Cure rate estimation with insufficient follow-up: A median-based bootstrap correction approach

Abstract

The cure rate in clinical trials can be estimated using the Kaplan–Meier (KM) estimator. However, when the clinical trial follow-up period is insufficient and short, the KM estimator may overestimate the proportion of cured patients. Although a correction method was proposed by Escobar-Bach and Keilegom based on bootstrap sampling, this can also lead to bias when the bootstrap distribution is skewed. We propose a median-based approach for bootstrap samples to address these issues. Simulation results showed that the effect of the variation of the proposed method due to many outliers was smaller than that of the other method and enabled stable estimation. The method was successfully applied to real clinical trial data from a D-penicillamine study on primary biliary cirrhosis.