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82 Multislice CT in Coronary Heart Disease KCE Reports 82 Outcomes Diabetic Non-diabetic patients patients BMS 21,7% 88,2% DES 78,3% 11,8% From these data, combined with data on the proportion of diabetic patients in the RCT of Goldstein et al. 67 , we could estimate the mean cost of PCI. In the RCT, 8.2% of the patients had diabetes mellitus in the MSCT arm and 12.2% in the „standard of care“arm. In order not to bias the results against the diagnostic arm with the most diabetic patients (PCI and CABG in diabetic patients entails higher costs than in non-diabetic patients), we assumed an equal proportion of 10% diabetic patients in both arms. The outcomes are valued based on data from literature about the quality of life impairment associated with PCI, CABG and CCA. SPECT and MSCT are assumed to have no impact on health-related quality of life. Serruys et al. (2001) 162 studied health-related quality of life in 600 patients who had undergone PCI with stenting and 605 patients having undergone CABG. The instrument used the EuroQol EQ-5D. EQ-5D health states were translated into an index value on a scale from 0 (dead) to 1 (perfect health) based on the UK off-the shelf utility values for EQ-5D health states. 163 This study found that healthy, on average 60-year old, patients have a quality of life index of 0.86 (s.d. 0.16). At the time of intervention, patients had an index of 0.69 (s.d. 0.20) in case of PCI and 0.68 (s.d. 0.20) in case of CABG. One month after the intervention, quality of life values were 0.84 (s.d. 0.16) and 0.78 (s.d. 0.17) for PCI and CABG respectively. At six months after the intervention, there was no longer a significant difference between the quality of life of patients who had undergone PCI and patients who had undergone CABG and both patient groups had already reached the quality of life index of 0.86, which is equivalent to baseline values in healthy patients of the same age. Scuffham and Chaplin (2004 and 2005) 164, 165 used these values to calculate the quality of life loss due to PCI and CABG in an economic model. They assumed a quality of life loss due to PCI of 0.17 for 1 month, which boils down to 5 quality adjusted life days lost. For CABG, they assumed a quality of life loss of 0.18 for one month and 0.08 for the subsequent 2.5 months. This is equivalent to 11.4 quality adjusted life days lost due to CABG. Other authors have used similar QALY decrements. Kuntz et al. (1996) 166 , for instance, estimated the number of quality-adjusted life days lost due to PCI and CABG at 2 and 10 days respectively. We used the quality of life values and their observed distribution as reported by Serruys et al. 162 to define the number of quality adjusted life days lost. Assumptions had to be made about the duration of quality of life impairment due to these procedures as for obvious reasons no continuous data are available for quality of life. Similarly to Scuffham and Chaplin (2004 and 2005) 164, 165 we assume that the baseline values at time of intervention as reported by Serruys et al. hold for one month in case of PCI and CABG and that in addition CABG patients suffer from a quality of life reduction of 0.08 compared to healthy individuals at that age during 2.5 months following the intervention. Unlike Scuffham et al. 164, 165 , however, we take the distributions in observed quality of life values into account in our estimates of the variability in quality of life impairment. For angiography without PCI we did not find specific utility values. We therefore assumed the same quality of life impairment as for PCI, albeit for a shorter period of time, i.e. 0.5 months instead of 1 month.
KCE Reports 82 Multislice CT in Coronary Heart Disease 83 Health state The quality of life values and their distributions for each of the states, on the basis of which the QALY decrements are calculated are presented in Table 24. Table 24: Distributions of quality of life index values used to calculate the number of quality adjusted life days lost Duration of state Quality of life index values, mean Standard deviation Distribution Lower bound Baseline 0,86 0,16 Normal 0.2 1 PCI procedure 1 month 0,69 0,2 Normal 0.25 1 CABG procedure 1 month 0,68 0,2 Normal 0.25 1 CABG 2.5 0,78 0,17 Normal 0.5 1 follow-up months Time horizon Sensitivity analysis Upper bound The impact of symptom relief from revascularisation on health-related quality of life was not taken into account in our economic evaluation because it is questionable whether the revascularisations performed in the study by Goldstein et al. actually induced pain relief. They presumably were rather meant for diagnostic reasons, i.e. the prevention of major cardiac events or death. While more revascularisations were performed during the index hospitalisation in the MSCT-arm compared to the ”standard of care”-arm (5% versus 1%), an equal number of patients were re-admitted for recurrent chest pain during the 6 months follow-up period in both arms. 4 Hence, we can reasonable conclude that the higher number of revascularisations did not reduce the risk of recurrent chest pain. The time horizon used in the economic model is the time horizon for which data are available from the RCT, i.e. from admission to the emergency department up to 6 months follow-up. We assume that longer time horizons would not change the results of the economic analysis, because it is uncertain whether the immediate CCAs and consequent revascularisations performed in the 8 patients showing severe stenosis on MSCT (over 70%) were clinically meaningful. As no MPS has been performed in these patients it is impossible to draw conclusions about the clinical relevance of these CCAs and revascularisations. As for the outcomes, we assume that only invasive coronary procedures (CCA, PCI and CABG) have an impact on the number QALYs. The absolute difference between the number of QALYs in both procedures remains therefore de facto the same in extended time periods if the difference in the number of invasive procedures remains the same. Obviously, the relative impact of the quality of life loss due to the procedures decreases if the time horizon increases. Bootstrapping was performed to obtain confidence intervals around the cost and outcome estimates in the economic evaluation. 1000 bootstrap samples were drawn from the defined distributions. The distributions used in the bootstrapping for cost and outcome variables are presented in the paragraphs where the sources and assumptions with respect to the cost and outcome variables are discussed. We verified the conclusions of Goldstein et al. by calculating the costs of both diagnostic strategies up to the point where the decision to perform CCA is taken. Costs of CCA or revascularisation were not included. 67 On the basis of this analysis, Goldstein et al. concluded that the MSCT procedure is less costly than the standard of care procedure. Outcomes, however, were not measured in terms of QALYs but in terms of ”time to diagnosis”, which is, as explained earlier, not relevant for resource
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