Evidence map›Paper›PMID 37926516›Full record

ArticleStatistics in medicine2023

Designing a phase-III time-to-event clinical trial using a modified sample size formula and Poisson-Gamma model for subject accrual that accounts for the lag in site initiation using the PERT distribution.

Virginia B Shipes, Caitlyn Meinzer, Bethany J Wolf, Hong Li, Mathew J Carpenter, Hooman Kamel, Renee H Martin

Abstract read
In one paragraph

Article in Statistics in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Virginia B ShipesDivision of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID 0000-0003-2104-6094
Caitlyn MeinzerDivision of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID 0000-0002-9905-4329
Bethany J WolfDivision of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID 0000-0002-7124-5158
Hong LiDivision of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA.
Mathew J CarpenterDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina, USA.
Hooman KamelDepartment of Neurology, Weill Cornell Medicine, New York City, New York, USA.
Renee H MartinDivision of Biostatistics, Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA.

Funding

NSTN National Clinical Coordinating CenterU01NS086872 · NINDS · UNIVERSITY OF CINCINNATI · PI Joseph Paul Broderick, Pooja Khatri · 2013 to 2026
$32.3M
AtRial Cardiopathy and Antithrombotic Drugs In prevention After cryptogenicstroke (ARCADIA)U01NS095869 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BRODERICK, JOSEPH PAUL, KAMEL, HOOMAN · 2017 to 2022
$22.0M
NINDS NIH HHS U01 NS086872NINDS NIH HHS U01 NS095869NINDS NIH HHS U01NS095869
6 · The paper itself

Abstract

A priori estimation of sample size and subject accrual in multi-site, time-to-event clinical trials is often challenging. Such trials are powered based on the number of events needed to detect a clinically significant difference. Sample size based on number of events relates to the expected duration of observation time for each subject. Temporal patterns in site initiation and subject enrollment ultimately affect when subjects can be accrued into the study. Lag times are common as the site start-up process optimizes, resulting in delays that may curtail observational follow-up and therefore undermine power. The proposed method introduces a Program Evaluation and Review Technique (PERT) model into the sample size estimation which accounts for the lag in site start-up. Additionally, a PERT model is introduced into a Poisson-Gamma subject accrual model to predict the quantity of study sites needed. The introduction of the PERT model provides greater flexibility in both a priori power assessment and planning the number of sites, as it specifically allows for the inclusion of anticipated delays in site start-up time. This model results in minimal power loss even when PERT distribution inputs are misspecified compared to the traditional assumption of simultaneous start-up for all sites. Together these updated formulations for sample size and subject accrual models offer an improved method for designing a multi-site time-to-event clinical trial that accounts for a flexible site start-up process.

Indexed as

Sample SizeHumansProgram EvaluationTime Factorsclinical trialsPERTsample sizesubject accrual modelstime-to-event

Identifiers

PMID37926516
PMCPMC10847961

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Registered trials

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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.