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Lookup NU author(s): Dr Jessica Barrett, Professor James WasonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2022 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. Mixed outcome endpoints that combine multiple continuous and discrete components are often employed as primary outcome measures in clinical trials. These may be in the form of co-primary endpoints, which conclude effectiveness overall if an effect occurs in all of the components, or multiple primary endpoints, which require an effect in at least one of the components. Alternatively, they may be combined to form composite endpoints, which reduce the outcomes to a one-dimensional endpoint. There are many advantages to joint modeling the individual outcomes, however in order to do this in practice we require techniques for sample size estimation. In this article we show how the latent variable model can be used to estimate the joint endpoints and propose hypotheses, power calculations and sample size estimation methods for each. We illustrate the techniques using a numerical example based on a four-dimensional endpoint and find that the sample size required for the co-primary endpoint is larger than that required for the individual endpoint with the smallest effect size. Conversely, the sample size required in the multiple primary case is similar to that needed for the outcome with the largest effect size. We show that the empirical power is achieved for each endpoint and that the FWER can be sufficiently controlled using a Bonferroni correction if the correlations between endpoints are less than 0.5. Otherwise, less conservative adjustments may be needed. We further illustrate empirically the efficiency gains that may be achieved in the composite endpoint setting.
Author(s): McMenamin ME, Barrett JK, Berglind A, Wason JMS
Publication type: Article
Publication status: Published
Journal: Statistics in Medicine
Year: 2022
Volume: 41
Issue: 13
Pages: 2303-2316
Print publication date: 15/06/2022
Online publication date: 23/02/2022
Acceptance date: 02/02/2022
Date deposited: 04/04/2022
ISSN (print): 0277-6715
ISSN (electronic): 1097-0258
Publisher: John Wiley and Sons Ltd
URL: https://doi.org/10.1002/sim.9356
DOI: 10.1002/sim.9356
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