Design of Trials with Composite Endpoints with the R Package CompAREdesign

Abstract Composite endpoints are frequently used as primary endpoints in clinical trials, especially those involving time-to-event data. Designing such trials poses significant challenges due to the frequent violation of the proportional hazards assumption when composite endpoints are used, even if the assumption holds true for individual components. Consequently, the conventional formulae for sample size calculation no longer apply. This paper introduces the R package CompAREdesign which incorporates novel methodologies developed by the authors to compute key trial design elements, including sample size and effect sizes, based on information of composite endpoint components. Additionally, the package offers features for designing trials with binary composite endpoints, and functions to simulate trials under a wide range of scenarios. While several R packages exist for analyzing trials with composite endpoints, CompAREdesign package is, to our knowledge, the first package specifically tailored to the design phase of such studies. CompAREdesign is available on CRAN.

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Publication Details

Journal
Statistics in Biosciences
Published
2025-05-15
DOI
https://doi.org/10.1007/s12561-025-09488-3
Citations
1
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
2.63

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article

Design of Trials with Composite Endpoints with the R Package CompAREdesign

Jordi Cortés, Guadalupe Gómez Melis, Marta Bofill Roig
1 citations
Statistics in Biosciences
Statistical Methods in Clinical Trials
2.63
article

Design of Trials with Composite Endpoints with the R Package CompAREdesign

Jordi Cortés, Guadalupe Gómez Melis, Marta Bofill Roig
article en
1 citations

Abstract

Abstract Composite endpoints are frequently used as primary endpoints in clinical trials, especially those involving time-to-event data. Designing such trials poses significant challenges due to the frequent violation of the proportional hazards assumption when composite endpoints are used, even if the assumption holds true for individual components. Consequently, the conventional formulae for sample size calculation no longer apply. This paper introduces the R package CompAREdesign which incorporates novel methodologies developed by the authors to compute key trial design elements, including sample size and effect sizes, based on information of composite endpoint components. Additionally, the package offers features for designing trials with binary composite endpoints, and functions to simulate trials under a wide range of scenarios. While several R packages exist for analyzing trials with composite endpoints, CompAREdesign package is, to our knowledge, the first package specifically tailored to the design phase of such studies. CompAREdesign is available on CRAN.

Statistics in Biosciences
Medical University of Vienna (AT), Universitat Politècnica de Catalunya (ES)
Austrian Science Fund, Generalitat de Catalunya, Ministerio de Economía y Competitividad, Ministerio de Ciencia e Innovación, Universitat Politècnica de Catalunya, Departament d'Empresa i Coneixement, Generalitat de Catalunya
Openalex Percentile: Top 12%
Statistical Methods in Clinical Trials
2.63
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