Economic evaluation of factorial randomised controlled trials

Factorial randomised controlled trials (RCTs) evaluate two or more interventions simultaneously, enabling assessment of interactions between treatments. This thesis presents literature reviews, methodological reviews, simulation studies and applied case studies that explore methods for assessing cost-effectiveness based on factorial RCTs. My systematic review suggests that factorial RCTs account for around 3% of trial-based economic evaluations, although there is currently no guidance or methodological work indicating the most appropriate methods. Around 40% of published studies assumed no interaction between treatments and many were poorly-reported. Various mechanisms are likely to produce large interactions within economic endpoints such as costs, quality-adjusted life-years (QALYs) and net benefits. Failing to take account of interactions can introduce bias and prevent efficient allocation of healthcare resources. I developed the opportunity cost of ignoring interactions as a measure of the implications of this bias. However, allowing for small, chance interactions is inefficient, potentially leading to over-investment in research if trial-based evaluations are used to inform decisions about subsequent research. Nonetheless, analyses on simulated trial data suggest that the opportunity cost of adopting a treatment that will not maximise health gains from the healthcare budget is minimised by including all interactions regardless of magnitude or statistical significance. Different approaches for conducting economic evaluations of factorial RCTs (including regression techniques, extrapolation using patient-level simulation, and considering different components of net benefit separately) are evaluated within three applied studies, including both full and partial factorials with 2x2 and 2x2x2 designs. I demonstrate that within both trial-based and model-based economic evaluation, efficient allocation of healthcare resources requires consideration of interactions between treatments, and joint decisions about interacting treatments based on incremental cost-effectiveness evaluated “inside-the-table” on a natural scale. I make recommendations for the design, analysis and reporting of factorial trial-based economic evaluations based on the results of this thesis.