Predictive model assessment for mapping between measures of health outcomes

Patient-reported outcomes measures (PROMs), which include those evaluating health-related quality of life, are used extensively in health servicesresearch and to inform policy making; in general, PROMs can be distinguished as preference-based and non-preference-based measures, dependingon whether the valuation method that is used to derive their index score is consistent with economic theory. Unfortunately, it is quite common forclinical studies to employ different PROMs, thus limiting the comparability of the evidence base that they contribute to. For this reason, nationalagencies as the National Institute for Health and Care Excellence for England and Wales, while have identified in EuroQoL-5D (EQ-5D) thePROM of choice, are accepting the use of a mapping approach to predict EQ-5D from other PROMs when EQ-5D data have not been collected. Weconsider the problem of directly predicting EQ-5D responses from ‘Short form 12’ by means of multivariate ordered probit models, and carry outthe analysis within a Bayesian framework. In particular, we address the key problem of choosing an appropriate summary measure of agreementbetween predicted and actual results when analysing PROMs, and focus on scoring rules, with particular attention devoted to the case of discreteordered data and to the importance of propriety