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Drug and alcohol dependence

October 8, 2026 · via Europe PMC

Incidence of opioid use disorder among patients prescribed long-term opioid therapy: An observational study.

Yarborough BJH, Smith N, Stumbo SP, +14 more, Boudreau DM.

Journal ArticleAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

Among patients on long-term opioid therapy, 12-month incidence of at least moderate DSM-5 opioid use disorder ranged from 1.54% to 4.46%, depending on whether pain was adjusted for.

What was studied

A prospective observational cohort of 1952 patients in 10 health systems with one year of follow-up, using a structured interview (PRISM-5-OP) to measure pain-adjusted and unadjusted moderate to severe and any DSM-5 OUD involving prescription opioids.

Key findings

  • 12-month incidence of pain-adjusted moderate to severe OUD was 1.54%, and 4.46% without pain adjustment
  • Incidence of any OUD was 6.92% with pain adjustment and 18.14% without
  • Estimates were similar across age, sex and Medicaid status, and some were higher with past substance use or major depressive disorder

Clinical relevance

Gives concrete incidence figures to support shared decision-making and evaluate OUD prevention efforts for patients on long-term opioids.

Who should care

Psychiatry

Limitations

Participants were mostly older, White and in health systems, limiting generalisability; incidence depends heavily on how pain-related criteria are handled, and no confidence intervals are given in the abstract.

New OUD is uncommon but not rare in long-term opioid therapy, and estimates vary widely with the definition.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Background

There are no estimates of incident opioid use disorder (OUD), using current diagnostic criteria, among patients prescribed long-term opioid therapy (LtOT). The U.S. Food and Drug Administration issued a postmarketing requirement to estimate the 12-month incidence of OUD among patients receiving LtOT.

Methods

Study 3033-1 was a prospective, observational cohort study conducted in 10 health systems with one year of follow up. Data were collected August 2017 to October 2021, analyses were completed December 2025. The primary outcome was pain-adjusted, moderate to severe DSM-5 OUD involving prescription opioids measured using the Psychiatric Research Interview for Substance and Mental Disorders, adapted for assessing OUD among patients treated with opioids (PRISM-5-OP). Secondary outcomes included moderate to severe DSM-5 OUD without pain adjustment and any OUD involving prescription opioids with and without pain adjustment. Overall and stratified incidence were calculated.

Results

1952 participants were included; 76% were aged 50 + ; 58% were female, 80% were White. The 12-month incidence of the primary outcome was 1.54%, the outcome without pain adjustment resulted in an incidence of 4.46%. Incidence of any DSM-5 OUD involving prescription opioids was 6.92% with pain adjustment and 18.14% without pain adjustment. Incidence estimates were similar across age, sex, and Medicaid status. Some estimates were higher among those with past-year or prior to past-year substance use or major depressive disorders.

Conclusions

At one year, the incidence of at least moderate OUD ranged from 1.54% to 4.46%. These findings can inform clinician and patient shared decision-making and evaluations of OUD prevention efforts.

Trial registration

NCT02751762.

DOI

10.1016/j.drugalcdep.2026.113385

PMID

42879916

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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