OBJECTIVES:

Parametric survival based cost-effectiveness analyses are preferred for trials with time to event outcomes such as overall survival. The objective of this case study was to assess feasibility of developing parametric survival based CEA using simulated IPD.

METHODS:

A targeted literature review was conducted for vericiguat, sacubitril/valsartan and omecamtiv clinical publications. The Kaplan-Mier (K-M) curves for the three products are extracted and used to create simulated IPD. The data for incremental life years (LYs) and quality adjusted life years (QALYs) gained for vericiguat and sacubitril/valsartan were extracted from published CEAs based on IPD. The simulated IPD was used to create a survival dataset that matched the number of patients at risk and risk times from published K-M curves. Seven parametric distribution models were considered, exponential, Weibull, Gompertz, log-normal, log-logistic, gamma, and generalized gamma. The LYs and QALYs for simulated and IPD based models were compared to assess feasibility and accuracy.

RESULTS: The IPD based models predicted incremental gains of 0.35LYs and 0.28 QALYs for vericiguat versus placebo, and 0.69 LYs and 0.62 QALYs, for sacubitril/valsartan versus placebo. The simulated IPD based model for vericiguat predicted gains of 0.33 LYs and 0.25 QALYs, showing near 95% match to IPD based model. For sacubitril/valsartan simulated IPD based model predicted gains of 0.68LYs and 0.605 QALYs, showing near 99% match to IPD based model. The time effort involved in simulated IPD based model was estimated to be 40-50% lower than that needed for IPD based model. However, simulated IPD does not allow analysis of covariates, for which patient level data are needed. A test model for new emerging HFrEF products was conducted to develop early hypothesis.

CONCLUSIONS: Simulated IPD based simpler CEA showed high match to IPD based models. This simple approach could be useful to develop early CEAs.