{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T11:02:38Z","timestamp":1789642958966,"version":"4.0.0"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:00:00Z","timestamp":1775692800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,4,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Adjusting for prognostic baseline covariates in the design and analysis of randomized controlled trials can increase statistical power and improve the precision of treatment effect estimates by reducing outcome variability. In this paper, we describe how the covariate-adjusted log-rank test can be used to enhance the power of late-phase oncology studies with primary time-to-event endpoints. Using a case study of a metastatic castration-resistant prostate cancer trial with overall survival as the primary endpoint, we demonstrate how to estimate variance reductions achievable through different covariate adjustment strategies, including adjustment for a prognostic score, based on historical data. We also compare these strategies with respect to Type I error rate control. We further describe a method that can be used to prevent Type I error rate inflation that can arise when naively embedding covariate adjustment within a group sequential design. A simulation study illustrates the performance of this method across scenarios with different prognostic covariate strength and different numbers of events, randomization strata, and interim analyses. Finally, we present a re-analysis of the overall survival endpoint from a trial in metastatic colorectal cancer using covariate adjustment in a group sequential design.<\/jats:p>","DOI":"10.1093\/biomtc\/ujag109","type":"journal-article","created":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T11:48:10Z","timestamp":1779968890000},"source":"Crossref","is-referenced-by-count":0,"title":["Practical considerations when using the covariate-adjusted log-rank test for the analysis of time-to-event endpoints in oncology trials"],"prefix":"10.1093","volume":"82","author":[{"given":"Daniel","family":"Backenroth","sequence":"first","affiliation":[{"name":"Statistics and Decision Sciences, Johnson & Johnson , Raritan, NJ 08869 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3453-5269","authenticated-orcid":false,"given":"Sanne","family":"Roels","sequence":"additional","affiliation":[{"name":"Statistics and Decision Sciences, Johnson & Johnson , 2340 Beerse ,","place":["Belgium"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiva","family":"Dibaj","sequence":"additional","affiliation":[{"name":"Statistics and Decision Sciences, Johnson & Johnson , La Jolla, CA 92121 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6009-641X","authenticated-orcid":false,"given":"Ting","family":"Ye","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington , Seattle, WA 98195 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fredrik","family":"\u00d6hrn","sequence":"additional","affiliation":[{"name":"Statistics and Decision Sciences, Johnson & Johnson , SE-170 67 Stockholm ,","place":["Sweden"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3458-3788","authenticated-orcid":false,"given":"Kelly","family":"Van\u00a0Lancker","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Computer Science and Statistics, Ghent University , 9000 Ghent ,","place":["Belgium"]},{"name":"Vrije Universiteit Brussel Department of Mathematics and Data Science, , 1050 Brussels ,","place":["Belgium"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,6,17]]},"reference":[{"key":"2026091706171726500_bib1","doi-asserted-by":"crossref","first-page":"2094","DOI":"10.1200\/JCO-24-01968","article-title":"Characteristics of patients and prognostic factors across treatment lines in metastatic colorectal cancer: An analysis from the Aide et Recherche en Canc\u00e9rologie Digestive Database","volume":"43","author":"Bachet","year":"2025","journal-title":"Journal of Clinical Oncology"},{"key":"2026091706171726500_bib2","doi-asserted-by":"crossref","first-page":"e70577","DOI":"10.1002\/sim.70577","article-title":"Adaptive designs in trials with time-to-event endpoints and covariate adjustment","volume":"45","author":"Backenroth","year":"2026","journal-title":"Statistics in Medicine"},{"key":"2026091706171726500_bib3","doi-asserted-by":"crossref","first-page":"ujad034","DOI":"10.1093\/biomtc\/ujad034","article-title":"Adaptive selection of the optimal strategy to improve precision and power in randomized trials","volume":"80","author":"Balzer","year":"2024","journal-title":"Biometrics"},{"key":"2026091706171726500_bib4","doi-asserted-by":"crossref","first-page":"1713","DOI":"10.1002\/sim.2059","article-title":"Generating survival times to simulate Cox proportional hazards models","volume":"24","author":"Bender","year":"2005","journal-title":"Statistics in Medicine"},{"key":"2026091706171726500_bib5","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1111\/biom.13377","article-title":"Improving