Abstract
Objectives Extrapolation is often required to inform cost-effectiveness (CE) evaluations of immune-checkpoint inhibitors (ICIs) since survival data from pivotal clinical trials are seldom complete. The objectives of this study were to evaluate the accuracy of estimates of long-term overall survival (OS) predicted in French CE assessment reports of ICIs, and to identify models presenting the best fit to the observed long-term survival data. Methods A systematic review of French assessment reports of ICIs in the metastatic setting since inception until May 2020 was performed. A targeted literature review was conducted to collect associated extended follow-up of randomized controlled trials (RCTs) used in the CE assessment reports. Difference between projected and observed OS was calculated. A range of standard parametric and spline-based models were applied to the extended follow-up data from the RCT to determine the best-fitting survival models. Results Of the 121 CE assessment reports published, 11 reports met the inclusion criteria. OS was underestimated in 73Â percent of the CE assessment reports. The mean relative difference between each source was-13Â percent (median:-15Â percent; IQR:-0.4 to 26Â percent). Models providing the best fit were those that could reflect nonmonotonic hazards. Conclusions Based on the available data at the time of submission, longer-term survival of ICIs was not fully captured by the extrapolation models used in CE assessments. Standard and flexible parametric models which can capture nonmonotonic hazard functions provided the best fit to the extended follow-up data. However, these models may still have performed poorly if fitted to survival data available at the time of submission to the French National Authority for Health.
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Grumberg, V., Roze, S., Chevalier, J., Borrill, J., Gaudin, A. F., & Branchoux, S. (2022). A Review of Overall Survival Extrapolations of Immune-Checkpoint Inhibitors Used in Health Technology Assessments by the French Health Authorities. International Journal of Technology Assessment in Health Care, 38(1). https://doi.org/10.1017/S0266462322000125
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