Background Hierarchical composite outcomes, analyzed using the win ratio, are increasingly used in randomized clinical trials (RCTs). However, methods for covariate adjustment in this context are underdeveloped, despite evidence that adjusting for prognostic variables can increase statistical power.

Objectives Introducing a new covariate adjustment method for hierarchical outcomes using ordinal logistic regression, comparing it with existing approaches, and assessing whether adjustment improves power in randomized trials with hierarchical outcomes.

Methods We developed an ordinal regression-based method for covariate adjustment of the win ratio and compared it with three alternatives: probability index models, inverse probability weighting, and a randomization-based estimator. Methods were applied to the EMPEROR-Preserved rial and tested through extensive simulations involving two common hierarchical outcome structures: time-to-event composites, and composites combining time-to-event with quantitative measures. Simulations assessed impacts on estimates, standard errors, and power across prognostic and non-prognostic settings.

Results In RCT data and simulations, covariate adjustment consistently increased power when adjusting for prognostic baseline variables. Gains were comparable to or greater than those in conventional Cox models, with no power loss for non-prognostic covariates. Our ordinal approach performed similarly to existing methods while providing interpretable covariate effect estimates. Adjusting for baseline values of quantitative components yielded power gains according to the baseline-to-follow-up correlation.

Conclusions Covariate adjustment for prognostic variables meaningfully improves efficiency in win ratio analyses for hierarchical outcomes. Our ordinal method is easily implemented and facilitates covariate effect interpretation. We recommend the broader adoption of covariate adjustment and our ordinal method in randomized trials using hierarchical outcomes.

Dr Hazewinkel has received research support from AstraZeneca. Dr Gregson is employed by Boston Scientific and declares research funding from AstraZeneca; consultancy fees from Boehringer Ingelheim. Dr Bartlett has in the past received consultancy fees from Bayer and Roche for statistical methodology advice; his past and present institutions have received consultancy fees for his advice on statistical methodology from AstraZeneca, Bayer, Novartis, and Roche. Dr Gasparyan is employed by and has shares in AstraZeneca. Dr. Wright is employed by and has shares in AstraZeneca. Dr Pocock declares research funding from AstraZeneca, Merk. Trial Committees with Abiomed, Bayer, Boehringer Ingelheim, CSL Behring, Fractyl, Idorsia, Janssen, Medtronic, Novartis, Occlutech. Consultancy from Amgen, BioConvergent, Boston Scientific, Cardiol, CVRx, Edwards, Faraday, JenaValve, Lilly, Medtronic, Orchestra BioMed.

NCT03057951

Dr Hazewinkel has received research support from AstraZeneca. Dr Gregson is employed by Boston Scientific and declares research funding from AstraZeneca; consultancy fees from Boehringer Ingelheim. Dr Bartlett has in the past received consultancy fees from Bayer and Roche for statistical methodology advice; his past and present institutions have received consultancy fees for his advice on statistical methodology from AstraZeneca, Bayer, Novartis, and Roche. Dr Gasparyan is employed by and has shares in AstraZeneca. Dr. Wright is employed by and has shares in AstraZeneca. Dr Pocock declares research funding from AstraZeneca, Merk. Trial Committees with Abiomed, Bayer, Boehringer Ingelheim, CSL Behring, Fractyl, Idorsia, Janssen, Medtronic, Novartis, Occlutech. Consultancy from Amgen, BioConvergent, Boston Scientific, Cardiol, CVRx, Edwards, Faraday, JenaValve, Lilly, Medtronic, Orchestra BioMed.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Ethics Committee of the London School of Hygiene and Tropical Medicine waived ethical approval for this work as it involves the secondary analysis of de-identified and anonymised data. This publication is based on research using EMPEROR-Preserved trial data provided by Boehringer Ingelheim (BI) through the Vivli, Inc. platform. Access was granted following the approval of a research proposal by BI and the execution of a Data Use Agreement. The original EMPEROR-Preserved trial (NCT03057951) was conducted in accordance with the principles of the Declaration of Helsinki and the International Conference on Harmonization Good Clinical Practice guidelines. The trial protocol was approved by the ethics committee or institutional review board at each of the 622 participating sites, and all participants provided written informed consent. Vivli has not contributed to or approved, and is not in any way responsible for, the contents of this publication.

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Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

The data used in this study were provided by Boehringer Ingelheim and accessed via the Vivli Inc. platform. The authors are not permitted to share the data under the terms of the Data Use Agreement. De-identified individual participant data and clinical study documents from the EMPEROR-Preserved trial are available to researchers upon approval of a research proposal submitted through the Vivli portal.