Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects

Nat Commun. 2022 Feb 15;13(1):873. doi: 10.1038/s41467-022-28410-9.


Individual participant data (IPD) from oncology clinical trials is invaluable for identifying factors that influence trial success and failure, improving trial design and interpretation, and comparing pre-clinical studies to clinical outcomes. However, the IPD used to generate published survival curves are not generally publicly available. We impute survival IPD from ~500 arms of Phase 3 oncology trials (representing ~220,000 events) and find that they are well fit by a two-parameter Weibull distribution. Use of Weibull functions with overall survival significantly increases the precision of small arms typical of early phase trials: analysis of a 50-patient trial arm using parametric forms is as precise as traditional, non-parametric analysis of a 90-patient arm. We also show that frequent deviations from the Cox proportional hazards assumption, particularly in trials of immune checkpoint inhibitors, arise from time-dependent therapeutic effects. Trial duration therefore has an underappreciated impact on the likelihood of success.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cancer Survivors / statistics & numerical data*
  • Clinical Trials as Topic / methods*
  • Humans
  • Kaplan-Meier Estimate
  • Models, Statistical
  • Neoplasms / mortality*
  • Neoplasms / therapy*
  • Proportional Hazards Models
  • Research Design / statistics & numerical data*