcomes 

The difference in the average number of FOBTs administered per invited individual is 

minimal, being 6.3 in the HemeSelect arm and 6.1 in the Hemoccult arm. As in the 

previous comparison (Hemoccult Sensa versus HemeSelect), this small difference is 

driven by the different participation rates. 

The difference in the life-expectancy of individuals invited to screening between these 

two FOBTs is marginal, despite notable differences in the sensitivity and specificity of 

the tests for CRC detection (Table 31). This is largely the result of the relatively low 

prevalence combined with repeated screening, equivalent sensitivity for adenoma 

detection and relatively similar participation rates. 


Table 31 Life-expectancy from the beginning of the economic model 

Patient group Life-expectancy from the beginning 

of the model (years) 

Patients screened with Hemoccult 15.465 

Incremental life-expectancy from the 

beginning of the model (years) 

Patients screened with HemeSelect 15.501 –0.036 

Screening with either Hemoccult or HemeSelect consistently detects more abnormalities 

than no screening. Importantly, there are improved rates of detection of both adenomas 

and early-stage CRC. Detection of adenomas has the potential to reduce the incidence of 

CRC, while early detection of cancer both improves life-expectancy and reduces lifetime 

treatment cancer costs. The distribution of stage of neoplasm detection for this analysis 

is presented in Figure 8. 


500 

450 

400 

350 

300 

250 

200 

150 

100 

50 

0 

Total cancers 

detected by 


Adenoma Dukes' A Dukes' B Dukes' C Dukes' D 

Figure 8 Pattern of detection in the Hemoccult versus HemeSelect screening analysis 

Note that adenoma detection illustrated includes detection of all adenomas, whether premalignant or otherwise. 

Hemoccult 

HemeSelect 

Of the two tests, HemeSelect appears more efficient in detecting CRC, though the 

difference in life-expectancy is marginal. Note that with equal sensitivity rates for 

adenoma detection between the FOBTs, the life-expectancy difference is driven by the 

difference in CRC sensitivity rates alone. This substantial difference causes a larger 

incremental difference in life-expectancy than occurs in the Hemoccult Sensa versus 

HemeSelect analysis. 



3000 

2500 

2000 

1500 

1000 

500 

0 

Total adenomas 

detected by 


Total cancers 

detected by 


Total cancers 

presenting 


Total cancers 

undetected at death 

Figure 9 Method of neoplasm detection in the Hemoccult versus HemeSelect analysis 


HemeSelect 


Figure 9 gives a breakdown of the method of detection in the Hemoccult versus 

HemeSelect analysis, illustrating that fewer cancers are left either undetected or are 

detected symptomatically in the screening arms compared with the no screening arm. 


Superficially, HemeSelect appears to offer a health benefit at what would normally be 

considered an acceptable price premium. Specifically, the relative cost-effectiveness of 

HemeSelect over Hemoccult is $3172 per life-year gained (Table 32). 

Table 32 Relative cost-effectiveness of Hemoccult over HemeSelect 

Hemoccult HemeSelect Incremental 

Total cost associated with screening option $1333.65 $1448.89 –$115.24 

Life-expectancy from the beginning of the model (years) 15.465 15.501 –0.036 

Incremental costs per life-year gained $3172.10 


Several sensitivity analyses have been conducted around key variables in order to 

illustrate how sensitive the relative cost-effectiveness measures are to change. Variables 

have been selected based on either their uncertainty or the scope of decision-makers to 

alter them through the design of the screening program. A justification for each scenario 

is presented below. 


• The frequency of screening has been increased from the base-case assumption of 

biennial testing to annual testing in order to improve understanding of how the 

frequency may affect costs and outcomes. 

• To better understand how the age of the eligible population may affect the costeffectiveness 

of various FOBTs, the age of the screened population has been 

adjusted by five years in either direction. Through the correlation between risk and 

age, it is expected that this will affect cost-effectiveness. 

• An analysis has been conducted varying the sensitivity and specificity of CRC 

detection using the Hemoccult test in the Hemoccult versus HemeSelect analysis. 

This has been conducted in response to the uncertainty surrounding the estimates 

used. The results of this analysis appear in Appendix K. 


The effect of increasing the frequency of screening to annual testing 

Increasing the frequency of screening, as would be expected, increases costs. 

Additionally, there are obvious improvements in life-expectancy. In the comparison of 

Hemoccult Sensa versus HemeSelect, increasing the frequency of screening to annual 

testing causes HemeSelect to dominate over Hemoccult Sensa. That is, HemeSelect 

offers marginally better outcomes at a lower cost than Hemoccult Sensa (Table 33). 

Increasing the frequency to annual screening is not a consistently cost-effective variation 

of the screening program by comparison with biennial screening. That is, life-expectancy 

does not increase to a greater degree than associated costs. 

Table 33 The effect of increasing the frequency of screening to annual testing on relative costeffectiveness: 


Base-case analysis – biennial screening 



Life-expectancy from the beginning of the model (years) 15.497 15.492 0.005 


Annual screening 



Incremental costs per life-year gained –$6908.59 

The effect of lowering the minimum eligible age to 50 years 

Lowering the minimum eligible age effectively increases the number of screening rounds 

an individual is eligible for. Consequently costs increase due to more intensive 

monitoring. 

Furthermore, increased exposure to screening improves the effectiveness of the program 

by improving the life-expectancy of the eligible population. Importantly for the relative 

cost-effectiveness, the incremental life-expectancy difference between the two tests 

increased. Consequently, the conclusion that Hemoccult Sensa offers a marginal benefit 


at a reasonable cost is accentuated (Table 34). Lowering the eligible screening age from 

55 to 50 years improves the cost-effectiveness of Hemoccult Sensa over HemeSelect. 

Additionally, lowering the minimum eligible screening age to 50 years is more costeffective, 

compared with the base-case age of 55 years, for both FOBTs. That is, lifeexpectancy 

by comparison with no screening increases to a greater degree than the 

associated increases in costs when the minimum eligible age is reduced to 50 years. 

Table 34 The effect of lowering the eligible age to 50 years on relative cost-effectiveness: Hemoccult 

Sensa versus HemeSelect 

Base-case analysis – minimum eligible age = 55 years 





Minimum eligible age = 50 years 




The effect of increasing the maximum eligible age to 80 years 

Altering the maximum age of the eligible patient population has very little effect on the 

Hemoccult Sensa versus HemeSelect analysis (Table 35). Costs and outcomes for 

Hemoccult Sensa increase marginally. This result is expected, as adenomas detected at 

later ages have reduced chances of undergoing malignant transformation. Detection of 

adenomas drives the result in the base-case analysis to a certain degree. 

Table 35 The effect of increasing the eligible age to 80 years on relative cost-effectiveness: Hemoccult 

Sensa versus HemeSelect 

Base-case analysis – maximum eligible age = 75 years 





Maximum eligible age = 80 years 




The conclusion of this analysis remains unchanged – though the relative costeffectiveness 

of Hemoccult Sensa is improved due to the growth in the incremental 

benefit outstripping the growth in the incremental costs. 


Additionally, for both FOBTs, increasing the maximum eligible screening age to 80 years 

is less cost-effective compared with the base-case age of 75 years. That is, changes in lifeexpectancy 

by comparison with no screening increase to a lesser degree than the 

associated increases in cost when the maximum age is increased to 80 years. 


The effect of increasing the frequency of screening to annual testing 

Increasing the frequency of screening had little effect overall in the comparison of 

Hemoccult versus HemeSelect. Costs for both tests increased, along with life-expectancy, 

as one would expect from increased screening. The conclusion drawn, however, remains 

the same. Under the changed assumptions, HemeSelect still offers a greater lifeexpectancy 

benefit at a reasonable cost premium (Table 36), though the cost per lifeyear 

saved increases. 

Increasing the frequency of screening to annual testing is not a consistently cost-effective 

variation of the screening program by comparison with biennial screening. That is, lifeexpectancy 

does not increase to a greater degree than associated costs. 

Table 36 The effect of increasing the frequency of screening to annual testing on relative costeffectiveness: 


Base-case analysis – biennial screening 



Life-expectancy from the beginning of the model 

(years) 

15.465 15.501 –0.036 


Annual screening 




The effect of lowering the minimum eligible age to 50 years 

Lowering the minimum eligible age of the screening population effectively increases the 

intensity of screening. As expected, this is associated with an increase in the cost of 

screening on a per invitee basis. Additionally, the difference between the life-expectancy 

of individuals in the screening arms and the no-screening arm increased – though the 

life-expectancy associated with Hemoccult surpassed that of HemeSelect. 

Consequently, the overall conclusion is reversed. By lowering the minimum eligible 

screening age, Hemoccult offers a superior life-expectancy at a lower overall cost than 

HemeSelect (Table 37). 

Additionally, lowering the minimum eligible screening age to 50 years is more costeffective, 

compared with the base-case age of 55 years, for both FOBTs. That is, lifeexpectancy 

by comparison with no screening increases to a greater degree than the 

associated increases in costs when the minimum age is lowered to 50 years. 


Discussion 

Table 37 The effect of lowering the eligible age to 50 years on relative cost-effectiveness: Hemoccult 

versus HemeSelect 

Base-case analysis – minimum eligible age = 55 years 



Life-expectancy from the beginning of model (years) 15.465 15.501 –0.036 


Minimum eligible age = 50 years 



Incremental costs per life-year gained –$32,405.24 

The effect of increasing the maximum eligible age to 80 years 

Increasing the maximum eligible screening age also has the effect of increasing costs due 

to more intensive screening, and the life-expectancy of the eligible population is similar. 

Again, however, the overall conclusion remains unchanged – HemeSelect offers greater 

life-expectancy at a reasonable level of relative cost-effectiveness (Table 38). 

Additionally, for both FOBTs, increasing the maximum eligible screening age to 80 years 

is less cost-effective compared with the base-case age of 75 years. That is, changes in lifeexpectancy 

by comparison with no screening increase to a lesser degree than the 

associated increases in cost when the maximum age is increased to 80 years. 

