Evidence map›Paper›PMID 27577191›Full record

ArticleTrials2016

A Bayesian comparative effectiveness trial in action: developing a platform for multisite study adaptive randomization.

Alexandra R Brown, Byron J Gajewski, Lauren S Aaronson, Dinesh Pal Mudaranthakam, Suzanne L Hunt, Scott M Berry, Melanie Quintana, Mamatha Pasnoor, Mazen M Dimachkie, Omar Jawdat and 2 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Trials, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02260388 (Patient Assisted Intervention for Neuropathy), which is not on this map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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.

NCT02260388 phase4completednot on this map

Patient Assisted Intervention for Neuropathy: Comparison of Treatment in Real Life Situations (PAIN-CONTRoLS)

TypeinterventionalSponsorUniversity of Kansas Medical CenterRan2014 to 2017Enrolled402ConditionsCryptogenic Sensory PolyneuropathyArmsNortriptyline, Duloxetine, Pregabalin, Mexiletine
3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 26 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Use of EpicClinical trials (London, England) · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. The Bayesian Design of Adaptive Clinical Trials.International journal of environmental research and public health · 2021
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

12 authors at 2 institutions in 1 country.

Alexandra R BrownDepartment of Biostatistics, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA. abrown8@kumc.edu.
Byron J GajewskiDepartment of Biostatistics, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA.
Lauren S AaronsonSchool of Nursing, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Dinesh Pal MudaranthakamDepartment of Biostatistics, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA.
Suzanne L HuntDepartment of Biostatistics, University of Kansas Medical Center, Mail Stop 1026, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA.
Scott M BerryBerry Consultants, 4301 Westbank Drive, Suite 140, Bldg B, Austin, TX, 78746, USA.
Melanie QuintanaBerry Consultants, 4301 Westbank Drive, Suite 140, Bldg B, Austin, TX, 78746, USA.
Mamatha PasnoorDepartment of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Mazen M DimachkieDepartment of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Omar JawdatDepartment of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Laura HerbelinDepartment of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
Richard J BarohnDepartment of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
University of Kansas Medical Center · USBerry & Associates (United States) · US

Funding

Heartland Institute for Clinical and Translational ResearchUL1TR000001 · NCATS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI BAROHN, RICHARD J. · 2012 to 2015
$13.0M
HEARTLAND INSTITUTE FOR CLINICAL AND TRANSLATIONAL RESEARCHUL1RR033179 · NCRR · UNIVERSITY OF KANSAS MEDICAL CENTER · PI BAROHN, RICHARD J. · 2011 to 2011
$3.2M
NCATS NIH HHS UL1 TR000001NCRR NIH HHS UL1 RR033179
6 · The paper itself

Abstract

backgroundIn the last few decades, the number of trials using Bayesian methods has grown rapidly. Publications prior to 1990 included only three clinical trials that used Bayesian methods, but that number quickly jumped to 19 in the 1990s and to 99 from 2000 to 2012. While this literature provides many examples of Bayesian Adaptive Designs (BAD), none of the papers that are available walks the reader through the detailed process of conducting a BAD. This paper fills that gap by describing the BAD process used for one comparative effectiveness trial (Patient Assisted Intervention for Neuropathy: Comparison of Treatment in Real Life Situations) that can be generalized for use by others. A BAD was chosen with efficiency in mind. Response-adaptive randomization allows the potential for substantially smaller sample sizes, and can provide faster conclusions about which treatment or treatments are most effective. An Internet-based electronic data capture tool, which features a randomization module, facilitated data capture across study sites and an in-house computation software program was developed to implement the response-adaptive randomization.

resultsA process for adapting randomization with minimal interruption to study sites was developed. A new randomization table can be generated quickly and can be seamlessly integrated in the data capture tool with minimal interruption to study sites.

conclusionThis manuscript is the first to detail the technical process used to evaluate a multisite comparative effectiveness trial using adaptive randomization. An important opportunity for the application of Bayesian trials is in comparative effectiveness trials. The specific case study presented in this paper can be used as a model for conducting future clinical trials using a combination of statistical software and a web-based application.

trial registrationClinicalTrials.gov Identifier: NCT02260388 , registered on 6 October 2014.

Indexed as

Bayes TheoremComparative Effectiveness ResearchResearch DesignAnalgesicsData CollectionEndpoint DeterminationHumansMulticenter Studies as TopicNervous System DiseasesRandomized Controlled Trials as TopicSample SizeSoftwareTime FactorsTreatment OutcomeAnalgesicsAdaptive randomizationBayesian adaptive designBayesian randomizationClinical trial conductData captureREDCapResponse-adaptive randomization

Identifiers

PMID27577191
PMCPMC5006258
OpenAlexW2511878324

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.