The Epidemiologic Comparison of Two Correlated Relative Risks: A Simple but Efficient Clinical Trial Design for Assessing Risk-Reduction and Treatment Significance

In the context of platform design, umbrella trials are a type of master protocol in which multiple treatments are randomized and evaluated with respect to a common, referent-control arm. In a simplified (1:1:1), non-adapted case, this is equivalent to the epidemiologic comparison of two correlated relative risks for assessing risk-reduction on the log-difference scale. The use of shared controls has the potential to reduce study time and costs but infers greater complexity to account for the covariance between relative effect estimates (i.e., dependence arising because treatment arms use the same referent group). Multiplicity adjustment is unnecessary on the log-difference scale (three-group design) as this is a single test statistic for interaction. An intuitive, risk-reduction (LDL-C statin) example is presented to illustrate the practical application of this method.

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Publication Details

Journal
Medicina
Published
2025-12-29
DOI
https://doi.org/10.3390/medicina62010070
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
0.00

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article

The Epidemiologic Comparison of Two Correlated Relative Risks: A Simple but Efficient Clinical Trial Design for Assessing Risk-Reduction and Treatment Significance

Jimmy T. Efird, Hongsheng Wu, Genevieve Dupuis, Yuk Ming Choi
Medicina
Statistical Methods in Clinical Trials
article

The Epidemiologic Comparison of Two Correlated Relative Risks: A Simple but Efficient Clinical Trial Design for Assessing Risk-Reduction and Treatment Significance

Jimmy T. Efird, Hongsheng Wu, Genevieve Dupuis, Yuk Ming Choi
article en

Abstract

In the context of platform design, umbrella trials are a type of master protocol in which multiple treatments are randomized and evaluated with respect to a common, referent-control arm. In a simplified (1:1:1), non-adapted case, this is equivalent to the epidemiologic comparison of two correlated relative risks for assessing risk-reduction on the log-difference scale. The use of shared controls has the potential to reduce study time and costs but infers greater complexity to account for the covariance between relative effect estimates (i.e., dependence arising because treatment arms use the same referent group). Multiplicity adjustment is unnecessary on the log-difference scale (three-group design) as this is a single test statistic for interaction. An intuitive, risk-reduction (LDL-C statin) example is presented to illustrate the practical application of this method.

MedicinaVol. 62(1)
Boston University (US), The Coordinating Center (US), Valley Health System (US), Case Western Reserve University (US), Babson College (US)
National Institutes of Health
Good health and well-being
Openalex Percentile: Top 22%
Statistical Methods in Clinical Trials
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