Table 38 The effect of increasing the eligible age to 80 years on relative cost-effectiveness: Hemoccult 


Base-case analysis – maximum eligible age = 75 years 





Maximum eligible age = 80 years 




The results of the analyses presented above make intuitive sense. On the basis of the 

available head-to-head comparison data, FOBT screening for CRC appears to be 

associated with a marked shift in the stage of diagnosis of CRC (Figure 5 and Figure 8). 

Most importantly, early detection of adenomas prior to malignant transformation allows 

CRC development to be circumvented through earlier treatment initiation, thereby 

avoiding increased risk of mortality and expensive cancer treatment costs. Based on these 

data, the model confirms that early diagnosis of CRC and adenomas results in greater 

life-expectancy in the eligible screening population. Although the costs associated with 


screening are higher, the difference appears to be at the lower margin of what is generally 

considered acceptable. 

The model aims to identify the most promising FOBTs for general population CRC 

screening. As discussed above, head-to-head comparisons have been made between 

various FOBTs and it is inappropriate to draw comparisons across the head-to-head 

scenarios presented. 

The economic model nevertheless reveals a general trend. There appears to be, based on 

the available data, small differences in the life-expectancy gains provided between the 

pairs of FOBTs tested. These differences are driven by the varying sensitivity rates 

utilised in each of the analyses. The level of certainty associated with this result would, 

however, be improved if the economic model were based on a greater body of clinical 

evidence. 

The base-case scenario of the model assumes biennial screening in individuals aged 55– 

74 years. The analyses show that Hemoccult Sensa is cost-effective relative to 

HemeSelect, with a cost of $21,533 per life-year gained. In a separate analysis, 

HemeSelect was shown to be cost-effective relative to Hemoccult, at a cost of $3172 per 

life-year gained. Again, it is inappropriate to draw conclusions across these comparisons. 

In light of the small differences in absolute life-expectancy between the different FOBTs 

and the uncertainty surrounding these estimates, considerations of the overall costs of 

the different FOBTs may become important. The total cost of colonoscopy is a key 

determinant in this cost difference (Figure 4 and Figure 7), primarily reflecting the 

specificity of the various tests. Thus, the overall costs associated with HemeSelect ($1420 

per individual invited to screening) were lower than those of Hemoccult Sensa ($1502 

per individual invited to screening). Similarly, the overall cost of Hemoccult ($1316 per 

individual invited to screening) was lower than that of HemeSelect ($1440 per individual 

invited to screening). Therefore, the average cost of colonoscopy associated with each 

FOBT is a key driver of overall costs by determining the intensity of resource wastage 

through false positive results. 

The issues surrounding the importance of the cost differences must be emphasised, as 

there is a degree of uncertainty associated with the costs themselves. Specifically, the cost 

of an adverse event following colonoscopy is based on the best available estimate, 

though it may be incorrect in the current environment. This is unlikely to have an effect 

on the overall conclusion, however, given the low proportion of individuals subject to 

this cost. 

Additionally, there is uncertainty surrounding the estimates of the costs of some of the 

FOBTs themselves. The costs used in the model are based on the best currently available 

information. These prices may change once a screening program is in place. This is 

unlikely to have a major effect on the relative cost-effectiveness. 

A final issue surrounding costs concerns the cost estimate for colonoscopy. The 

components making up the ‘associated costs’ of colonoscopy are unclear, making reestimation 

in the current setting difficult. As colonoscopy costs are a significant driver of 

the cost difference in all analyses, this is of notable importance. 

Significantly, there are factors other than relative cost-effectiveness which are of 

importance to decision-makers when considering the establishment of a population 


health screening program. This may include, for example, the importance of public 

confidence in a screening program. The World Health Organization recommendations 

for choice of FOBT for CRC screening indicate that resource availability to fund the 

additional costs associated with follow-up colonoscopy is a key factor in the decisionmaking 

process (Young et al 2002). The reliability of subject compliance with the diet 

and drug restrictions required with the use of guaiac tests may also influence choices 

made (Young et al 2002). 

Improving participation will logically lead to the detection of more neoplasms in practice, 

therefore increasing the effectiveness of any screening program. Participation will not, 

however, have a major impact upon the relative cost-effectiveness between different 

FOBTs as a change in participation will shift both costs and effectiveness in the same 

direction, thus having a minimal impact on the incremental cost-effectiveness ratio. 

Altering key variables of uncertainty generally yielded little difference in the relative costeffectiveness 

between FOBTs or in the conclusions drawn. These changes, however, do 

provide insight into general ways in which the screening program may be designed to 

maximise its cost-effectiveness compared with the no-screening option. Importantly, 

these conclusions are drawn from the head-to-head comparison data, making them 

impossible to quantify with certainty without utilising data comparing a particular 

FOBT’s efficacy with no screening. Despite this, they do provide good indications as to 

the direction of change brought about by alterations in key variables/designs of the 

screening program. 

Increasing the screening frequency from biennial to annual increases both costs and 

effectiveness, both of which are the result of more intensive monitoring of the screening 

population. This is an intuitive result. In terms of cost-effectiveness, previous studies 

tend to find annual screening less cost-effective than biennial screening (Bolin et al 1999; 

O’Leary et al 2002; Gyrd-Hansen 1998). 

Lowering the minimum eligible screening age from 55 to 50 years appears to offer 

benefits. Although costs do increase, earlier detection of adenomas and, to a lesser 

extent, early-stage CRC, has considerable benefits in terms of cost-effectiveness. The 

available data indicate that lowering the screening age to 50 may be a viable method of 

increasing the cost-effectiveness of FOBT screening versus no screening. 

Increasing the maximum screening age to 80 years does not appear to offer the same 

degree of benefit. This makes intuitive sense. Expanding the screening population in 

such a way is unlikely to offer benefits in terms of early adenoma detection and 

consequent reduction of CRC-induced mortality. It is not expected that such a design 

would prove cost-effective. 

All of the issues above are subject to the disclaimer that the available clinical outcomes 

data used in the economic model were substantially limited. Consequently, the relative 

cost-effectiveness ratios may be subject to change should more data become available. 


Conclusions 

Safety 

Faecal occult blood tests (FOBTs) are non-invasive and therefore unlikely to cause 

adverse events. Safety issues that have been raised previously in association with the use 

of FOBTs in a screening setting relate to a) the potential to increase the number of 

adverse events associated with follow-up diagnostic procedures and b) the psychological 

impact of colorectal cancer (CRC) screening. 

International randomised controlled trials (RCTs) have reported low complication rates 

associated with diagnostic follow-up from the use of the Hemoccult FOBT for 

population health screening. 

The head-to-head studies identified in this assessment examining the relative 

performance of different FOBTs did not report any safety data. Therefore, the 

performance of alternative FOBTs for population health screening cannot be assessed 

on the basis of safety data. 

Effectiveness 

There are two types of FOBTs in common use: the long established guaiac tests and the 

newer immunochemical tests. A key issue addressed in this review was the relative 

performance of guaiac versus immunochemical FOBTs when used for population health 

screening. Very few head-to-head studies providing estimates of the sensitivity and 

specificity of different commercially produced FOBTs in the detection of CRC were 

identified. Slightly more studies were available which enabled a comparison of the 

relative true positive rates (TPRs) and false positive rates (FPRs) of these tests in 

population health screening. There were no studies of a suitable quality available to 

enable assessment of the relative accuracy of the different FOBTs for the detection of 

adenomas. 

A comparison of Hemoccult, a guaiac test, and HemeSelect, a reversed passive 

haemagglutination (RPHA) test (which is a type of immunochemical test) was conducted. 

On the basis of two trials utilising the interval cancer rate as an indicator of false negative 

results, HemeSelect was found to be significantly more sensitive than Hemoccult; 

however, Hemoccult was significantly more specific than HemeSelect. This result was 

maintained in a sensitivity analysis incorporating a study conducted in a population with a 

high proportion of participants that were at increased risk of disease. Similarly, the 

relative TPR for detecting CRC was significantly in favour of pooled RPHA tests 

(HemeSelect and Immudia-HemSp) rather than Hemoccult, whereas the FPR of 

Hemoccult was lower than for RPHA. The practical impact of this trade-off cannot be 

determined by these measures alone and have been investigated via the use of an 

economic model. 

A comparison of the guaiac Hemoccult test and Fecatwin Sensitive/Feca EIA, a ‘twotier’ 

test which incorporated both guaiac and immunochemical tests conducted in a tiered 

fashion, was also performed. In a single study, the sensitivities of Hemoccult and 


Fecatwin Sensitive/Feca EIA were not significantly different; however, Hemoccult was 

significantly more specific than Fecatwin Sensitive/Feca EIA. Similarly, the TPR for 

detecting CRC was not significantly different when Hemoccult was compared to 

Fecatwin Sensitive/Feca EIA; however, the FPR of Hemoccult was lower than Fecatwin 

Sensitive/Feca EIA. Therefore, based on these limited data, Hemoccult is statistically the 

more accurate test of these two, when used for population health screening. 

A comparison of an alternative guaiac test, Hemoccult Sensa, versus the 

immunochemical test HemeSelect was also performed. The sensitivity of Hemoccult 

Sensa and HemeSelect were not significantly different; however, HemeSelect proved to 

be significantly more specific than Hemoccult Sensa, based on data from a single study. 

This result was maintained in a sensitivity analysis incorporating a study conducted in a 

population with a high proportion of participants who were at increased risk of disease. 

The TPR was not significantly different when Hemoccult Sensa was compared with 

HemeSelect, whereas the FPR of HemeSelect was significantly lower than that of 

Hemoccult Sensa. Therefore, based on these limited data, HemeSelect is statistically the 

more accurate test of the two, when used for population health screening. 

Newer immunochemical tests are currently commercially available. Other 

immunochemical FOBTs with similar technical characteristics (ie, in vitro diagnostic 

accuracy for the detection of haemoglobin) may provide similar outcomes to those of 

HemeSelect. However, there is currently a lack of evidence for this and the performance 

of other immunochemical tests in the context of population health screening for CRC 

remains to be determined. 

