A systematic literature review of methods of incorporating mortality in cost-effectiveness analyses of lipid-lowering therapies

Aims: Cost effectiveness analysis (CEA) is a useful tool for estimating the value of an intervention in relation to alternatives. In cardiovascular disease (CVD), CEA is especially important, given the high economic and clinical burden. One key driver of value is CVD mortality prevention. However, data used to inform CEA parameters can be limited, given the difficulty in demonstrating statistically significant mortality benefit in randomized clinical trials (RCTs), due in part to the frequency of fatal events and limited trial durations. This systematic review identifies and summarizes whether published CVD-related CEAs have incorporated mortality benefits, and the methodology among those that did. Materials and methods: A systematic literature review was conducted of CEAs of lipid-lowering therapies published between 2000-2017. Health technology assessments (HTA) and full-length manuscripts were included, and sources of mortality data and methods of applying mortality benefits were extracted. Results were summarized as proportions of articles to articulate common practices in CEAs of CVD. Results: This review identified 100 studies for inclusion, comprising 93 full-length manuscripts and seven HTA reviews. Among these, 99% assumed a mortality benefit in the model. However, 87 of these studies that incorporated mortality differences did so despite the trials used to inform model parameters not demonstrating statistically significant differences in mortality. None of the 12 studies that used statistically significant findings from an individual RCT were based on active control studies. In a sub-group analysis considering the 60 CEAs that incorporated a direct mortality benefit, 48 (80%) did not have RCT evidence for statistically significant benefit in CVD mortality. Limitations and conclusions: The finding that few CEA models included mortality inputs from individual RCTs of lipid-lowering therapy may be surprising, as one might expect that treatment efficacy should be based on robust clinical evidence. However, regulatory requirements in CVD-related RCTs often lead to insufficient sample sizes and observation periods for detecting a difference in CVD mortality, which results in the use of intermediate outcomes, composite end-points, or meta-analysis to extrapolate long-term mortality benefit in a lifetime CEA.