PCN46 - Retrospective Validation of Predicted Long-Term Survival Estimates from an Early Data Cut of the Phase III Checkmate 025 Study in Advanced Renal Cell Carcinoma

Abstract

Manufacturers often seek reimbursement of new treatments based on early clinical trial results. Extrapolation of overall survival (OS) trial data to a lifetime is often required to estimate cost-effectiveness. In oncology, this involves fitting parametric models to trial Kaplan-Meier data, however, different models will lead to different long-term survival estimates. For renal cell carcinoma, previous reimbursement submissions for nivolumab used OS data from a 1-year data cut of the CheckMate 025 (CM-025) trial. We assessed predicted survival from parametric models fitted to these data against a 3-year survival update from CM-025. We used a previous reimbursement dossier to fit a spline-based survival model to 1-year OS data for nivolumab and everolimus from CM-025. Function selection was based on criteria including visual inspection, statistical model fit, and validation versus longer-term data from the phase I CA209-003 study. A number of other parametric survival models were also evaluated. Our base-case spline function fitted to early Kaplan-Meier data from CM-025 predicted 3-year OS rates of 36.1% and 27.3% for nivolumab and everolimus, respectively. Analysis of the updated 3-year data shows observed 3-year OS rates of 39.1% and 29.5%, respectively. A lognormal distribution, which gave closer predictions to the long-term data from CA209-003, estimated 3-year OS rates of 41.6% and 32.0 %, and the best fitting non-spline-model, log-logistic, provided rates of 39.1% and 29.5% for nivolumab and everolimus, respectively. Three-year OS rate predictions using base-case parametric models originally fitted to 1-year survival data from CM-025 were conservative and underestimated the actual, observed 3-year survival rates. The observed incremental difference in 3-year OS between nivolumab and everolimus was also greater than the predicted estimates, with implications for cost-effectiveness analyses. These results show the importance of scenario testing with different OS curves in economic analyses and retrospective validation of the original results.