It is important to note that the measures of the sensitivity and specificity of the FOBTs 

for the detection of CRC varied considerably between studies conducted in different 

populations. In addition, estimates of these measures differed significantly between 

different tests of the same class. Therefore, relative findings for any individual pairs of 

guaiac and immunochemical tests cannot be generalised across comparisons and findings 

for any individual test do not represent all tests of that type. 

A modelled economic evaluation was used to determine the effectiveness and costeffectiveness 

of the different tests in a population screening setting. This model was built 

upon the sensitivity and specificity data summarised above and was able to determine the 

broader population-wide impact of the sensitivity and specificity of these tests. 


The economic model indicates that FOBTs with greater sensitivity for colorectal 

neoplasia detection will offer better overall survival outcomes. A key driver of the 

difference in the total cost associated with the FOBTs is the specificity. Tests with lower 

specificities are associated with higher diagnostic follow-up costs due to the increased 

levels of resource wastage. 

The model attempts to present the trade-off between these values in an economic 

context by providing estimates of the incremental cost per life-year gained for each pair 

of tests compared. The base-case scenario assumes biennial screening in individuals aged 

55–74 years. 


The incremental cost per life-year gained of HemeSelect was $3172 in a comparison 

against Hemoccult. For Hemoccult Sensa in a comparison against HemeSelect, the 

incremental cost per life-year gained was $21,533. These findings should, however, be 

constrained to the context of the head-to-head data upon which they are based. That is, 

the magnitude of the difference in the sensitivity between tests contains a level of 

uncertainty. This is particularly due to the low prevalence of CRC in the populations 

tested in the FOBT studies and the scarcity and poor quality of data providing estimates 

of the sensitivity for adenoma detection. Consequently, use of these data in the economic 

model may render the results of the economic model equally uncertain. 

However, the absolute estimates of the difference in specificity between tests are more 

reliable than the estimates of the sensitivity. Similarly, the results concerning costs of the 

FOBTs, inclusive of diagnostic follow-up and treatment, are more reliable than the 

modelled life-expectancy, due to the quality of the estimates that they are based upon. 

Therefore, the tests associated with the higher specificity were shown to be less costly 

overall, with the impact of sensitivity upon effectiveness of uncertain magnitude. This 

implies that the most promising tests in an economic sense may be those associated with 

a high specificity. 

The results of these analyses for the immunochemical tests used may reflect those for 

FOBTs with similar technical characteristics (ie, diagnostic accuracy for the detection of 

haemoglobin). However, there is currently a lack of suitable comparative evidence for the 

performance of other immunochemical FOBTs in the context of population health 

screening for CRC. 

Other important findings of the economic model include the following. 

• There was no apparent class effect in determining the relative cost-effectiveness of 

different FOBTs. 

• Increasing participation will lead to increased cancer detection and an increase in the 

effectiveness of any screening program. Participation will not, however, have a major 

impact upon the relative cost-effectiveness between different FOBTs as a change in 

participation will shift both costs and effectiveness in the same direction, thus having 

a minimal effect on the incremental cost per life-year gained. 

• Altering key variables endogenous to the screening program generally yielded little 

difference in the relative cost-effectiveness between FOBTs. However, these 

sensitivity analyses did demonstrate consistent trends which provide insight into 

methods which may maximise the cost-effectiveness of screening by comparison 

with no-screening. 

• Increasing the screening frequency from biennial to annual increases both costs and 

effectiveness. Within the context of the main analyses, it appears that annual FOBT 

screening is not cost-effective compared to biennial screening. 

• Changing the minimum eligible screening age from 55 to 50 years appears to offer 

benefits in terms of cost-effectiveness. 

• Increasing the maximum screening age from 75 to 80 years does not appear to offer 

the same degree of benefit. 


It is important to note that the reliability of the above findings is dependent upon the 

reliability of the clinical data available to make head-to-head comparisons between the 

FOBTs. An improvement in the quantity, quality and external validity of head-to-head 

study data is required to validate the findings of the economic model. 


Summary of outcomes 

The Medical Services Advisory Committee (MSAC) considers that faecal occult blood 

testing is useful for population health screening to reduce colorectal cancer (CRC) 

mortality. 

The available evidence indicated that there was no apparent class effect of the guaiac 

versus immunochemical faecal occult blood tests (FOBTs) with regard to their 

effectiveness or cost-effectiveness. 

Different brands of FOBTs possess different sensitivities and specificities for the 

detection of CRC within an average-risk screening population setting. The specificity of 

the FOBTs was a major determinant of the total associated costs of FOBT screening, 

inclusive of diagnostic follow-up and treatment. 

An economic model indicated that biennial screening was more cost-effective than 

annual screening, within the context of the main analysis. Lowering the minimum eligible 

screening age from 55 to 50 years offered benefits in terms of cost-effectiveness. 

Increasing the maximum screening age from 75 to 80 years did not offer the same degree 

of benefit. 

The immunochemical tests included in the assessment are no longer available as they 

have been replaced by newer assays. There was no available evidence suitable for the 

assessment of the comparative performance of currently available immunochemical tests 

within an average-risk population health screening setting. However, the results of the 

analyses of the immunochemical tests used may reflect those for FOBTs with similar 

technical characteristics (ie, in vitro diagnostic accuracy for the detection of haemoglobin). 

Therefore, it is suggested that currently available and new immunochemical tests with 

promising technical characteristics be evaluated against established FOBTs within the 

context of an ongoing screening program. 


Appendix A MSAC terms of reference and 

membership 

MSAC's terms of reference are to: 

• advise the Minister for Health and Ageing on the strength of evidence pertaining to 

new and emerging medical technologies and procedures in relation to their safety, 

effectiveness and cost-effectiveness and under what circumstances public funding 

should be supported; 

• advise the Minister for Health and Ageing on which new medical technologies and 

procedures should be funded on an interim basis to allow data to be assembled to 

determine their safety, effectiveness and cost-effectiveness; 

• advise the Minister for Health and Ageing on references related either to new and/or 

existing medical technologies and procedures; and 

• undertake health technology assessment work referred by the Australian Health 

Ministers’ Advisory Council (AHMAC) and report its findings to AHMAC. 

The membership of MSAC comprises a mix of clinical expertise covering pathology, 

nuclear medicine, surgery, specialist medicine and general practice, plus clinical 

epidemiology and clinical trials, health economics, consumers, and health administration 

and planning: 

Member Expertise or affiliation 

Dr Stephen Blamey (Chair) General surgery 

Associate Professor John Atherton Cardiology 

Professor Bruce Barraclough General surgery 

Professor Syd Bell Pathology 

Dr Michael Cleary Emergency medicine 

Dr Paul Craft Clinical epidemiology and oncology 

Dr Gerry FitzGerald AHMAC representative 

Dr Kwun Fong Thoracic medicine 

Professor Jane Hall Health economics 

Dr Terri Jackson Health economics 

Professor Brendon Kearney Health administration and planning 

Associate Professor Richard King Internal medicine 

Dr Ray Kirk Health research 

Dr Michael Kitchener Nuclear medicine 

Dr Ewa Piejko General practice 

Ms Sheila Rimmer Consumer health issues 

Dr Jeffrey Robinson Obstetrics and gynaecology 

Professor John Simes Clinical epidemiology and clinical trials 


Professor Bryant Stokes Neurological surgery 

Professor Ken Thomson Radiology 

Dr Douglas Travis Urology 


Appendix B Advisory panel 

Advisory panel for MSAC reference 18 

Faecal occult blood testing for population health screening 

Professor Brendon Kearney AM (Chair) 

MB BS FRACP FRACMA 

Executive Director Clinical Systems 

SA Department of Human Services 

Adelaide, SA 

Professor Syd Bell 

MD BS FRCPA FAFPHM(RACP) 

SEALS Prince of Wales Hospital 

Randwick, NSW 

Dr David Deam 

MB BS MAACB FRCPA 

Gribbles Pathology 

Clayton, VIC 

Professor Les Irwig 

MBBCh PhD FFPHM 

School of Public Health 

University of Sydney 

Sydney, NSW 

Ms Alex Lloyd 

Department of Health and Ageing 

Canberra 

ACT 

Associate Professor Michael Solomon 

MB BCH BAO(Hons) LRCSI LRCPI MSc 

FRACS 

Royal Prince Alfred Hospital 

Newton, NSW 

Elizabeth Symons 

RN GradDip AE&T PGradDipEval 

Independent Consumer Representative 

Highton, VIC 

Member of MSAC 

Member of MSAC 

Nominated by the Royal 

College of Pathologists 

of Australasia 

Co-opted member 

Project manager 

Nominated by the 

Colorectal Surgical 

Society of Australasia 


Consumers’ Health 

Forum 


Professor Graeme Young 

MBBS MD FRACP 

Department of Gastroenterology and Hepatology 

Flinders Medical Centre and Repatriation Hospital 

Bedford Park, SA 


Gastroenterological 

Society of Australia 


Appendix C Studies included in the review 

Table 39 Relevant studies identified 

Specificity 

carcinoma 

n/N (%) 

Sensitivity 

carcinoma 

n/N (%) 

PPV 

neoplasm 

n/N (%) 

PPV 

carcinoma 

n/N (%) 

FOBTs 

Included in final 

assessment? 

(QS) 

LoE 

Long-term 

follow-up 


multiple tests in a 

single patient 


Population 

(ITS) 

Study 

7845/8030 

(97.7) 

13/35 

(37.1) 

46/198 

(23.2) 

13/198 

(6.6) 

Hemoccult II 

Y 

(7) 

1 

6824/7870 

(86.7) 

27/34 

(79.4) 

99/1073 

(9.2) 

27/1073 

(2.5) 


Sensa 

Yes, 2 years 

review of 

insurance 


neoplasms 

(96% of 

subjects) 


Positive FOBT: 

colonoscopy; 

Hemoccult II Sensa 

positive: FSa 7043/7461 

(94.4) 

22/32 

(68.8) 

90/440 

(20.5) 

22/440 

(5.0) 

HemeSelect 

1261/1298 

(97.2) 

3/6 

(50.0) 

28/40 

(70.0) 

3/40 

(7.5) 

Hemoccult (no 

dietary 

restriction) 

Y 

(6) 

1 

1197/1298 

(92.2) 

5/6 

(83.3) 

27/106 

(25.5) 

5/106 

(4.7) 

Feca EIA b 

Yes, 1 year 

review of 

hospital 

pathology 


neoplasms 

(Hardcastle et 

al 1986) 


Positive: history, exam, RS 

and 60 cm fibreoptic 

sigmoid. 

