{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T01:18:23Z","timestamp":1791422303387,"version":"4.3.3"},"reference-count":31,"publisher":"American Medical Association (AMA)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Psychiatry"],"published-print":{"date-parts":[[2024,1,1]]},"abstract":"<jats:sec id=\"ab-yoi230076-4\"><jats:title>Importance<\/jats:title><jats:p>No existing model allows clinicians to predict whether patients might return to opioid use in the early stages of treatment for opioid use disorder.<\/jats:p><\/jats:sec><jats:sec id=\"ab-yoi230076-5\"><jats:title>Objective<\/jats:title><jats:p>To develop an individual-level prediction tool for risk of return to use in opioid use disorder.<\/jats:p><\/jats:sec><jats:sec id=\"ab-yoi230076-6\"><jats:title>Design, Setting, and Participants<\/jats:title><jats:p>This decision analytical model used predictive modeling with individual-level data harmonized in June 1, 2019, to October 1, 2022, from 3 multicenter, pragmatic, randomized clinical trials of at least 12 weeks\u2019 duration within the National Institute on Drug Abuse Clinical Trials Network (CTN) performed between 2006 and 2016. The clinical trials covered a variety of treatment settings, including federally licensed treatment sites, physician practices, and inpatient treatment facilities. All 3 trials enrolled adult participants older than 18 years, with broad pragmatic inclusion and few exclusion criteria except for major medical and unstable psychiatric comorbidities.<\/jats:p><\/jats:sec><jats:sec id=\"ab-yoi230076-7\"><jats:title>Intervention<\/jats:title><jats:p>All participants received 1 of 3 medications for opioid use disorder: methadone, buprenorphine, or extended-release naltrexone.<\/jats:p><\/jats:sec><jats:sec id=\"ab-yoi230076-8\"><jats:title>Main Outcomes and Measures<\/jats:title><jats:p>Predictive models were developed for return to use, which was defined as 4 consecutive weeks of urine drug screen (UDS) results either missing or positive for nonprescribed opioids by week 12 of treatment.<\/jats:p><\/jats:sec><jats:sec id=\"ab-yoi230076-9\"><jats:title>Results<\/jats:title><jats:p>The overall sample included 2199 trial participants (mean [SD] age, 35.3 [10.7] years; 728 women [33.1%] and 1471 men [66.9%]). The final model based on 4 predictors at treatment entry (heroin use days, morphine- and cocaine-positive UDS results, and heroin injection in the past 30 days) yielded an area under the receiver operating characteristic curve (AUROC) of 0.67 (95% CI, 0.62-0.71). Adding UDS in the first 3 treatment weeks improved model performance (AUROC, 0.82; 95% CI, 0.78-0.85). A simplified score (CTN-0094 OUD Return-to-Use Risk Score) provided good clinical risk stratification wherein patients with weekly opioid-negative UDS results in the 3 weeks after treatment initiation had a 13% risk of return to use compared with 85% for those with 3 weeks of opioid-positive or missing UDS results (AUROC, 0.80; 95% CI, 0.76-0.84).<\/jats:p><\/jats:sec><jats:sec id=\"ab-yoi230076-10\"><jats:title>Conclusions and Relevance<\/jats:title><jats:p>The prediction model described in this study may be a universal risk measure for return to opioid use by treatment week 3. Interventions to prevent return to regular use should focus on this critical early treatment period.<\/jats:p><\/jats:sec>","DOI":"10.1001\/jamapsychiatry.2023.3596","type":"journal-article","created":{"date-parts":[[2023,10,4]],"date-time":"2023-10-04T15:01:14Z","timestamp":1696431674000},"page":"45","source":"Crossref","is-referenced-by-count":20,"title":["Individual-Level Risk Prediction of Return to Use During Opioid Use Disorder Treatment"],"prefix":"10.1001","volume":"81","author":[{"given":"Sean X.","family":"Luo","sequence":"first","affiliation":[{"name":"Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel J.","family":"Feaster","sequence":"additional","affiliation":[{"name":"Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, 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