Faculty, Staff and Student Publications
Publication Date
9-1-2024
Journal
JCO Clinical Cancer Informatics
DOI
10.1200/CCI.24.00102
PMID
39213473
PMCID
PMC11371366
PubMedCentral® Posted Date
9-1-2025
PubMedCentral® Full Text Version
Author MSS
Abstract
Purpose: A previous study demonstrated that power against the (unobserved) true effect for the primary end point (PEP) of most phase III oncology trials is low, suggesting an increased risk of false-negative findings in the field of late-phase oncology. Fitting models with prognostic covariates is a potential solution to improve power; however, the extent to which trials leverage this approach, and its impact on trial interpretation at scale, is unknown. To that end, we hypothesized that phase III trials using multivariable PEP analyses are more likely to demonstrate superiority versus trials with univariable analyses.
Methods: PEP analyses were reviewed from trials registered on ClinicalTrials.gov. Adjusted odds ratios (aORs) were calculated by logistic regressions.
Results: Of the 535 trials enrolling 454,824 patients, 69% (n = 368) used a multivariable PEP analysis. Trials with multivariable PEP analyses were more likely to demonstrate PEP superiority (57% [209 of 368] v 42% [70 of 167]; aOR, 1.78 [95% CI, 1.18 to 2.72]; P = .007). Among trials with a multivariable PEP model, 16 conditioned on covariates and 352 stratified by covariates. However, 108 (35%) of 312 trials with stratified analyses lost power by categorizing a continuous variable, which was especially common among immunotherapy trials (aOR, 2.45 [95% CI, 1.23 to 4.92]; P = .01).
Conclusion: 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.
Keywords
Humans, Clinical Trials, Phase III as Topic, Endpoint Determination, Medical Oncology, Multivariate Analysis, Neoplasms, Odds Ratio, Prognosis
Published Open-Access
yes
Recommended Citation
Sherry, Alexander D; Passy, Adina H; McCaw, Zachary R; et al., "Increasing Power in Phase III Oncology Trials With Multivariable Regression: An Empirical Assessment of 535 Primary End Point Analyses" (2024). Faculty, Staff and Student Publications. 4852.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/4852
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