Then if carcinoma: DCBE; 

adenoma: colonoscopy; no 

neoplasm: DCBE 

If negative follow-up: 

repeat FOBT, if positive, 

gastroscopy 

Hemoccult (no 

dietary 

restriction) 


– 

– 

– 

– 

N 

Guaiac to guaiac 

comparison 

1 

Yes, 2 years 

follow-up for 

colonic 

symptom 

presentation to 

GP 


Fecatwin 

(guaiac) 

Positive: history, exam, 

RS, sample obtained on 

exam tested with 

Haemostix. Then if positive 

or pathology suspected: 

full investigation 

If negative: repeat FOBT 

after 3 months 

Members of 

non-profit US 

private health 

insurer 

electing health 

appraisal, 

≥ 50 years; 

N = 10,702 

Individuals 

from GP 

registers (UK), 

45–75 years; 

N = 3225; 

excluded 

known large 

bowel disease 

patients 

GP patient 

attendees 

(UK), 

> 40 years; 

N = 640 

(group 1) 

Allison et al 

1996a 

Armitage et 

al 1985 

Barrison and 

Parkins 

1985b 

Rehydrated 

Hemoccult I 

– 

– 

– 

– 

N 

Rehydrated 

1 

Yes, 2 year 

repeat FOBT 

screening in 

25% of 

subjects 


HemeSelect 

No 

Shionogi B 

Parallel arm with 

historical cohort 

Immudia- 

HemSp 

N 

Low quality of 

evidence 

3b 

Positive HO and/or 

positive/borderline 

HSelect: pancolonoscopy 

or left colonoscopy plus 

DCBE when 

pancolonoscopy not 

possible 

Positive, symptomatic or 

FH CRC: exam, FS and 

DCBE 

General 

population 

(Italy) 

40–70 years; 

N = 24,282 

Castiglione 

et al 1997 

Mass 


(Japan) 

> 40 years; 

N = 18,497 

Fujita et al 

1992

Specificity 

carcinoma 

Sensitivity 

carcinoma 

PPV 

neoplasm 

PPV 

carcinoma 

FOBTs 


assessment? 

(QS/12) 

LoE 

Long-term 

follow-up 






Study 

16/410 

(3.9) 

8/410 

(2.0) 

No 



All: FS 

Positive: DCBE or colonoscopy 

Individuals presenting for 

health care examination 

(Japan); most 50–59 years 

(mean 52 years); N = 6437 

Iwase 1992 

– 

– 

Y 

(5) 

1 

44/391 

(11.3) 

16/391 

(4.1) 

Immudia- 

HemSp 

– 

– 

– 

– 


(unhydrated) 

Hydrated 



Sensa 

No 


Positive: full colonoscopy or FS 

+ DCBE 

N 

Guaiac to guaiac 

comparison 

1 

60/456 

(13.2) c 

16/456 

(3.5) c 

No 




– 

– 

104/849 

(12.2) c 

19/849 

(2.2) c 


Sensa 

Y 

(5) 

1 

Positive: mixed, including 

exam, repeat FOBT, DCBE, 

sigmoid, colonoscopy or an 

upper gastrointestinal barium 

series. 70% had DCBE or 

colonoscopy 

General population (US, 

distribution through 

pharmacies and 

community groups 

following media campaign) 

≥ 50 years; N = 85,931 

General population (US, 

distribution through 

selected pharmacies 

following media campaign) 

> 30 years; N = 39,000 

Levin et al 

1997 

Petrelli et al 

1994 

66/438 

(15.1) c 

21/438 

(4.8) c 

HemeSelect 

1462/1478 

(98.9) b 

1/11 

(9.1) a,b 

9/17 

(52.9) 

1/17 

(5.9) 


Y 

(6) 

1 

1344/1478 

(90.9) b 

11/11 

(100) b 

57/145 

(39.3) 

9/145 

(6.2) 

HemeSelect 

Yes, median 

35 months by 

GP information 

and review of 

hospital 

pathology 


neoplasm 


Positive: exam, sigmoid and 

colonoscopy/FS & DCBE 

Individuals from GP 

registers (UK) 

50–75 years; N = 4018; 

known colorectal 

neoplasm, advanced 

visceral malignancy or 

unfit for further 

investigation excluded 

Robinson et 

al 1995 

No 


437/522 

(83.7) 

3/5 

(60.0) 

21/88 

(23.9 

3/88 

(3.4) 


Sensa 

All had endoscopy, FS (41%) or 

total colonoscopy (59%, 

including FOBT positive) 

Consecutive attendees at 

CRC screening service 

(95% asymptomatic); 

N = nr (527 screened) 

Rozen et al 

1995 

Y 

(Sensitivity 

analysis) 

(4) 

1 

467/522 

(89.5) 

4/5 (80.0) 

17/59 

(28.8) 

4/59 

(6.8) 

BM-Test Colon 

Albumin

Specificity 

carcinoma 

Sensitivity 

carcinoma 

PPV 

neoplasm 

PPV 

carcinoma 

FOBTs 


assessment? 

(QS) 

LoE 

Long-term 

follow-up 






Study 

377/398 

(94.7) 

3/5 

(60.0) 

7/24 

(29.2) 

3/24 

(12.5) 

No 



All had endoscopy, 59% at time 

of study 

366/398 

(92.0) 

3/5 

(60.0) 

8/35 

(22.9) 

385/398 

(96.7) 

4/5 

(80.0) 

6/17 

(35.3) 

390/398 

(98.0) 

4/5 

(80.0) 

8/12 

(66.7) 

3/35 

(8.6) 

4/17 

23.5 

4/12 

(33.3) 


Sensa 





Rozen et al 

1997 

FlexSure OBT 

Y 

(Sensitivity 

analysis) 

(5) 

1 

HemeSelect 

1332/1403 

(95.2) 

3/7 

(42.9) 

19/74 

(25.7) 

3/74 

(4.1) 


Sensa 

1382/1403 

(98.6) 

3/7 

(42.9) 

10/24 

(41.7) 

3/24 

(12.5) 

FlexSure OBT 

Y 

(Sensitivity 

analysis) 

(5) 

1 

Yes, > 2 years 

clinical followup 

in 4 

subjects with 

positive FOBT 

who refused 

colonoscopy 


All had full colonoscopy or FS, 

48% at time of study 





Rozen et al 

2000 


16/68 

(23.5) 

1/68 

(1.5) 


Sensa 

No 


Positive: colonoscopy 

– 

– 

11/41 

(26.8) 

1/41 

(2.4) 

HemeSelect 

Y 

(Sensitivity 

analysis) 

(5) 

1 

Participants in screening 

program (screenees: 

individuals with FH CRC 

(80%) and community 

volunteers); 45–79 years; 


St John et al 

1993 

(Screenees) 


– 

– 

– 

– 

N 

Low quality of 

evidence 

3b 

Yes, cancer 

registry data 

over 5 years & 

negative 

FOBTs 

rescreened in 

2.5 years 

Parallel arms, 

non-randomised 

Total colonoscopy or 

colonoscopy & DCBE 

General population (Italy) 

50–70 years; N = nr 

(41,744 screened) 

Zappa et al 

2001 

RPHA 

(HemeSelect; 

Immudia-- 

HemSp) 

Abbreviations: CRC, colorectal cancer; DCBE, double contrast barium enema; Fecatwin, Fecatwin Sensitive/Feca EIA; FH, family history; FOBT, faecal occult blood test; FS, flexible sigmoidoscopy; GP, general practice; HSelect, 

HemeSelect; HO, Hemoccult; ITS, intention to screen; LoE, level of evidence; nr, not reported; PPV, positive predictive value; QS, quality score; RPHA, reverse-passive haemagglutination; RS, rigid sigmoidoscopy. 

aAssumes that the patient developing cancer during follow-up for adenoma initially tested negative with Hemoccult. bTaken from Robinson et al (1996). cTotal positives calculated from number of patients screened and percentage 

positivity rate as reported, authors were contacted for data confirmation but no response was received.

Appendix D Literature searches 

Medline search strategy 

The search strategy used to identify relevant studies of faecal occult blood tests (FOBTs) 

in Medline is presented in Table 40. 

Table 40 FOBT Medline search strategy (1966 to February week 3 2004) 

Search history Results 

1 occult blood/ 2654 

2 ((fecal or faecal) adj2 blood).ti,ab. 1679 

3 (fobt$1 or hemoccult or haemoccult).ti,ab. 748 

4 ((fecal or faecal) adj2 (haemoglobin or hemoglobin)).ti,ab. 58 

5 ((fecal or faecal) adj2 (globin or haem or heme)).ti,ab. 19 

6 or/1–5 3472 

7 exp colorectal neoplasms/ 76,016 

8 (colorect$ adj5 screen$).ti,ab. 2188 

9 or/6–7 77,631 

10 9 and exp mass screening/ 2793 

11 6 and exp "sensitivity and specificity"/ 471 

12 6 and pc.fs. 938 

13 6 and di.fs. 1745 

14 6 and ep.fs. 553 

15 or/8,10–14 4881 

16 haemoccult.ti,ab. 131 

17 fecatwin.ti,ab. 13 

18 colocare.ti,ab. 3 

19 okokit.ti,ab. 3 

20 hemofec.ti,ab. 10 

21 flexsure.ti,ab. 22 

22 hemeselect.ti,ab. 28 

23 (feca-eia or (feca adj eia) or fecaeia).ti,ab. 10 

24 ((iatro adj hemcheck) or iatro-hemcheck or iatrohemcheck).ti,ab. 2 

25 (imdia-hem or (imdia adj hem) or imdiahem).ti,ab. 0 

26 hemochaser.ti,ab. 2 

27 monohaem.ti,ab. 27 

28 (hemodia or ochemodia or oc-hemodia).ti,ab. 11 

29 (hemoglobin-haptoglobin or (hemoglobin adj haptoglobin) or hemoglobinhaptoglobin).ti,ab. 131 

30 haptoglobin.ti,ab. 3661 

31 annual bowel check.ti,ab. 0 

32 guaiac.ti,ab. 294 

33 (immunochemical and test$).ti,ab. 1699 

34 elisa.ti,ab. 50,550 

35 inform.ti,ab. 5142 

36 or/30,32–35 61,105 

37 36 and 6 291 



38 or/15–29,31,37 5103 

39 38 and exp clinical trials/ 178 

40 38 and clinical trial.pt. 322 

41 38 and (clinical adj trial$1).ti,ab. 59 

42 or/39–41 491 

43 (case adj report).ti,ab. 96,592 

44 letter.pt. 495,739 

45 historical article.pt. 206,244 

46 review of reported cases.pt. 48,682 

47 review multicase.pt. 7963 

48 or/43–47 838,778 

49 42 not 48 476 

EMBASE search strategy 

The search strategy used to identify relevant studies of FOBTs in EMBASE is presented 

in Table 41. 

