Derivative survival analyses: Analysis methods to derive survival outcomes for the remainder patient cohort without individual patient data

Niraj K. Shenoy*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

It is not uncommon for industry-sponsored randomized controlled trials to publish survival curves/data for the overall patient cohort(“A+B”) and for a favorable subgroup (“A”) pre-specified or post hoc, but not the survival curves/data for the remainder cohort(“B”). Consequently, following regulatory approval of the intervention treatment for the overall patient population if the primary endpoint is met, it is common for cancer patients representing the remainder cohort (B) to be treated as per the results of the overall cohort (A+B). To overcome this important issue in clinical decision-making, this study aimed to identify methods to accurately derive the survival curves and/or hazard ratio (95% confidence interval) for the remainder cohort (B), utilizing published curves and hazard ratios (95% confidence intervals) of the overall (A+B) and favorable subgroup (A) cohorts. The analysis methods (method I and method II) presented here, termed “derivative survival analyses,” enable accurate assessment of survival outcomes in the remainder cohort without individual patient data.

Original languageEnglish (US)
Article number101500
JournalCell Reports Medicine
Volume5
Issue number4
DOIs
StatePublished - Apr 16 2024

Keywords

  • derivative analysis
  • immunotherapy
  • individual patient data
  • randomized controlled trials
  • remainder cohort
  • survival analysis

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology

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