MSR95 Use of Generalized F Parameterization in Long-Term Extrapolation for Adjuvant Cancer Therapies

Abstract

In the adjuvant oncology setting, there is often an initial high risk of relapse or death after surgery, but patients who remain relapse free for a longer period may experience outcomes similar to the general population. Flexible survival modelling approaches, such as spline or semi-parametric analysis, are required to provide good fits to observed data while predicting plausible long-term outcomes. In contrast to spline models, which rely on continuity assumptions and may not be limited to positive hazards, the generalized F (genF) function is a flexible, fully parametric extension to the most common survival distributions, and so shares the same extrapolative assumptions as these well-accepted models. As such, this approach was explored and applied in two recent NICE submissions for adjuvant therapies. This paper highlights key challenges associated with the genF distribution and describes potential solutions.