Table 41 FOBT EMBASE search strategy (1980 to 2004 week 09) 


1 occult blood/ or occult blood test/ 2411 

2 ((fecal or faecal) adj2 blood).ti,ab. 1435 

3 (fobt$1 or hemoccult or haemoccult).ti,ab. 617 

4 ((fecal or faecal) adj2 (haemoglobin or hemoglobin)).ti,ab. 51 

5 ((fecal or faecal) adj2 (globin or haem or heme)).ti,ab. 16 

6 or/1–5 2986 

7 colorectal cancer/ 18,806 

8 colorectal carcinoma/ 6335 

9 colorectal tumor/ 1163 

10 (colorect$ adj5 screen$).ti,ab. 1928 

11 or/6–9 27,581 

12 11 and exp screening/ 3158 

13 6 and exp "sensitivity and specificity"/ 41 

14 6 and pc.fs. 287 

15 6 and di.fs. 1725 

16 6 and ep.fs. 473 

17 exp feces analysis/ 8053 

18 17 and exp diagnostic test/ 1404 

19 or/10,12–16,18 5155 

20 haemoccult.ti,ab,tn,mf. 105 

21 fecatwin.ti,ab,tn,mf. 16 

22 colocare.ti,ab,tn,mf. 4 

23 okokit.ti,ab,tn,mf. 2 

24 hemofec.ti,ab,tn,mf. 3 

25 flexsure.ti,ab,tn,mf. 24 



26 hemeselect.ti,ab,tn,mf. 28 

27 (feca-eia or (feca adj eia) or fecaeia).ti,ab,tn,mf. 8 

28 ((iatro adj hemcheck) or iatro-hemcheck or iatrohemcheck).ti,ab,tn,mf. 2 

29 (imdia-hem or (imdia adj hem) or imdiahem).ti,ab,tn,mf. 0 

30 hemochaser.ti,ab,tn,mf. 2 

31 monohaem.ti,ab,tn,mf. 20 

32 (hemodia or ochemodia or oc-hemodia).ti,ab,tn,mf. 13 

33 (hemoglobin-haptoglobin or (hemoglobin adj haptoglobin) or hemoglobinhaptoglobin).ti,ab,tn,mf. 79 

34 haptoglobin.ti,ab,tn,mf. 2224 

35 annual bowel check.ti,ab,tn,mf. 0 

36 guaiac.ti,ab,tn,mf. 251 

37 (immunochemical and test$).ti,ab,tn,mf. 1230 

38 elisa.ti,ab,tn,mf. 41,694 

39 inform.ti,ab,tn,mf. 4202 

40 or/34,36–39 49,392 

41 40 and 6 217 

42 40 and 18 122 

43 or/19–33,35,41–42 5318 

44 43 and exp clinical trial/ 539 

45 43 and (clinical adj trial$1).ti,ab. 85 

46 43 and ct.fs. 185 

47 or/44–46 594 

48 case study/ 3312 

49 (case adj report).ti,ab. 81,218 

50 abstract-report/ 71,109 

51 letter/ 268,678 

52 or/48–51 423,107 

53 47 not 52 578 


Appendix E Excluded references 

488 citations were excluded as they were a non-systematic review, editorial, letter; news article, 

note, survey, opinion piece, or economic analysis. 

12 citations were excluded as they were a non-human or in vitro study. 

485 citations were excluded as they were not of FOBT. 

Reasons for exclusion of all other citations are given below: 

1. Ahlquist DA, Wieand HS, Moertel CG, McGill DB, Loprinzi CL, O'Connell MJ, Mailliard 

JA, Gerstner JB, Pandya K, Ellefson RD (1993). Accuracy of fecal occult blood screening 

for colorectal neoplasia. A prospective study using Hemoccult and HemoQuant tests. 

JAMA 269: 1262-1267. 

Reason for exclusion: wrong patient group 

2. Aisawa T, Saito H, Kawaguchi H, Uno Y, Munakata A, Yoshida Y (1988). Mass screening 

for colon cancer using an immunologic fecal occult blood test by reversed passive 

hemagglutination reaction (RPHA)-comparison of single RPHA with 2-day testing, 

Proceedings of the 8th Asia-Pacific Congress of Gastroenterology FP23-FP25. 

Reason for exclusion: unavailable 

3. Archambault F, Durand G, Faivre J, Voilquin JP, Archambault P, Riou F, Ageorges P, 

Archambault ML, Delville JM, Fesneau M, et al (1989). Acceptability of the Hemoccult test 

in general medical practice. Results of a pilot study [French]. Bulletin du Cancer 76: 1071-1075. 

Reason for exclusion: wrong outcome 

4. Armitage NC, Hardcastle JD (1987). Screening for colorectal cancer–the Nottingham 

experience. Annals of the Academy of Medicine, Singapore 16: 432-436. 

Reason for exclusion: study duplication 

5. Armitage N, Hardcastle J, Leicester R (1989). Screening for colorectal cancer. Practitioner 233: 

830-833. 


6. Asao T, Kuwano H, Ide M, Hirayama I, Nakamura J-I, Fujita K-I, Horiuti R (1992). 

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compared with Buscopan. Clinical Radiology 58: 01. 


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Appendix F Positive predictive values 

Positive predictive value 

Table 42 and Table 43 present the results of meta-analyses comparing the positive 

predictive values (PPV) of individual guaiac and immunochemical faecal occult blood 

tests (FOBTs). These meta-analyses are based on the results of the nine head-to-head 

studies of FOBTs identified in the literature search. PPV is the probability that if a 

person tests positive with a FOBT then that person actually has a carcinoma and/or an 

adenoma (ie, avoid false-positives). PPV does not incorporate the probability that a 

person who tests negative may actually have the condition (ie, false-negatives). This is 

difficult to avoid in screening studies where it is generally not acceptable to subject all 

participants to an invasive ‘reference standard’ such as colonoscopy. 

PPV is only a useful comparative measure of diagnostic performance between tests when 

the tests are applied to populations with the same prevalence of disease. This means that, 

in general, PPV is only useful for comparing test performance within a study. Therefore, 

the most valid trial design for determining the comparative PPV of FOBTs is where both 

tests are applied to the same person in a ‘within-subjects’ analysis. It is only valid to 

compare PPV values in ‘between-subjects’ analysis (eg, a parallel arm study) when the 

populations undergoing each test carry the same spectrum of disease. This is most likely 

to occur in randomised controlled trials (RCTs). All of the studies included in this 

analysis employed a ‘within-subjects’ design. 

Table 42 and Table 43 include a meta-analysis where studies on HemeSelect and 

Immudia-HemSp are pooled, since these FOBTs are equivalent international versions of 

the same test (St John et al 1993; Zappa et al 2001). 

Table 42 presents the results of the meta-analyses for carcinoma alone. The table is split 

into two sections, one reporting the results of the main meta-analyses and the other 

reporting the results of a series of sensitivity meta-analyses. The main meta-analyses are 

strictly limited to the assessment of only those studies in which the participants came 

entirely from a screening population at average risk. The sensitivity meta-analyses 

includes four additional studies in which some of the participants were symptomatic or at 

increased risk (Rozen et al 1995; Rozen et al 1997; Rozen et al 2000; St John et al 1993). 

The immunochemical test HemeSelect had a greater PPV for carcinoma than Hemoccult 

Sensa (4.8% versus 2.4%, respectively). The PPV odds ratio (OR) for carcinoma for 

HemeSelect versus Hemoccult Sensa was significantly different and favoured the 

HemeSelect test (OR 2.10; 95% confidence interval (CI): 1.37, 3.26). The PPV risk 

difference (RD) was also significantly different in favour of the HemeSelect test (RD 

0.025; 95% CI: 0.009, 0.048). The difference in PPV between HemeSelect and 

Hemoccult Sensa was maintained in the sensitivity analyses (4.9% versus 2.3%, 

respectively). The PPV OR for carcinoma for HemeSelect versus Hemoccult Sensa in 

the sensitivity analysis was statistically different and favoured the HemeSelect test (OR 

2.19; 95% CI: 1.45, 3.31). The PPV RD was also statistically significant in favour of the 

HemeSelect test in the sensitivity analysis (RD 0.026; 95% CI: 0.012, 0.042). The PPVs 

for all of the other immunochemical to guaiac test comparisons did not differ 

significantly. In all of the main meta-analyses the level of heterogeneity between studies 

was low. In the sensitivity meta-analyses the level of heterogeneity between studies 

increases, reflecting the differences in study participants. 


Table 43 presents the results of the meta-analyses for carcinoma or adenoma 

(neoplasms). The table is split into two sections, one reporting the results of the main 

meta-analyses and the other reporting the results of a series of sensitivity meta-analyses. 

The main meta-analyses are strictly limited to the assessment of only those studies in 

which the participants came entirely from a screening population at average risk. The 

sensitivity meta-analyses include four additional studies in which some of the participants 

were symptomatic or at increased risk (Rozen et al 1995; Rozen et al 1997; Rozen et al 

2000; St John et al 1993). 

