Evidence map›Paper›PMID 35129422›Full record

ArticleJournal of biopharmaceutical statistics2021

Calibrated dynamic borrowing using capping priors.

Sharon X Ling, Brian P Hobbs, Alexander M Kaizer, Joseph S Koopmeiners

Abstract read
In one paragraph

Article in Journal of biopharmaceutical statistics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

4 authors.

Sharon X LingDivision of Biostatistics, School of Public Health, University of Minnesota, United States.
Brian P HobbsDepartment of Population Health, Dell Medical School, the University of Texas at Austin, United States.
Alexander M KaizerDepartment of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, United States.
Joseph S KoopmeinersDivision of Biostatistics, School of Public Health, University of Minnesota, United States.

Funding

VERY LOW NICOTINE CIGARETTES IN SMOKERS WITH SCHIZOPHRENIAU54DA031659 · NIDA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI DONNY, ERIC CHRISTIAN, HATSUKAMI, DOROTHY K · 2011 to 2022
$64.7M
Innovative Statistical Methods for Evaluating the Impact of Tobacco Product StandardsR01DA046320 · NIDA · UNIVERSITY OF MINNESOTA · PI Joseph S. Koopmeiners, David M. Vock · 2018 to 2026
$2.4M
Statistical Methods and Adaptive Trial Designs for Cardiovascular Outcomes with Information SharingK01HL151754 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI KAIZER, ALEXANDER MARK · 2021 to 2025
$742k
NHLBI NIH HHS K01 HL151754NIDA NIH HHS R01 DA046320NIDA NIH HHS U54 DA031659
6 · The paper itself

Abstract

Multisource exchangeability models (MEMs), a BayeTsian approach for dynamically integrating information from multiple clinical trials, are a promising approach for gaining efficiency in randomized controlled trials. When the supplementary trials are considerably larger than the primary trial, care must be taken when integrating supplementary data to avoid overwhelming the primary trial. In this paper, we propose "capping priors," which controls the extent of dynamic borrowing by placing an

Indexed as

Research DesignBayes TheoremComputer SimulationHumansSample Sizecapping priorsMultisource exchangeability modelsprior specificationreduced nicotine content cigarettessupplementary data

Identifiers

PMID35129422
PMCPMC9940118

What OpenQuestion holds

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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.