Estimating cure proportion in cancer clinical trials using flexible parametric cure models

BJC Rep. 2024 Aug 28;2(1):61. doi: 10.1038/s44276-024-00092-4.

Abstract

Background: In the context of survival analysis in recent cancer clinical trials, there has been an increasing interest in the proportion of patients who are not susceptible to the event, known as the cure proportion. To estimate it, cure models implicitly specify the time point when patients are considered cured, although the impact of the cure point position on cure proportion estimates is unclear.

Methods: Sensitivity of cure proportion estimates to the knot number and placement in flexible parametric cure models was examined using data from a clinical trial of CheckMate 141, an immuno-oncology compound. The performance of the model and procedures to determine the cure point position were evaluated using a simulation study.

Results: Analysis of the CheckMate 141 data showed the impact of the last knot position on the cure proportion estimate and model fit. Simulations revealed that the flexible parametric cure model with the last knot at the last observed event time overestimated the cure proportion. This bias was reduced when the last knot was placed later.

Conclusions: For cure proportion estimation in clinical trials with survival outcomes, the flexible parametric cure model can be an attractive alternative to the Kaplan-Meier method.