Moving beyond the Cox proportional hazards model in survival data analysis: a cervical cancer study.

ABSTRACT:

Objectives

This study explored the prognostic factors and developed a prediction model for Chinese-American (CA) cervical cancer (CC) patients. We compared two alternative models (the restricted mean survival time (RMST) model and the proportional baselines landmark supermodel (PBLS model, producing dynamic prediction)) versus the Cox proportional hazards model in the context of time-varying effects.

Setting and data sources

A total of 713 CA women with CC and available covariates (age at diagnosis, International Federation of Gynecology and Obstetrics (FIGO) stage, lymph node metastasis and radiation) from the Surveillance, Epidemiology and End Results database were included.

Design

We applied the Cox proportional hazards model to analyse the all-cause mortality with

SUBMITTER: Li L 

PROVIDER: S-EPMC7371360 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature