Survival analysis and extrapolation modeling of time-to-event clinical trial data for economic evaluation: an alternative approach.

ABSTRACT

A recent publication includes a review of survival extrapolation methods used in technology appraisals of treatments for advanced cancers. The author of the article also noted shortcomings and inconsistencies in the analytical methods used in appraisals. He then proposed a survival model selection process algorithm to guide modelers' choice of projective models for use in future appraisals. This article examines the proposed algorithm and highlights various shortcomings that involve questionable assumptions, including researchers' access to patient-level data, the relevance of proportional hazards modeling, and the appropriateness of standard probability functions for characterizing risk, which may mislead practitioners into employing biased structures for projecting limited data in decision models. An alternative paradigm is outlined. This paradigm is based on the primacy of the experimental data and adherence to the scientific method through hypothesis formulation and validation. Drawing on extensive experience of survival modeling and extrapolation in the United Kingdom, practical advice is presented on issues of importance when using data from clinical trials terminated without complete follow-up as a basis for survival extrapolation.