Dynamic prediction of overall survival: a retrospective analysis on 979 patients with Ewing sarcoma from the German registry.

ABSTRACT:

Objectives

This study aimed at developing a dynamic prediction model for patients with Ewing sarcoma (ES) to provide predictions at different follow-up times. During follow-up, disease-related information becomes available, which has an impact on a patient's prognosis. Many prediction models include predictors available at baseline and do not consider the evolution of disease over time.

Setting

In the analysis, 979 patients with ES from the Gesellschaft für Pädiatrische Onkologie und Hämatologie registry, who underwent surgery and treatment between 1999 and 2009, were included.

Design

A dynamic prediction model was developed to predict updated 5-year survival probabilities from different prediction time points during follow-up. Time-dependent variables, such as local

SUBMITTER: Liu C 

PROVIDER: S-EPMC7552850 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature