ArticleStatistics in medicine2026
Exact Randomized Two-Stage Phase 2 Clinical Trial Designs for Two Binary Co-Primary Endpoints.
Article in Statistics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Exact Randomized Two-Stage Phase 2 Clinical Trial Designs for Two Binary Co-Primary Endpoints.Statistics in medicine · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Phase 2 clinical trials typically rely on a single primary endpoint, yet in many settings, treatment efficacy must be demonstrated across multiple co-primary endpoints. Such settings require intersection-union hypothesis testing, in which the global null hypothesis is rejected only when all individual component hypotheses are rejected. Existing phase 2 designs for binary endpoints are largely restricted to single-arm or single-endpoint settings, or rely on large-sample normal approximations for two-arm trials, which may be inadequate when sample sizes are small. We developed exact and simulation-based methods for designing two-arm, two-stage phase 2 trials with two co-primary binary endpoints using the bivariate binomial distribution, allowing different correlations between endpoints across treatment arms. The proposed framework identifies optimal designs that minimize the expected sample size and minimax designs that minimize the maximum sample size, while allowing early termination for futility at the first stage. For small sample sizes (approximately
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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.