Assurance de qualité pour le cancer rectal – phase 2 ...

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18 PROCARE – phase 2 KCE reports 81⎡ ss ⎤distribution ( CI95 %= ⎢a− 2 ⋅ ; a + 2 ⋅ ⎥ with a the unweighted mean,⎣ N N ⎦N∑ 2( x − a)i=1 is = , and N the number of centres). The 95%CI was computed forN −1the weighted mean using a binomial distribution⎡ p ⋅ (1 − p)p ⋅ (1 − p)⎤( CI95 %= ⎢ p − 2 ⋅ ; p + 2 ⋅ ⎥ with p the weighted⎣ NN ⎦mean).3.1.6 Aggregation of the resultsIn order to examine the ability of the set of QI to provide a global impression on thequality of care for rectal cancer patients, the QI results were aggregated for the 2databases separately using two different methods.First, a global mean of the values of all measurable QI was computed per centre. Foreach centre, only the values of the QI with a denominator of 10 or more were takeninto account. A complementary analysis was performed with the values of those QI witha denominator of 20 or more. For the presentation of the results, centres with less than15 measurable QI for the prospective database or less than 6 measurable QI for theadministrative database were not selected. These cut-off values relate to the overallnumber of measurable QI for each database (30 QI for the prospective database, 10 QIfor the administrative database; see below).To allow a calculation of the global mean, all QI needed to be reported in the same way(i.e. a proportion) and needed to point in the same direction. For most QI a highproportion reflects good quality of care. However, for some QI a low proportion isdesired. These QI were ‘redirected’ by calculating the complement, i.e. 1 – the QI value.One QI (time between first histopathologic diagnosis and first treatment) is reported indays, and was transformed in the proportion of patients for whom the first treatmentstarted within 28 days after the first histopathologic diagnosis.A second method consisted of the calculation of a ‘mean corrected rank’ per centre.For this calculation, the same selection criteria were applied as above. Only centreswith at least 15 measurable QI for the prospective database or 6 measurable QI for theadministrative database using a minimum of 10 (20) patients in the denominator weretaken into account. For each QI, a rank was assigned to each centre using the proc rankprocedure in SAS (rank 1 for the best centre). The lowest rank was assigned in case ofties. A corrected rank per centre was obtained by dividing the rank by the number ofcentres for which the QI was measurable. Finally, for each centre the mean of allcorrected ranks was calculated.A correlation analysis was done to verify whether the PROCARE centres were rankedin the same way using the prospective and the administrative database. A Spearman’srank correlation coefficient was calculated on the mean corrected ranks for the centreswith at least 10 patients in the denominator for at least 15 QI in the prospectivedatabase and at least 6 QI in the administrative database. The link between theanonymous codes in the prospective and administrative databases for the centresparticipating at the PROCARE project was provided by the KCE. The null hypothesis ofthe Spearman’s rank correlation test corresponded to no association between the meancorrected ranks. As we were only interested to know whether the correlation betweenthe mean corrected ranks was positive, the test was one-tailed with alpha = 0.05. TheSpearman’s rank correlation coefficient and p-value were calculated using thecorrelation procedure (proc corr) in SAS.
KCE Reports 81 PROCARE – phase 2 193.2 RESULTS3.2.1 Description of study cohorts3.2.1.1 Prospective PROCARE cohortFor the present study, patient inclusion was stopped on December 4 th 2007. At thattime, 1071 patients with rectal cancer were included, involving 56 centres and 98surgeons. More then 60% of these patients are males, and about 75% is 60 years orolder (Table 1). Mean age is 67 years (SD 12).The number of included patients per hospital ranges from 1 to 87, with a mean of 19patients per hospital (SD 16). Twenty-one centres included 20 patients or more.For about one third of patients the clinical stage is unknown (Table 2). The main reasonis insufficient information on the cT and/or cN to calculate the clinical stage. Of thepatients with a known clinical stage, 49% has cStage III.About 64% of all patients received neoadjuvant treatment (Table 3). More specifically,66% of the cStage II patients and 85% of the cStage III patients received neoadjuvanttreatment. Only 1% of the patients was not treated with surgery, while 28% wasexclusively treated with surgery (Table 4). Table 5 clearly shows a shift towards lowerstages from cStage to (y)pStage. Importantly, two different elements are covered by the(y)pStage. First, in patients not treated with neoadjuvant treatment (and morespecifically those patients not treated with a long course of neoadjuvant radiotherapy),the shift from cStage to pStage could represent a wrong clinical staging. On the otherhand, in patients treated with neoadjuvant treatment (mainly those patients treated witha long course of neoadjuvant radiotherapy), a shift from a given cStage to a lowerypStage also represents a downstaging.Table 1. Age and gender distribution according to used databases*.PROCARE databaseAdministrative databaseAge Males Females Total (%) Males Females Total (%)? 1 1 2 (0.2%) 0 0 0 (0.0%)20-24 0 0 0 (0.0%) 2 3 5 (0.1%)25-29 1 1 2 (0.2%) 2 2 4 (0.1%)30-34 1 2 3 (0.3%) 15 14 29 (0.4%)35-39 5 6 11 (1.0%) 29 26 55 (0.8%)40-44 16 11 27 (2.5%) 70 52 122 (1.7%)45-49 26 16 42 (3.9%) 124 105 229 (3.2%)50-54 39 24 63 (5.9%) 279 176 455 (6.4%)55-59 82 46 128 (12.0%) 402 237 639 (9.0%)60-64 99 54 153 (14.3%) 512 297 809 (11.4%)65-69 109 66 175 (16.3%) 711 383 1094 (15.5%)70-74 113 55 168 (15.7%) 765 439 1204 (17.0%)75-79 76 52 128 (12.0%) 643 485 1128 (15.9%)80-84 66 55 121 (11.3%) 363 373 736 (10.4%)85+ 22 26 48 (4.5%) 215 350 565 (8.0%)Total 656 (61.3%) 415 (38.7%) 1071 (100%) 4132 (58.4%) 2942 (41.6%) 7074 (100%)* Chi-Square (for age distribution) 53.3208, p < 0.0001Table 2. Distribution of cStage according to used databases*.PROCARE database Administrative database0 1 (0.1%) 10 (0.4%)I 107 (14.5%) 446 (16.9%)II 160 (21.7%) 801 (30.4%)III 357 (48.5%) 813 (30.8%)IV 111 (15.1%) 567 (21.5%)0-IV 736 (100%) 2637 (100%)X 335 4437Total 1071 7074* Chi-Square 75.9994, p < 0.0001
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