Evidence map›Paper›PMID 42505082›Full record

ArticleClinical trials (London, England)2026

Design and monitoring of randomized trials in vision research with binary endpoints.

Guoqing Diao, Qiang Zhang, Toshimitsu Hamasaki, Scott R Evans

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Guoqing DiaoDepartment of Biostatistics and Bioinformatics, The George Washington University, DC, USA.ORCID 0000-0001-7304-9591
Qiang ZhangVickie & Jack Farber Vision Research Center, Wills Eye Hospital, Philadelphia, PA, USA.
Toshimitsu HamasakiDepartment of Biostatistics and Bioinformatics, The George Washington University, DC, USA.
Scott R EvansDepartment of Biostatistics and Bioinformatics, The George Washington University, DC, USA.ORCID 0000-0003-3186-172X

Funding

Unified group sequential designs for clustered data (eye level) in randomized eye trialsR21EY032951 · NEI · GEORGE WASHINGTON UNIVERSITY · PI DIAO, GUOQING, ZHANG, QIANG · 2022 to 2023
$462k
NEI NIH HHS R21 EY032951
6 · The paper itself

Abstract

backgroundRandomized eye trials often involve both eyes if eligible from a patient. Few studies have investigated the design properties of randomized eye trials with binary endpoints, for instance, the sample size/power determination, leaving a significant gap in the literature. In addition, proper interim data-monitoring plans, which are essential for a successful design, are not available for eye trials with binary endpoints.

methodsWe propose a unified design for vision research with binary endpoints that accommodate all possible design options while accounting for correlations between the two eyes of the same patient. We derive closed-form formulas for the sample size and power calculations under the generalized linear mixed model framework. We also describe how to properly calculate the information fractions during interim monitoring, which is an essential component used to determine the efficacy/futility boundaries or calculate the alpha-spending function, as the standard technique may not apply.

resultsWe conduct extensive simulation studies to examine the performance of the proposed unified design for clustered binary data in randomized eye trials and compare it with the existing specific individual design. The simulation results demonstrate that the proposed methods perform well in practical settings. We provide an application to the Age-Related Eye Disease Study.

conclusionWe propose a unified design that accommodates all scenarios in eye trials with binary outcomes, including one-eye, paired, two-eye, mixture of one-eye and two-eye, and hybrid designs, and develop appropriate interim analysis plans. A proper study design and interim monitoring using the proposed methods in these studies can help study investigators make informed decisions.

Indexed as

alpha spendinggeneralized linear mixed modelinformation timesample size/power calculation

Identifiers

PMID42505082
PMCPMC13410960

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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.