precision and power in randomized Ttials for COVID-19 treatments using covariate adjustment, for binary, ordinal, and time-to-event outcomes","volume":"77","author":"Benkeser","year":"2020","journal-title":"Biometrics"},{"key":"2026091706171726500_bib6","doi-asserted-by":"crossref","first-page":"C1","DOI":"10.1111\/ectj.12097","article-title":"Double\/debiased machine learning for treatment and structural parameters","volume":"21","author":"Chernozhukov","year":"2018","journal-title":"The Econometrics Journal"},{"key":"2026091706171726500_bib7","article-title":"Guideline on adjustment for baseline covariates in clinical trials","author":"CHMP","year":"2015"},{"key":"2026091706171726500_bib8","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-4541-9","volume-title":"An Introduction to the Bootstrap","author":"Efron","year":"1993"},{"key":"2026091706171726500_bib9","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1634\/theoncologist.2014-0431","article-title":"The Project Data Sphere Initiative: Accelerating cancer research by sharing data","volume":"20","author":"Green","year":"2015","journal-title":"The Oncologist"},{"key":"2026091706171726500_bib10","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1200\/JCO.2013.52.3696","article-title":"Updated prognostic model for predicting overall survival in first-line chemotherapy for patients with metastatic castration-resistant prostate cancer","volume":"32","author":"Halabi","year":"2014","journal-title":"Journal of Clinical Oncology"},{"key":"2026091706171726500_bib11","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-19425-7","volume-title":"Regression Modeling Strategies","author":"Harrell","year":"2015"},{"key":"2026091706171726500_bib12","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1080\/01621459.1997.10473654","article-title":"Group-sequential analysis incorporating covariate information","volume":"92","author":"Jennison","year":"1997","journal-title":"Journal of the American Statistical Association"},{"key":"2026091706171726500_bib13","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1093\/jrsssb\/qkad007","article-title":"Estimating the efficiency gain of covariate-adjusted analyses in future clinical trials using external data","volume":"85","author":"Li","year":"2023","journal-title":"Journal of the Royal Statistical Society Series B: Statistical Methodology"},{"key":"2026091706171726500_bib14","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1093\/biomet\/asn003","article-title":"Improving the effi ciency of the log-rank test using auxiliary covariates","volume":"95","author":"Lu","year":"2008","journal-title":"Biometrika"},{"key":"2026091706171726500_bib15","first-page":"163","article-title":"Evaluation of survival data and two new rank order statistics arising in its consideration","volume":"50","author":"Mantel","year":"1966","journal-title":"Cancer Chemotherapy Reports"},{"key":"2026091706171726500_bib16","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1177\/009286150103500407","article-title":"Flexible sample size considerations using information-based interim monitoring","volume":"35","author":"Mehta","year":"2001","journal-title":"Drug Information Journal"},{"key":"2026091706171726500_bib17","article-title":"Commentary submitted to the EMA on the Qualification Opinion for Prognostic Covariate Adjustment (PROCOVA)","author":"MSD","year":"2022"},{"key":"2026091706171726500_bib18","doi-asserted-by":"crossref","first-page":"4706","DOI":"10.1200\/JCO.2009.27.6055","article-title":"Randomized phase III study of panitumumab with fluorouracil, leucovorin, and irinotecan (FOLFIRI) compared with FOLFIRI alone as second-line treatment in patients with metastatic colorectal cancer","volume":"28","author":"Peeters","year":"2010","journal-title":"Journal of Clinical Oncology"},{"key":"2026091706171726500_bib19","article-title":"Super learner in prediction","author":"Polley","year":"2010"},{"key":"2026091706171726500_bib20","article-title":"How to get the most out of prognostic baseline variables in clinical trials. effective strategies for employing covariate adjustment and stratification","author":"Schiffman","year":"2022"},{"key":"2026091706171726500_bib21","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1515\/ijb-2021-0072","article-title":"Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score","volume":"18","author":"Schuler","year":"2021","journal-title":"International Journal of Biostatistics"},{"key":"2026091706171726500_bib22","article-title":"Benchmarking covariate-adjustment strategies for randomized clinical trials","author":"Shao","year":"2026"},{"key":"2026091706171726500_bib23","doi-asserted-by":"crossref","first-page":"ujae094","DOI":"10.1093\/biomtc\/ujae094","article-title":"Adjusting for incomplete baseline covariates in randomized controlled trials: a cross-world imputation framework","volume":"80","author":"Song","year":"2024","journal-title":"Biometrics."