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bioRxiv · 10.1101/2021.05.14.442837

Cancer patient survival can be accurately parameterized, revealing time-dependent therapeutic effects and doubling the precision of small trials

Plana, D.·Fell, G.·Alexander, B. M.·Palmer, A. C.·Sorger, P. K.
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Abstract

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.

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Plana, D., Fell, G., Alexander, B. M., Palmer, A. C., Sorger, P. K.. 2021-05-17. Cancer patient survival can be accurately parameterized, revealing time-dependent therapeutic effects and doubling the precision of small trials. https://doi.org/10.1101/2021.05.14.442837

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