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

View ORCID ProfileDeborah Plana, Geoffrey Fell, Brian M. Alexander, View ORCID ProfileAdam C. Palmer, View ORCID ProfilePeter K. Sorger
doi: https://doi.org/10.1101/2021.05.14.442837
Deborah Plana
1Laboratory of Systems Pharmacology and the Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA
2Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School and MIT, Cambridge, Massachusetts, USA
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Geoffrey Fell
3Dana-Farber Cancer Institute, Boston, Massachusetts, USA
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Brian M. Alexander
3Dana-Farber Cancer Institute, Boston, Massachusetts, USA
4Foundation Medicine Inc., Cambridge, Massachusetts, USA
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Adam C. Palmer
5Department of Pharmacology, Computational Medicine Program, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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  • For correspondence: palmer@unc.edu peter_sorger@hms.harvard.edu sorger_admin@hms.harvard.edu
Peter K. Sorger
1Laboratory of Systems Pharmacology and the Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA
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  • For correspondence: palmer@unc.edu peter_sorger@hms.harvard.edu sorger_admin@hms.harvard.edu
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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.

Competing Interest Statement

P.K. Sorger is a member of the SAB or Board of Directors of Applied Biomath, Glencoe Software, RareCyte Inc and NanoString and has equity in the first three of these companies. In the last five years the Sorger lab has received research funding from Novartis and Merck. Sorger declares that none of these relationships are directly or indirectly related to the content of this manuscript. B.M. Alexander is an employee of Foundation Medicine. No potential conflicts of interest were disclosed by the other authors.

Footnotes

  • http://www.cancertrials.io/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 17, 2021.
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Cancer patient survival can be accurately parameterized, revealing time-dependent therapeutic effects and doubling the precision of small trials
Deborah Plana, Geoffrey Fell, Brian M. Alexander, Adam C. Palmer, Peter K. Sorger
bioRxiv 2021.05.14.442837; doi: https://doi.org/10.1101/2021.05.14.442837
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Cancer patient survival can be accurately parameterized, revealing time-dependent therapeutic effects and doubling the precision of small trials
Deborah Plana, Geoffrey Fell, Brian M. Alexander, Adam C. Palmer, Peter K. Sorger
bioRxiv 2021.05.14.442837; doi: https://doi.org/10.1101/2021.05.14.442837

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