Parametric Survival Extrapolation of Early Survival Data in Economic Analyses: A Comparison of Projected Versus Observed Updated Survival.

<bold>Objectives: </bold>To establish the value of cancer drugs by cost-effectiveness analysis, lifetime parametric survival extrapolations are often fitted to early data. Recent literature suggests that the benefit of cancer agents in primary publications is often different compared with updated data. This study aimed to examine the projected survival based on parametric extrapolations compared with observed survival based on updated data.<bold>Methods: </bold>US Food and Drug Administration oncology approvals from January 2006 to December 2015 were reviewed to identify randomized controlled trials, with updated overall survival (OS) or progression-free survival (PFS) data within 5 years. Individual patient data were reconstructed using established methods on initial and updated publications. Projected survival was calculated as the best-fit parametric restricted mean survival time (RMST) based on extrapolated initial Kaplan-Meier curves whereas observed survival was calculated as observed RMST based on updated Kaplan-Meier curves. Mean deviations, mean absolute error (MAE), mean absolute percentage error, and linear regressions were conducted to examine the relationship between projected and observed survival.<bold>Results: </bold>In total, 32 randomized controlled trials were included. The MAE between the projected RMST and observed RMST was 3.18 months (OS) and 2.84 months (PFS) and absolute percentage error of 100% (OS) and 23% (PFS), suggesting substantial imprecision of the projected RMST in predicting the updated RMST. The linear regression indicated MAE increased as time extrapolated and as the percentage of censored patients increased.<bold>Conclusions: </bold>This study demonstrated substantial difference in projected survival between initial and updated publications. Health technology assessment committees need to be aware of the potential uncertainty of incremental effectiveness and resultant value-for-money assessment when making reimbursement decisions based on initial publications with immature survival data. [ABSTRACT FROM AUTHOR]