Evidence map›Paper›PMID 41392386›Full record

ArticleAddiction (Abingdon, England)2026

Impact of study design decisions on identification of treatment initiators of medications for opioid use disorder.

Payel J Roy, Ryan Colvin, Katelin B Nickel, Rachael K Ross, Michael J Durkin, Katie J Suda, Andrew Atkinson, Anne M Butler

Abstract read
In one paragraph

Article in Addiction (Abingdon, England), 2026. 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
–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

1 citing paper in PubMed.

  1. 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

8 authors.

Payel J RoyDepartment of Medicine, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA.ORCID https://orcid.org/0000-0002-8177-2058
Ryan ColvinDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA.
Katelin B NickelDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA.
Rachael K RossDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.ORCID https://orcid.org/0000-0002-2049-6918
Michael J DurkinDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA.
Katie J SudaDepartment of Medicine, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Andrew AtkinsonDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA.
Anne M ButlerDepartment of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA.

Funding

WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8M
Comparative Risk of Oral Complications Associated with Medications for Opioid Use Disorder: A Mixed-Methods ApproachR01DE033322 · NIDCR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Anne Mobley Butler, Payel Jhoom Roy · 2023 to 2026
$2.5M
Oral Health Utilization and Outcomes Among Patients on Medications for Opioid Use DisorderR21DA057464 · NIDA · WASHINGTON UNIVERSITY · PI DURKIN, MICHAEL JOSEPH, ROY, PAYEL JHOOM · 2023 to 2024
$418k
NCATS NIH HHS UL1 TR002345NIDA NIH HHS R21DA057464NIDCR NIH HHS R01 DE033322NIDCR NIH HHS R01DE033322Washington University Institute of Clinical and Translational Sciences UL1 TR002345
6 · The paper itself

Abstract

BACKGROUND AND

aimsComparative effectiveness research studies commonly restrict cohorts to individuals who initiate a medication and do not have evidence of prior treatment. This is particularly challenging in research on medications for opioid use disorder (MOUD) because of sporadic use or intermittent adherence. We examined the impact of different lookback windows and washout criteria to identify MOUD initiator cohorts on sample size, cohort characteristics, and misclassification of treatment initiation. DESIGN AND

settingCohort study using the Merative™ MarketScan® Multi-State Medicaid Database (2011-2022).

participantsMedicaid-insured adults aged 18-64 with an MOUD prescription from 01/01/2022 to 12/31/2022 and a history of opioid use disorder (OUD) with at least 3 months of continuous enrollment. MEASUREMENTS: We created treatment initiator cohorts with increasingly restrictive lookback windows for inclusion (6-, 12-, 24-, 36-months, all-available). During each lookback window, we required [1] continuous enrollment; [2] continuous enrollment and OUD diagnosis; or [3] continuous enrollment, OUD diagnosis, and no prior treatment with MOUD. We defined prior treatment with MOUD as: (a) ≥ 30 days use (less restrictive definition; allowed for some prior treatment); or (b) ≥ 1 day use (more restrictive definition; did not allow prior treatment). We quantified changes in cohort sample size, demographic characteristics, and proportion of prevalent use episodes misclassified as MOUD treatment initiation (gold standard: 36-month lookback window).

findingsWe identified 103 794 eligible MOUD initiators (64.8% buprenorphine, 24.8% methadone, 10.4% naltrexone). Sample size of the cohorts decreased with increasingly restrictive lookback windows and washout criteria: [1] continuous enrollment (range, 96.9% for 6 months to 51.8% for 36 months); [2] continuous enrollment and less restrictive washout (range, 29.7% to 8.4%); and [3] continuous enrollment and more restrictive washout (range, 22.2% to 5.8%). All-available lookback performed similarly to a 12-month lookback. Longer lookback windows resulted in initiator cohorts with a greater proportion of individuals who were older, female, and of a minoritized race/ethnicity. The proportion of people with prevalent MOUD use misclassified as treatment initiation increased steadily with decreasing duration of lookback windows (24-, 12-, and 6-month); we observed misclassification among 16.1% to 49.2% of individuals (less restrictive washout), and 16.8% to 53.2% of individuals (more restrictive washout).

conclusionsThe choice of lookback window duration and washout criteria in research on medications for opioid use disorder (MOUD) presents tradeoffs between cohort sample size, demographic characteristics, and misclassification of treatment initiation. This study offers practical guidance for researchers planning to perform comparative studies in MOUD.

Indexed as

Narcotic AntagonistsOpiate Substitution TreatmentOpioid-Related DisordersResearch DesignAdolescentAdultBuprenorphineCohort StudiesComparative Effectiveness ResearchFemaleHumansMaleMedicaidMethadoneMiddle AgedNaltrexoneBuprenorphineMethadoneNaltrexoneNarcotic Antagonistsadministrative claimsepidemiologic methodsincident user designMedicaidmedications for opioid use disorderopioid use disorderpharmacoepidemiologystudy design

Identifiers

PMID41392386
PMCPMC13097994

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.