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Moving beyond conventional stratified analysis to assess the treatment effect in a comparative oncology study

In a comparative oncology study with progression-free or overall survival as the endpoint, the primary or key secondary analysis is routinely stratified by patients’ baseline characteristics when evaluating the treatment difference. The validity of a conventional strategy such as a stratified HR ana...

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Detalles Bibliográficos
Autores principales: Sun, Ryan, McCaw, Zachary, Tian, Lu, Uno, Hajime, Hong, Fangxin, Kim, Dae Hyun, Wei, Lee-Jen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606770/
https://www.ncbi.nlm.nih.gov/pubmed/34799398
http://dx.doi.org/10.1136/jitc-2021-003323
Descripción
Sumario:In a comparative oncology study with progression-free or overall survival as the endpoint, the primary or key secondary analysis is routinely stratified by patients’ baseline characteristics when evaluating the treatment difference. The validity of a conventional strategy such as a stratified HR analysis depends on stringent model assumptions that are unlikely to be met in practice, especially in immunotherapy studies. Thus, the resulting summary is generally neither valid nor interpretable. This article discusses issues with conventional stratified analyses and presents alternatives using data from KEYNOTE-189, a recent immunotherapy trial for treating patients with metastatic, non-squamous, non-small-cell lung cancer.