The PPV for the detection of neoplasms (adenoma or carcinoma) for the reverse-passive 

haemagglutination (RPHA) tests (HemeSelect and Immudia-HemSp) was greater than 

that for Hemoccult (15.5% vs 11.8%, respectively). The PPV OR for neoplasms 

(adenoma or carcinoma) for RPHA versus Hemoccult was statistically significant and 

favoured RPHA (OR 1.38; 95% CI: 1.09, 1.75). Similarly, the PPV RD for neoplasms for 

RPHA versus Hemoccult was also statistically significant and favoured the Immudia- 

HemSp test (RD 0.038; 95% CI: 0.01, 0.065). However, the data showed a significant 

degree of heterogeneity. 

In contrast, the PPV for Fecatwin Sensitive/Feca EIA was lower than that for 

Hemoccult (25.5% vs 70.0%, respectively). The OR for neoplasm PPV for Hemoccult 

was statistically significant and favoured Hemoccult (OR 0.15; 95% CI: 0.07, 0.328). 

Similarly, the RD for neoplasm PPV for Hemoccult versus Fecatwin Sensitive/Feca EIA 

was different and favoured Hemoccult (RD –0.445; 95% CI: –0.610, –0.281). 

The PPV for neoplasms was greater for HemeSelect than for Hemoccult Sensa (17.7% 

vs 10.5%, respectively). The PPV OR for HemeSelect versus Hemoccult Sensa was 

statistically significant and favoured HemeSelect (OR 1.83; 95% CI: 1.45, 2.28). The PPV 

RD for HemeSelect versus Hemoccult Sensa was statistically significant and also 

favoured HemeSelect (RD 0.071; 95% CI: 0.037, 0.103). 

In the main meta-analyses the level of heterogeneity between the Hemoccult and 

HemeSelect studies was higher than seen in the assessment of PPV for carcinoma. This 

is likely to be a reflection of the variation in definitions used to classify neoplasms in each 

of the included studies. The relatively high levels of heterogeneity between studies were 

also observed in the sensitivity meta-analyses. 


Table 42 Meta-analyses of PPV for carcinoma from FOBT head-to-head studies 

Heterogeneity 

(95% CI) 

Pooled results (95% CI) 

Pooled PPV % 

RD 

OR 


Guaiac 

n/N 

(True +ve/ 

Total +ve) 

FOBT 

Studies 

FOBT 

comparison 

0.011 

(0.0001, 0.51) 

0.012 

(–0.005, 0.028) 

1.35 

(0.89; 2.04) 

RPHA 

5.4 

HO 

3.6 

– 

–0.028 

(–0.119, 0.063) 

0.61 

(0.14; 2.68) 

Fecatwin 

4.7 

HO 

7.5 

0.004 

(0.00009, 1.682) 

0.025 

(0.009, 0.048) 

2.10 

(1.37; 3.26) 

HemeSelect 

4.8 

HO Sensa 

2.4 

13/198 

22/440 

16/456 

21/438 

1/17 

9/145 

8/410 

16/391 

3/40 

5/106 

27/1073 

22/440 

19/849 

21/438 

HO 

HemeSelect 

HO 

HemeSelect 

Allison 1996 

Petrelli 1994c Main guaiac to immunochemical comparisons 

HO vs RPHA 

(pooled 

HemeSelect and 

Immudia- 

HemSp) 

HO 

HemeSelect 

Robinson 

1995a HO 

Immudia-HemSpb Iwase 1992 

HO 

Fecatwin 

Armitage 

1985 


HO Sensa 

HemeSelect 

Allison 1996 

HO Sensa vs 

HemeSelect 

HO Sensa 

HemeSelect 

13/198 

22/440 

HO 

HemeSelect 

16/456 

21/438 

HO 

HemeSelect 

0.204 

(0.0003, 3.91) 

0.013 

(–0.005, 0.036) 

1.34 

(0.90; 2.02) 

RPHA 

5.4 

HO 

4.1 

1/17 

9/145 

8/410 

16/391 

HO 

HemeSelect 

HO 

Immudia-HemSpb 3/24 

4/12 

HO 

HemeSelect 


Petrelli 1994 f 

Allison 1996 

Petrelli 1994 c 


HO vs RPHA 

(pooled 


Immudia- 

HemSp) 

Robinson 

1995a Iwase 1992 

Rozen 1997

Heterogeneity 

(95% CI) 


Pooled PPV % 

RD 

OR 


Guaiac 

n/N 

(True +ve / 

Total +ve) 

FOBT 

Studies 

FOBT 

comparison 

27/1073 

22/440 

19/849 

21/438 

4.70 

(0.052, 2302) 

0.026 

(0.012, 0.042) 

2.19 

(1.45, 3.31) 

HemeSelect 

4.9 

HO Sensa 

2.3 

3/35 

4/12 

1/68 

1/41 

– 

0.110 

(–0.230, 0.352) 

2.15 

(0.41, 11.2) 

Flexsure OBT 

23.5 

HO 

12.5 

3/24 

4/17 

HO Sensa 

HemeSelect 

HO Sensa 

HemeSelect 

HO Sensa 

HemeSelect 

HO Sensa 

HemeSelect 

HO 

Flexsure OBT 

HO Sensa 

Flexsure OBT 

HO Sensa 

BM-Test Colon 

Sensitivity analyses (continued) 

HO Sensa vs Allison 1996 

HemeSelect 

Petrelli 1994 c 

Rozen 1997 

St John 1993 

Rozen 1997 

HO vs Flexsure 

OBT 

HO Sensa vs Rozen 2000 

3/74 

HO Sensa 

Flexsure OBT 

3.38 

0.08 

Flexsure OBT 

– 

3/24 

4.1 

12.5 

(0.63, 18.0) (–0.055, 0.224) 


3/88 

BM-Test Colon 

HO Sensa BM-Test Colon Albumin 

2.06 

0.034 

4/59 

– 

Albumin 

3.4 

6.8 

(0.44, 9.56) (–0.041, 0.108) 

Albumin 

Abbreviations: CI, confidence interval; Fecatwin, Fecatwin Sensitive/Feca EIA; FOBT, faecal occult blood test; HO, Hemoccult; HO Sensa, Hemoccult Sensa; OR, odds ratio; PPV, positive predictive value; RD, risk difference; 

RPHA, reverse-passive haemagglutination. 

aData from Robinson et al (1996) are not used due to slight discrepancies between the publications and a degree of uncertainty surrounding the data. bOver 3 days. cTotal positives calculated from number of patients screened 

and percentage positivity rate as reported, authors were contacted for data confirmation but no response was received. 


Table 43 Meta-analyses of PPV for neoplasms (carcinoma or adenoma) from FOBT head-to-head 

studies 

Heterogeneity 

(95% CI) 


Pooled PPV % 

RD 

OR 


Guaiac 

n/N 

(True +ve/ 

Total +ve) 

FOBT 

Studies 

FOBT 

comparison 

46/198 

90/440 

HO 

HemeSelect 

60/456 

66/438 

HO 

HemeSelect 

Allison 1996a Petrelli 1994b Main guaiac to immunochemical comparisons 

HO vs RPHA 

(pooled 


Immudia- 

HemSp) 

3.86 

(0.32, 2247) 

0.038 

(0.01, 0.065) 

1.38 

(1.09, 1.75) 

RPHA 

15.5 

HO 

11.8 

9/17 

57/145 

HO 

HemeSelect 

Robinson 

1995c 16/410 

44/391 

HO 

Immudia-HemSpe Iwase 1992 d 

– 

–0.445 

(–0.610, –0.281) 

0.15 

(0.07, 0.328) 

Fecatwin 

25.5 

HO 

70.0 

28/40 

27/106 

HO 

Fecatwin 

Armitage 

1985 


99/1073 

90/440 

HO Sensa 

HemeSelect 


HO Sensa vs 

HemeSelect 

0.002 

(0.00007, 1.113) 

0.071 

(0.037, 0.103) 

1.83 

(1.45, 2.28) 

HemeSelect 

17.7 

HO Sensa 

10.5 

104/849 

66/438 

HO Sensa 

HemeSelect 

46/198 

90/440 

HO 

HemeSelect 

60/456 

66/438 

HO 

HemeSelect 

2.53 

(0.20, 1205) 

0.061 

(0.026, 0.095) 

1.45 

(1.18, 1.88) 

RPHA 

22.2 

HO 

16.1 

9/17 

57/145 

HO 

HemeSelect 

16/410 

44/391 

HO 

Immudia-HemSpe 7/24 

8/12 

HO 

HemeSelect 






HO vs RPHA 

(pooled 


Immudia- 

HemSp) 

Robinson 

1995c Iwase 1992 d 

Rozen 1997

Heterogeneity 

(95% CI) 


Pooled PPV % 

RD 

OR 


Guaiac 

n/N 

(True +ve/ 

Total +ve) 

FOBT 

Studies 

FOBT 

comparison 

99/1073 

90/440 

104/849 

66/438 

1.72 

(0.12, 849) 

0.121 

(0.075, 0.170) 

1.83 

(1.48, 2.26) 

HemeSelect 

34.8 

HO Sensa 

22.6 

8/35 

8/12 

16/68 

11/41 

– 

0.061 

(0.230, 0.352) 

1.32 

(0.35, 5.00) 

Flexsure OBT 

35.3 

HO 

29.2 

7/24 

6/17 

HO Sensa 

HemeSelect 

HO Sensa 

HemeSelect 

HO Sensa 

HemeSelect 

HO Sensa 

HemeSelect 

HO 

Flexsure OBT 

HO Sensa 

Flexsure OBT 

HO Sensa 

BM-Test Colon 

Allison 1996a Sensitivity analyses (continued) 

HO Sensa vs 

HemeSelect 


Rozen 1997 

St John 1993 

Rozen 1997 

HO vs Flexsure 

OBT 


19/74 

HO Sensa 

Flexsure OBT 

2.07 

0.160 

Flexsure OBT 

– 

10/24 

25.7 

41.7 

(0.79, 5.43) (0.061, 0.381) 


21/88 

BM-Test Colon 

HO Sensa BM-Test Colon Albumin 

1.29 

0.049 

17/59 

– 

Albumin 

23.9 

28.8 

(0.61, 2.73) (–0.096, 0.195) 

Albumin 

Abbreviations: CI, confidence interval; Fecatwin, Fecatwin Sensitive/Feca EIA; FOBT, faecal occult blood test; HO, Hemoccult; HO Sensa, Hemoccult Sensa; OR, odds ratio; PPV, positive predictive value; RD, risk difference; 

RPHA, reverse-passive haemagglutination. 

aAdenoma data are only for adenomas > 1cm. bTotal positives calculated from number of patients screened and percentage positivity rate as reported, authors were contacted for data confirmation however no response was 

received. cData from Robinson et al (1996) are not used due to slight discrepancies between the publications and a degree of uncertainty surrounding the data. dOver 3 days. 


