Handling informative dropout in longitudinal analysis of health-related quality of life: application of three approaches to data from the esophageal cancer clinical trial PRODIGE 5/ACCORD 17.

Date publication

septembre 2020

Journal

BMC medical research methodology

Auteurs

Membres identifiés du Cancéropôle Est :
Pr CONROY Thierry

Tous les auteurs :
Cuer B, Mollevi C, Anota A, Charton E, Juzyna B, Conroy T, Touraine C

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/32883216

Résumé

Health-related quality of life (HRQoL) has become a major endpoint to assess the clinical benefit of new therapeutic strategies in oncology clinical trials. Typically, HRQoL outcomes are analyzed using linear mixed models (LMMs). However, longitudinal analysis of HRQoL in the presence of missing data remains complex and unstandardized. Our objective was to compare the modeling alternatives that account for informative dropout.

Mots clés

Cancer clinical trial, Health-related quality of life, Informative dropout, Joint modeling, Pattern-mixture model, Selection model, Shared-parameters model

Référence

BMC Med Res Methodol. 2020 Sep 3;20(1):223