},{"key":"2026091706171726500_bib24","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1023\/A:1009648914586","article-title":"An asymptotic analysis of the logrank test","volume":"3","author":"Strawderman","year":"1997","journal-title":"Lifetime Data Analysis"},{"key":"2026091706171726500_bib25","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1093\/biomet\/73.2.363","article-title":"Misspecified proportional hazard models","volume":"73","author":"Struthers","year":"1986","journal-title":"Biometrika"},{"key":"2026091706171726500_bib26","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1081\/BIP-100101179","article-title":"Nonparametric analysis of covariance for hypothesis testing with logrank and wilcoxon scores and survival-rate estimation in a randomized clinical trial","volume":"9","author":"Tangen","year":"1999","journal-title":"Journal of Biopharmaceutical Statistics"},{"key":"2026091706171726500_bib27","doi-asserted-by":"crossref","first-page":"e70307","DOI":"10.1002\/sim.70307","article-title":"Independent increments and group sequential tests","volume":"44","author":"Tsiatis","year":"2025","journal-title":"Statistics in Medicine"},{"key":"2026091706171726500_bib28","doi-asserted-by":"crossref","first-page":"4658","DOI":"10.1002\/sim.3113","article-title":"Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: A principled yet flexible approach","volume":"27","author":"Tsiatis","year":"2008","journal-title":"Statistics in Medicine"},{"key":"2026091706171726500_bib29","article-title":"Adjusting for covariates in randomized clinical trials for drugs and biological products","author":"U.S. FDA","year":"2023"},{"key":"2026091706171726500_bib30","doi-asserted-by":"crossref","first-page":"ujaf020","DOI":"10.1093\/biomtc\/ujaf020","article-title":"Combining covariate adjustment with group sequential, information-adaptive designs to improve randomized trial efficiency","volume":"81","author":"Van\u00a0Lancker","year":"2025","journal-title":"Biometrics"},{"key":"2026091706171726500_bib31","article-title":"Automated, efficient and model-free inference for randomized clinical trials via data-driven covariate adjustment","author":"Van\u00a0Lancker","year":"2024"},{"key":"2026091706171726500_bib32","article-title":"Commentary submitted to the EMA on the Qualification Opinion for Prognostic Covariate Adjustment (PROCOVA)","author":"Van\u00a0Lancker","year":"2022"},{"key":"2026091706171726500_bib33","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1214\/24-STS937","article-title":"Feature importance: a closer look at Shapley values and LOCO","volume":"39","author":"Verdinelli","year":"2024","journal-title":"Statistical Science"},{"key":"2026091706171726500_bib34","doi-asserted-by":"crossref","first-page":"1152","DOI":"10.1080\/01621459.2021.1981338","article-title":"Model-robust inference for clinical trials that improve precision by stratified randomization and covariate adjustment","volume":"118","author":"Wang","year":"2023","journal-title":"Journal of the American Statistical Association"},{"key":"2026091706171726500_bib35","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1093\/biomet\/asad045","article-title":"Covariate-adjusted log-rank test: Guaranteed efficiency gain and universal applicability","volume":"111","author":"Ye","year":"2024","journal-title":"Biometrika"},{"key":"2026091706171726500_bib36","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1080\/01621459.2022.2123814","article-title":"To adjust or not to adjust? Estimating the average treatment effect in randomized experiments with missing covariates","volume":"119","author":"Zhao","year":"2024","journal-title":"Journal of the American Statistical Association"},{"key":"2026091706171726500_bib37","article-title":"Covariate adjustment in randomized experiments motivated by higher-order influence functions","author":"Zhao","year":"2024"}],"container-title":["Biometrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/biometrics\/article-pdf\/82\/2\/ujag109\/68541197\/ujag109.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/biometrics\/article-pdf\/82\/2\/ujag109\/68541197\/ujag109.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T10:17:27Z","timestamp":1789640247000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/biometrics\/article\/doi\/10.1093\/biomtc\/ujag109\/8709753"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,9]]},"references-count":37,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,4,9]]}},"URL":"https:\/\/doi.org\/10.1093\/biomtc\/ujag109","relation":{},"ISSN":["0006-341X","1541-0420"],"issn-type":[{"value":"0006-341X","type":"print"},{"value":"1541-0420","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,6]]},"published":{"date-parts":[[2026,4,9]]},"article-number":"ujag109"}}