Abstract
PurposePreference-based measures are essential for producing quality-adjusted life years (QALYs) that are widely used for economic evaluations. In the absence of such measures, mapping algorithms can be applied to estimate utilities from disease-specific measures. This paper aims to develop mapping algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and the English and the US-based EQ-5D-5L value sets.MethodsIndividuals with heart disease were recruited from six countries: Australia, Canada, Germany, Norway, UK and the US in 2011/12. Both parametric and non-parametric statistical techniques were applied to estimate mapping algorithms that predict utilities for MacNew scores from EQ-5D-5L value sets. The optimal algorithm for each country-specific value set was primarily selected based on root mean square error (RMSE), mean absolute error (MAE), concordance correlation coefficient (CCC), and r-squared. Leave-one-out cross-validation was conducted to test the generalizability of each model.ResultsFor both the English and the US value sets, the one-inflated beta regression model consistently performed best in terms of all criteria. Similar results were observed for the cross-validation results. The preferred model explained 59 and 60% for the English and the US value set, respectively. Linear equating provided predicted values that were equivalent to observed values.ConclusionsThe preferred mapping function enables to predict utilities for MacNew data from the EQ-5D-5L value sets recently developed in England and the US with better accuracy. This allows studies, which have included the MacNew to be used in cost-utility analyses and thus, the comparison of services with interventions across the health system.
Highlights
Coronary heart disease (CHD) is the leading cause of death and disability worldwide, in Western countries
Data were obtained from a large international Multi-Instrument Comparison (MIC) study, which includes both EQ5D-5L, and MacNew in addition to other instruments
The estimated EQ-5D-5L utilities varied in both the mean score and the range between the value sets of the two countries
Summary
Coronary heart disease (CHD) is the leading cause of death and disability worldwide, in Western countries. The rising prevalence of CHD deaths will lead to increased demand for healthcare services. In the cost-effectiveness appraisal of competing healthcare programmes across disease areas, there is a growing interest in estimating health outcomes on a generic metric, such as quality-adjusted life years (QALYs) [3]. To obtain the quality adjustment weight in the QALY, generic preference-based measures are used [4]. Condition- or disease-specific non-preference-based measures commonly applied. This is mainly because these measures tend to identify disease-specific changes in health that might not be picked up by generic preference-based measures, though they may miss side effects and the impact on possible co-morbidities [3, 11]. In the absence of preference-based measures, the second-best alternative is to ‘crosswalk’, or ‘map’, disease-specific scores onto generic
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