Bias in Mean Survival From Fitting Cure Models With Limited Follow-Up.

ABSTRACT:

Objectives

When populations contain mixtures of cured and uncured patients, the use of traditional parametric approaches to estimate overall survival (OS) can be biased. Mixture cure models may reduce bias compared with traditional parametric models, but their accuracy is subject to certain conditions. Importantly, mixture cure models assume that that there is enough follow-up to identify individuals censored at the end of the follow-up period as cured. The purpose of this article is to describe biases that can occur when mixture cure models are used to estimate mean survival from data with limited follow-up.

Methods

We analyzed 6 trials conducted by the SWOG Cancer Research Network Leukemia Committee. For each trial, we analyzed 2 data sets: the data released to the committ

SUBMITTER: Othus M 

PROVIDER: S-EPMC7446760 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature