Increasing Power in Phase III Oncology Trials With Multivariable Regression: An Empirical Assessment of 535 Primary End Point Analyses
Trials increasing power by fitting multivariable models were more likely to demonstrate PEP superiority than trials with unadjusted analysis. Underutilization of conditioning models and empirical power loss associated with covariate categorization required by stratification were identified as barriers to power gains. These findings underscore the opportunity to increase power in phase III trials with conventional methodology and improve patient access to effective novel therapies.
Authors
- Timothy A. Lin (ORCID: https://orcid.org/0000-0003-4183-9120)
- Alexander D. Sherry (ORCID: https://orcid.org/0000-0001-5115-1691)
- Ethan B. Ludmir (ORCID: https://orcid.org/0000-0002-5472-5344)
- Zachary R. McCaw (ORCID: https://orcid.org/0000-0002-2006-9828)
- Joseph Abi Jaoude (ORCID: https://orcid.org/0000-0002-2283-4765)
- Ramez Kouzy (ORCID: https://orcid.org/0000-0002-1521-0495)
- Pavlos Msaouel (ORCID: https://orcid.org/0000-0001-6505-8308)
- Esther J. Beck
- Gabrielle S. Kupferman (ORCID: https://orcid.org/0000-0003-2088-4395)
- Adina H. Passy (ORCID: https://orcid.org/0000-0002-8626-8969)
- Avital M. Miller (ORCID: https://orcid.org/0009-0007-4072-1442)
Institutions
- University of North Carolina at Chapel Hill (US)
- The University of Texas MD Anderson Cancer Center (US)
- Johns Hopkins University (US)
- Johns Hopkins Medicine (US)
- Stanford University (US)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2024-08-30
- DOI
- https://doi.org/10.1200/cci.24.00102
- Citations
- 8
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 5.67
Funders
- University of Texas MD Anderson Cancer Center
- National Cancer Institute