2021/05/17 by Deborah Plana, Geoffrey Fell, Brian M. Alexander +2 · 1 citation
Mathematics · Economics, Econometrics and Finance · Biochemistry, Genetics and Molecular Biology · #Statistical Methods in Clinical Trials #Health Systems, Economic Evaluations, Quality of Life #Cancer Genomics and Diagnostics
paper · pdf · doi:10.1101/2021.05.14.442837
openalex publication_date 2021/05/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
SUMMARY Individual participant data (IPD) from completed oncology clinical trials are a valuable but rarely available source of information. A lack of minable survival distributions has made it difficult to identify factors determining the success and failure of clinical trials and improve trial design. We imputed survival IPD from ∼500 arms of phase III oncology trials (representing ∼220,000 events) and found that they are well fit by a two-parameter Weibull distribution. This makes it possible to use parametric statistics to substantially increase trial precision with small patient cohorts typical of phase I or II trials. For example, a 50-person trial parameterized using Weibull distributions is as precise as a 90-person trial evaluated using traditional statistics. Mining IPD also showed that frequent violations of the proportional hazards assumption, particularly in trials of immune checkpoint inhibitors (ICIs), arise from time-dependent therapeutic effects and hazard ratios. Thus, the duration of ICI trials has an underappreciated impact on the likelihood of their success.