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

Ryan Sun, Zachary Mccaw, Lu Tian, Hajime Uno, Fangxin Hong, Dae Hyun Kim, Lee Jen Wei

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article numbere003323
JournalJournal for immunotherapy of cancer
Volume9
Issue number11
DOIs
StatePublished - Nov 19 2021
Externally publishedYes

Keywords

  • biostatistics
  • clinical trials as topic
  • immunotherapy

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology
  • Molecular Medicine
  • Oncology
  • Pharmacology
  • Cancer Research

MD Anderson CCSG core facilities

  • Biostatistics Resource Group

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