ArticleStatistics in biosciences2026
Design of Trials with Composite Endpoints with the R Package CompAREdesign.
Article in Statistics in biosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Empirical Comparison of Win Ratio and Joint Frailty Models for Recurrent Event Endpoints With Applications in Oncology and Cardiology.Statistics in medicine · 2026Article
- Comparison of primary analysis strategies of randomized controlled trials with multiple endpoints with application to kidney transplantation.Scientific reports · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.