Evidence map›Paper›PMID 34702088›Full record

ArticleThe American journal of drug and alcohol abuse2021

The estimand framework and its application in substance use disorder clinical trials: a case study.

Jessica K Roydhouse, Lysbeth Floden, Rachel L Tomko, Kevin M Gray, Melanie L Bell

Open access · greenAbstract read
In one paragraph

Article in The American journal of drug and alcohol abuse, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 46% 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.

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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Trial
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

5 authors at 4 institutions in 2 countries.

Jessica K RoydhouseMenzies Institute for Medical Research, University of Tasmania, Hobart, Australia.ORCID 0000-0002-8025-5841
Lysbeth FlodenClinical Outcomes Solutions, Tucson, AZ, USA.
Rachel L TomkoDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA.
Kevin M GrayDepartment of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA.
Melanie L BellDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA.
Medical University of South Carolina · USHealth Outcomes Solutions (United States) · USThe University of Sydney · AUUniversity of Tasmania · AU

Funding

Southern Consortium Node of the Clinical Trials Network (Varenicline)UG1DA013727 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KATHLEEN T. BRADY, Kelly S. Barth · 2015 to 2026
$24.8M
Interdisciplinary Women's Health Research at MUSCK12HD055885 · NICHD · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI MCGINTY, JACQUELINE F. · 2007 to 2021
$7.2M
NICHD NIH HHS K12 HD055885NIDA NIH HHS UG1 DA013727
6 · The paper itself

Abstract

Relapse rates among individuals with substance use disorder (SUD) remain high and new treatment approaches are needed, which require evaluation in randomized controlled trials (RCTs). Measurement and interpretation challenges for SUD RCT data are often ignored or presented only in statistical analysis plans. Since different analytic approaches may result in different estimates and thus interpretations of the treatment effect, it is important to present this clearly throughout the trial. Inconsistencies between study analyses and objectives present further challenges for interpretation and cross-study comparisons. The recent International Council for Harmonization (ICH) addendum provides standardized language and a common framework for aligning trial objectives, design, conduct, and analysis. The framework focuses on estimands, which describe the treatment effect and link the trial objective with the scientific question and the analytic approach. The use of estimands offers SUD researchers and clinicians the opportunity to explicitly address events that affect measurement and interpretation at the outset of the trial. Furthermore, the use of standard terminology can lead to clearer interpretations of SUD trials and the treatments evaluated in SUD trials. Resources for understanding and applying estimands are needed to optimize the use of this new, helpful framework. This Perspective provides this resource for SUD researchers. Specifically, it highlights the relevance of estimands for SUD trials. Furthermore, it demonstrates how estimands can be used to develop clinically relevant analyses to address challenges in SUD trials. It also shows how a standardized framework can be employed to improve the interpretation and presentation of SUD study findings.

Indexed as

Randomized Controlled Trials as TopicSubstance-Related DisordersData Interpretation, StatisticalHumansResearch DesignefficacyEstimandSUDtrial

Identifiers

PMID34702088
PMCPMC10124131
OpenAlexW3209660238

What OpenQuestion holds

Textmetadata
LicenceTDM
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.