Appendix G Diagnostic odds ratios 

Accuracy 

The diagnostic odds ratios (DORs) were determined for those tests for which the 

sensitivity and specificity were available, by utilising the interval cancer rate (Table 44). 

In addition, studies estimating the sensitivity and specificity in screening populations with 

a high proportion of participants who were at higher risk of disease, by subjecting all 

participants to the reference standard, were included in a sensitivity analysis (Rozen et al 

1995; Rozen et al 1997; Rozen et al 2000; St John et al 1993). However, in these studies 

the endoscopic examination had been performed up to several years previously in a 

proportion of the patients testing negative with FOBT. Therefore, these studies were still 

subject to verification bias. These studies have been included in a sensitivity analyses. In 

the sensitivity analyses the use of different reference standards (ie, colonoscopy plus 

interval cancer rates, versus colonoscopy in all subjects) is likely to lead to a threshold 

effect across studies. 

The heterogeneity in the DORs indicated that the pooled DOR estimate is likely to be 

imprecise. Nevertheless, the DOR was significantly higher for HemeSelect than 

Hemoccult (DOR 0.384; 95% confidence interval (CI): 0.140, 0.993) and this difference 

was maintained in the sensitivity analysis. 

The DORs were also higher for the immunochemical tests in single head-to-head studies 

in the main analyses when Hemoccult was compared with Fecatwin Sensitive/Feca EIA 

and when Hemoccult Sensa was compared with HemeSelect. The difference in the 

DORs between Hemoccult Sensa and HemeSelect was not significantly different in the 

sensitivity analysis. 

The practical impact of the relative DORs is not apparent from these data in isolation. 

The clinical significance of these trade-offs between sensitivity and specificity has been 

investigated via the use of an economic model in the cost-effectiveness section of this 

assessment report. 

A summary receiver-operating characteristic curve (SROC) was obtained for the 

Hemoccult test from the Hemoccult to HemeSelect sensitivity analyses by back 

transformation of a linear regression of the difference between logit (true positive rate, 

TPR) and logit (false negative rate, FNR) on the sum of the two logits (Figure 10). The 

equation for the curve was: 

Sensitivity = 

1+ 

e 

1 

a 

1+ 

b 

FPR 

1 −b 

1−b 

× ( ) 

1− 

FPR 

where, FPR = 1 – specificity, a = 4.087515, and b = 0.262321. 

This SROC curve was used to determine alternative hypothetical pairs of sensitivity and 

specificity data for use in a sensitivity analyses in the economic model (Appendix K). 


Table 44 Meta-analyses of diagnostic odds ratios for carcinoma from FOBT head-to-head studies 

Relative DORg (95% CI) 

Pooled DOR 

immunochemicalf Pooled DOR 

guaiacf DOR 

Specificity 

Sensitivity 

FOBT 

Studies 



HO vs HemeSelect Allison 1996 

0.384 

(0.140, 0.993) 

HemeSelect: 

45.7 

HO: 

17.7 

25.1 

37.1 

0.9 

97.7 

94.4 

37.1 

68.8 

HO 

HemeSelect 

– 

Fecatwin: 

59.3 

HO: 

34.1 

– 

HemeSelect: 

37.1 

HO Sensa: 

25.2 

210.6e 34.1 

59.3 

25.2 

37.1 

98.9 

90.9 

9.1a 100 

HO 

HemeSelect 

Robinson 1996 

97.2 

92.2 

50.0 

83.3 

86.7 

94.4 

79.4 

68.8 

HO 

Fecatwin 

HO Sensa 

HemeSelect 

Armitage 1985 b 


Allison 1996 

HO Sensa vs 

HemeSelect 

25.1 

37.1 

0.9 

97.7 

94.4 

0.394 

(0.149, 0.956) 

HemeSelect: 

55.3 

HO: 

21.8 

98.9 

90.9 

37.1 

68.8 

9.1a 100 

HO 

HemeSelect 

Allison 1996 



HO 

HemeSelect 

Robinson 1996 

HemeSelect: 

0.930 

43.55 (0.327, 2.793) 

– 

– 

– 

d 

HO Sensa: 

23.55 

Flexsure OBT: 

118.5 

Flexsure OBT: 

49.4 

BM-Test Colon Alb: 

34.0 

d 

Rozen 1997 HO 

60.0 

94.7 

HemeSelect 

80.0 

98.0 

195 

HO Sensa vs 

Allison 1996 HO Sensa 

79.4 

86.7 

25.2 

HemeSelect 

HemeSelect 

68.8 

94.4 

37.1 

Rozen 1997 HO Sensa 

60.0 

92.0 

17.2 

HemeSelect 

80.0 

98.0 

195 

Rozen 2000 HO 

60.0 

94.7 

26.9 

HO: 

Flexsure OBT 

80.0 

96.7 

118.5 

26.9 


42.9 

94.9 

14.1 

HO Sensa: 

Flexsure OBT 

42.9 

98.5 

49.4 

14.1 


60.0 

83.7 

7.7 

HO Sensa: 

BM-Test Colon Albumin 

80.0 

89.5 

34.0 

7.7 

c 


HO Sensa vs Flexsure 

OBT 

HO Sensa vs BM-Test 

Colon Albumin 

Abbreviations: CI, confidence interval; DOR, diagnostic odds ratio; HO, Hemoccult; HO Sensa, Hemoccult Sensa; Fecatwin, Fecatwin Sensitive/Feca EIA; FOBT, faecal occult blood test. 

aAssumes that the patient developing cancer during follow-up for adenoma initially tested negative with Hemoccult. bData from Hardcastle 86. c Results affected by BUGS convergence problem noted during the analysis. 

dEstimated by inverse-variance pooling method. eEstimate only, as false negative rate was 0. fMedian parameter estimate. gGuaiac test relative to immunochemical test. 

210.6e 26.9 


Figure 10 Summary receiver-operating characteristic curve for Hemoccult versus HemeSelect 

sensitivity analyses 

Abbreviations: H’occult, Hemoccult; H’select, HemeSelect; SROC, summary receiver-operating characteristic. 


Appendix H Quality scoring 

Table 45 Quality scoring scale for FOBT comparative screening studies 

Evaluation criteria 

Quality 

score (/12) 

Criteria for study design quality 

A. Was the study prospectively designed? 

No (unclear) 0 

Yes 1 

B. Was there a within-subjects study design? 

No, different tests done on different individuals, not randomly allocated (case-control) 0 

No, different tests done on randomly allocated individuals (parallel randomised or 

quasi-randomised) 

1 

Yes, tests performed on each individual (single group with sequential tests) 2 

C. Was the test being evaluated compared with a valid reference standard? 

No (not reported) 0 

Yes 1 

D. What was the industry’s relationship to the study? 

Full or partial support 0 

No support 1 

Criteria for minimising verification bias 

E. Was the decision to perform the reference standard independent of the test results? 

No (not reported, positives only or positives and sample of negatives) 0 

Yes (all tests) 1 

Criteria for minimising selection bias 

F. Was the selection of sample of participants: 

Not random (or not reported) 0 

Consecutive 1 

Random 2 

Criteria for blinding 

G. Were the test and the reference standard measured independently (blind) of each other? 

No (or not reported) 0 

Yes, the test was measured independently of the reference standard and the reference 

standard independently of the test (or methodology not subject to observer bias) 

H. Were the test and the comparator measured independently (blind) of each other? 

No (or not reported) 0 

Yes, the test was measured independently of the reference standard and the reference 

1 

standard independently of the test (or methodology not subject to observer bias) 

Criteria relevant to the external validity of the results 

I. Was the participant population consistent with proposed Australian screening setting (ie, 

population-based, average-risk, older age group)? 

No (not reported) 0 

Partially 1 

Yes 2 

Abbreviation: FOBT, faecal occult blood test. 


1

Appendix I Participation in FOBT 

screening rates 

The participation rates used in the economic model differentiate between screening 

rounds and between type of faecal occult blood test (FOBT) used. This is necessary in 

order to capture the negative effect of non-participation on the cost-effectiveness of the 

FOBTs investigated. The calculations behind the rates used in the economic model 

appear below. The values used in the economic model appear in italics. 

As shown in Table 46, the participation rate for guaiac FOBTs is calculated by 

multiplying the ratio of guaiac-to-immunochemical participation rates taken from Cole et 

al (2003) by the immunochemical participation rate in the Australian Bowel Cancer 

Screening Pilot Program (the pilot). 

Table 46 Round 1 participation with FOBT screening 

Row Parameter Guaiac FOBT Immunochemical 

FOBT 

A Participation rates from 

the literature 

B Participation rates used 

in the economic model 

C Non-participation rates 

implicit in the economic 

model 


0.2340 0.3050 Cole et al (2003) 

Reference 

0.3483 0.4540 Immunochemical = data from the pilot 

Guaiac = (Row A guaiac rate/Row A 

immunochemical rate) × Row B 

immunochemical rate 

0.6517 0.5460 C = 1 – Row B 

An individual’s participation after the first invitation to screening is assumed to be a 

function of the individual’s previous decision regarding participation. The calculations 

supporting the values used in the economic model are presented below. Table 47 gives 

details of the calculation of proportional round 2 losses from screening from the Danish 

trial (Jorgensen et al 2002). Table 48 provides details of the calculation of estimated 

losses from screening in the economic model. 

