Individual-Level Risk Prediction of Return to Use During Opioid Use Disorder Treatment

被引:8
|
作者
Luo, Sean X. [1 ]
Feaster, Daniel J. [2 ]
Liu, Ying [1 ]
Balise, Raymond R. [2 ]
Hu, Mei-Chen [1 ]
Bouzoubaa, Layla [2 ]
Odom, Gabriel J. [3 ]
Brandt, Laura [4 ]
Pan, Yue [2 ]
Hser, Yih-Ing [5 ]
VanVeldhuisen, Paul [6 ]
Castillo, Felipe
Calderon, Anna R.
Rotrosen, John [7 ]
Saxon, Andrew J. [8 ]
Weiss, Roger D. [9 ]
Wall, Melanie [1 ]
Nunes, Edward V. [1 ]
机构
[1] Columbia Univ, Dept Psychiat, Vagelos Coll Phys & Surg, New York, NY USA
[2] Univ Miami, Dept Publ Hlth Sci, Miller Sch Med, Miami, FL USA
[3] Florida Int Univ, Dept Biostat, Stempel Coll Publ Hlth, Miami, FL USA
[4] CUNY City Coll, Dept Psychol, New York, NY USA
[5] Univ Calif Los Angeles, Semel Inst Neurosci & Human Behav, Dept Psychiat & Biobehav Sci, Los Angeles, CA USA
[6] Emmes Co LLC, Rockville, MD USA
[7] NYU, NYU Grossman Sch Med, Dept Psychiat, New York, NY USA
[8] Univ Washington, Dept Psychiat & Behav Sci, Seattle, WA USA
[9] Harvard Med Sch, Dept Psychiat, Belmont, MA USA
关键词
ENDOCRINE-DISRUPTING CHEMICALS; BISPHENOL-A; POSTNATAL DEPRESSION; PHTHALATE METABOLITES; PREGNANT-WOMEN; URINARY CONCENTRATIONS; MATERNAL-BEHAVIOR; EXPOSURE; HORMONES; HEALTH;
D O I
10.1001/jamapsychiatry.2023.3596
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
IMPORTANCE No existing model allows clinicians to predict whether patients might return to opioid use in the early stages of treatment for opioid use disorder. OBJECTIVE To develop an individual-level prediction tool for risk of return to use in opioid use disorder. DESIGN, SETTING, AND PARTICIPANTS 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' 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. INTERVENTION All participants received 1 of 3 medications for opioid use disorder: methadone, buprenorphine, or extended-release naltrexone. MAIN OUTCOMES AND MEASURES Predictive modelswere 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. RESULTS 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). CONCLUSIONS AND RELEVANCE 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.
引用
收藏
页码:45 / 56
页数:12
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