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

Author

Listed:
  • Deborah Plana

    (Harvard Medical School
    Harvard Medical School and MIT)

  • Geoffrey Fell

    (Dana-Farber Cancer Institute)

  • Brian M. Alexander

    (Dana-Farber Cancer Institute
    Foundation Medicine Inc.)

  • Adam C. Palmer

    (University of North Carolina at Chapel Hill)

  • Peter K. Sorger

    (Harvard Medical School)

Abstract

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.

Suggested Citation

  • Deborah Plana & Geoffrey Fell & Brian M. Alexander & Adam C. Palmer & Peter K. Sorger, 2022. "Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28410-9
    DOI: 10.1038/s41467-022-28410-9
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    References listed on IDEAS

    as
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