Table 47 Participation data from Jorgensen et al (2002) 

Row Parameter Value Reference 

A Round 1 participation 0.6700 Jorgensen et al (2002) 

B Round 1 non-participation 0.3300 B = 1 – Row A 

C Participation in round 2 for those individuals who participated in 

round 1 

0.9300 Jorgensen et al (2002) 

D Proportion of individuals not participating in round 2 0.0700 D = 1 – Row C 

E Proportion of invitees previously participating but lost in round 2 0.0469 E = Row A × Row D 


Table 48 Later-round participation with FOBT screening for those who participated in round 1 

Row Parameter Guaiac 

FOBT 

A Ratio of estimated round 1 

loss to round 1 loss in 

Jorgensen et al (2002) 

B Estimated proportion of 

invitees lost from screening 

in round 2 

C Proportion of individuals 

participating in round 2. 


Note that figures may not multiply exactly due to rounding. 


FOBT 

Reference 

1.97 1.65 A = (Table 46 Row C / Table 47 Row B) × 100 

0.1382 0.1155 B = Row A × Table 47 Row D 

0.862 0.884 C = 1 – Row B 

In addition to these figures, the economic model also allows for a proportion of first 

round non-participants to participate in later screening rounds. 

Expert opinion indicates that the number of new participants in the second round of 

screening is roughly equivalent to the number of individuals lost from screening after 

participating in round 1. The calculations used to estimate the proportion of new 

participants used in the economic model are presented in Table 49. 

Table 49 Proportion of new participants after the first screening round 

Row Parameter Guaiac 

FOBT 

A Proportion of invitees 

previously participating but 

lost in round 2 

B Proportion of new 

participants after the first 

screening round 



FOBT 

Reference 

0.0481 0.0526 D = Table 46 Row B × Table 48 Row B 

0.0739 0.0963 B = A/Table 46 Row C 

Rates of participation calculated for round 2 are used for all further rounds of screening. 


Appendix J Relative cost-effectiveness 

of Hemoccult versus 

Fecatwin Sensitive/ 

Feca EIA 

The variables used in this analysis of the economic model were outlined previously in the 

main document. The reason for not including the results in that section is that the data 

are of a lower quality, particularly due to the absence of reliable estimates on the 

sensitivity of the tests in detection of adenomas. This is an important feature, as the 

ability to detect precancerous adenomas prior to malignant transformation is an integral 

feature of faecal occult blood test (FOBT) screening for colorectal cancer (CRC). As 

previously discussed, early detection of adenomas may lead to increased life-expectancy 

and reduced lifetime treatment costs by avoiding the incidence of CRC. In addition, it 

should be noted that the subjects in this study were not required to adhere to the dietary 

restrictions generally recommended with the use of a guaiac FOBT. Consequently, it 

would be inappropriate to place the results of this head-to-head comparison alongside 

those with better quality data. 

The results of the analysis are discussed below. 

Costs 

Fecatwin Sensitive/Feca EIA is associated with higher costs overall. The expected cost 

of the test itself is more than the alternatives. Participation is also higher, leading to a 

marginally higher average cost per individual invited to screening. Furthermore, 

diagnostic-follow up costs are substantially more in the Fecatwin Sensitive/Feca EIA 

arm of the economic model, a result of higher sensitivity and a lower specificity for 

detection of CRC. This is the key driver of the incremental price difference between the 

two tests, with diagnostic follow-up costs accounting for 14% of all costs in the Fecatwin 

Sensitive/Feca EIA arm of the model, compared with 5% in the Hemoccult arm. 

Costs are broken down into their components in Figure 11. 


Cost 

$1,800.00 

$1,600.00 

$1,400.00 

$1,200.00 

$1,000.00 

$800.00 

$600.00 

$400.00 

$200.00 

$0.00 

Hemoccult Fecatwin 

Type of FOBT 

Figure 11 Component costs in the Hemoccult versus Fecatwin Sensitive/Feca EIA analysis 

Outcomes 

As a result of the higher participation rates, Fecatwin Sensitive/Feca EIA is associated 

with only a marginally higher average number of completed FOBTs (6.0 compared with 

5.8). It is unlikely, therefore, that this will be a key driver of the relative costeffectiveness. 

Alongside higher overall costs, Fecatwin Sensitive/Feca EIA is also associated with a 

numerically greater life-expectancy from the outset of the model. As with the analyses 

presented in the main document, however, the difference is small and statistically 

insignificant. This is illustrated in Table 50. 

Table 50 Life-expectancy from the beginning of the economic model in the Hemoccult versus Fecatwin 

Sensitive/Feca EIA analysis 

Patient group Life-years gained 

(per patient) 

Patients screened with Hemoccult 14.399 

Incremental life-years 

gained 

Patients screened with Fecatwin 14.442 –0.043 


Colonoscopy 

FOBT 

The positive difference in life-expectancy between screening and no screening is driven 

by the better detection of early-stage CRC. This difference is most pronounced in terms 

of Dukes’ A CRC, though it remains in the case of Dukes’ B. 

Figure 12 illustrates the difference in detection between the two tests, based on this 

analysis. 


Number detected by screening or symptoms 

350 

300 

250 

200 

150 

100 

50 

0 

Note that despite the assumed inability to detect adenomas, there is still a greater 

number of abnormalities detected overall when compared with the no screening option. 

Figure 13 illustrates the method of detection of all neoplasms. 

Total cancers detected by 


Figure 12 The pattern of detection in the Hemoccult versus Fecatwin Sensitive/Feca EIA 

2500 

2000 

1500 

1000 

500 

0 

Total neoplasms detected by 


Dukes' A Dukes' B Dukes' C Dukes' D 

Total cancers detected by 


Total cancers presenting 


Total cancers undetected at 

death 

Figure 13 Method of CRC/cancerous adenoma detection in the Hemoccult versus Fecatwin 

Sensitive/Feca EIA analysis 


Fecatwin 


Fecatwin 




While Fecatwin Sensitive/Feca EIA offers a numerically superior benefit in terms of lifeexpectancy 

at a reasonable cost, the difference is marginal (Table 51). 

Table 51 Incremental cost-effectiveness of Hemoccult versus Fecatwin Sensitive/Feca EIA 

Hemoccult Fecatwin Incremental 


Life-years gained 14.399 14.442 –0.043 



Appendix K Sensitivity analysis of 

Hemoccult versus 

HemeSelect 

The following analysis is based on variations to the sensitivity and specificity of the 

Hemoccult faecal occult blood test (FOBT) in detection of colorectal cancer (CRC). It is 

motivated by a desire to explore the possible inaccuracies of the estimates used in the 

main analysis. 

The values used in this analysis have been calculated from the summary receiveroperating 

characteristic (SROC) curve appearing in Appendix G, using the following 

formulas: 

False positive rate (FPR) = 1 – specificity (Equation 1) 

Sensitivity = 

1+ 

e 

where a = 4.087515 and b = 0.262321. 

1 

a 

1+ 

b 

FPR 

1 −b 

1−b 

× ( ) 

1− 

FPR 

(Equation 2) 

Using Equations 1 and 2 and selecting a Hemoccult specificity of 0.9550, a sensitivity of 

0.5778 is calculated. These values are then used in the economic model comparing 

Hemoccult with HemeSelect. All other values used in the main analysis remain the same. 

The results of this analysis appear alongside the base-case analysis in Table 52. 

Table 52 The effect of selecting alternative sensitivity and specificity values for Hemoccult: Hemoccult 



Base-case analysis – Hemoccult sensitivity 30.0%, specificity 97.8% 

HemeSelect Incremental 




Different accuracy estimate – Hemoccult sensitivity 57.8%, specificity 95.5% 




With regards to outcomes, the variation means that Hemoccult detects slightly more 

CRC in the screening population. The pattern of detection, however, remains similar to 

that of the main analysis. 


Overall, altering the sensitivity and specificity has little effect on the relative costeffectiveness 

result. Individuals subject to Hemoccult have a slightly higher lifeexpectancy 

due to better accuracy in detecting the presence of CRC, although this is 

achieved at a marginally higher cost. Nonetheless, HemeSelect remains cost-effective 

compared with Hemoccult and, importantly, the incremental cost-effectiveness ratio 

improves due to faster growth in costs than outcomes in the Hemoccult arm of the 

model. 


Abbreviations 

AACR Australasian Association of Cancer Registries 

AHMAC Australian Health Ministers’ Advisory Council 

AIHW Australian Institute of Health and Welfare 

CCOHTA Canadian Coordinating Office for Health Technology Assessment 

CI Confidence interval 

CRC Colorectal cancer 

DACEHTA Danish Centre for Evaluation and Health Technology Assessment 

DARE Database of Abstracts of Reviews and Effects 

DCBE Double contrast barium enema 

DOR Diagnostic odds ratio 

FNR False negative rate 

FOBT Faecal occult blood test 

FPR False positive rate 

GI Gastrointestinal 

HIRU Health Information Research Unit 

HSTAT Health Services Technology Assessment Texts 

HTA Health Technology Assessment 

ISRTCN International Standard Randomised Controlled Trial Number 

MBS Medicare Benefits Scheme 

MCMC Markov chain Monte Carlo 

MSAC Medical Services Advisory Committee 

NCCI National Cancer Control Initiative 

NHMRC National Health and Medical Research Council 

NHS CRD National Health Service Centre for Reviews and Dissemination 

NHSEED National Health Service Economic Evaluation Database 


NSAID Non-steroidal anti-inflammatory drug 

NZHTA New Zealand Health Technology Assessment 

OR Odds ratio 

Pilot The Australian Government Bowel Cancer Screening Pilot Program 

PPV Positive predictive value 

RCT Randomised controlled trial 

RD Risk difference 

RPHA Reverse-passive haemagglutination 

SBU Swedish Council on Technology Assessment in Health Care 

SROC Summary receiver-operating characteristic 

TGA Therapeutic Goods Administration 

TPR True positive rate 

USPSTF United States Preventative Services Task Force 


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