Predicting EQ-5D responses from SF-12: should we take into account dependence and ordering?

Generic health status measures such as the SF-12 provide important in- formations about health-related quality-of-life (HRQL), but they do not incorpo- rate preferences for health states and cannot be used for the calculation of quality- adjusted life-years (QALYs). It follows that in order to conduct a cost-effectiveness analysis it is common to use mapping algorithms to estimate preference-based HRQL intruments scores from SF-12 scores. Here we consider the problem of di- rectly predicting EQ-5D responses rather than utility values, and in recognising that there might be dependence between the five dimensions of EQ-5D responses, and that the possible levels of each dimension are ordered, we explore the behaviour of a multivariate ordered probit regression model.