Evidence map›Paper›PMID 33042476›Full record

ArticleStatistics in biopharmaceutical research2020

Interim Monitoring for Futility in Clinical Trials with Two Co-primary Endpoints Using Prediction.

Koko Asakura, Scott R Evans, Toshimitsu Hamasaki

Abstract read
In one paragraph

Article in Statistics in biopharmaceutical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Article
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

3 authors.

Koko AsakuraDepartment of Data Science, National Cerebral and Cardiovascular Center, Osaka, Japan.
Scott R EvansThe Biostatistics Center and the Department of Biostatistics and Bioinformatics, George Washington University, Maryland, USA.
Toshimitsu HamasakiDepartment of Innovative Clinical Trials and Data Science, Osaka University Graduate School of Medicine, Osaka, Japan.

Funding

Antibacterial Resistance Leadership Group (ARLG)UM1AI104681 · NIAID · DUKE UNIVERSITY · PI Vance G. Fowler, Henry F HENRY CHAMBERS · 2013 to 2026
$180.8M
NIAID NIH HHS UM1 AI104681
6 · The paper itself

Abstract

We discuss using prediction as a flexible and practical approach for monitoring futility in clinical trials with two co-primary endpoints. This approach is appealing in that it provides quantitative evaluation of potential effect sizes and associated precision, and can be combined with flexible error-spending strategies. We extend prediction of effect size estimates and the construction of predicted intervals to the two co-primary endpoints case, and illustrate interim futility monitoring of treatment effects using prediction with an example. We also discuss alternative approaches based on the conditional and predictive powers, compare these methods and provide some guidance on the use of prediction for better decision in clinical trials with co-primary endpoints.

Indexed as

Conditional PowerGroup-sequential designsInterim analysesPredicted intervalsPredictive PowerType I error

Identifiers

PMID33042476
PMCPMC7539647

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

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.