Association of Opioid Use Disorder Treatment With Alcohol-Related Acute Events.

Importance: Persons with opioid use disorder (OUD) and co-occurring alcohol use disorder (AUD) are understudied and undertreated. It is unknown whether the use of medications to treat OUD is associated with reduced risk of alcohol-related morbidity. Objective: To determine whether the use of OUD medications is associated with decreased risk for alcohol-related falls, injuries, and poisonings in persons with OUD with and without co-occurring AUD. Design, Setting, and Participants: This recurrent-event, case-control, cohort study used prescription claims from IBM MarketScan insurance databases from January 1, 2006, to December 31, 2016. The sample included persons aged 12 to 64 years in the US with an OUD diagnosis and taking OUD medication who had at least 1 alcohol-related admission. The unit of observation was person-day. Data analysis was performed from June 26 through September 28, 2020. Exposures: Days of active OUD medication prescriptions, with either agonist (ie, buprenorphine or methadone) or antagonist (ie, oral or extended-release naltrexone) treatments compared with days without OUD prescriptions. Main Outcomes and Measures: The primary outcome was admission for any acute alcohol-related event defined by International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Conditional logistic regression was used to compare OUD medication use between days with and without an alcohol-related event. Stratified analyses were conducted between patients with OUD with and without a recent AUD diagnostic code. Results: There were 8 424 214 person-days of observation time among 13 335 participants who received OUD medications and experienced an alcohol-related admission (mean [SD] age, 33.1 [13.1] years; 5884 female participants [44.1%]). Agonist treatments (buprenorphine and methadone) were associated with reductions in the odds of any alcohol-related acute event compared with nontreatment days, with a 43% reduction for buprenorphine (odds ratio [OR], 0.57; 95% CI, 0.52-0.61) and a 66% reduction for methadone (OR, 0.34; 95% CI, 0.26-0.45). The antagonist treatment naltrexone was associated with reductions in alcohol-related acute events compared with nonmedication days, with a 37% reduction for extended-release naltrexone (OR, 0.63; 95% CI, 0.52-0.76) and a 16% reduction for oral naltrexone (OR, 0.84; 95% CI, 0.76-0.93). Naltrexone use was more prevalent among patients with OUD with recent AUD claims than their peers without AUD claims. Conclusions and Relevance: These findings suggest that OUD medication is associated with fewer admissions for alcohol-related acute events in patients with OUD with co-occurring AUD.

Magnetic Resonance Imaging-Defined Prostate-Specific Antigen Density Significantly Improves the Risk Prediction for Clinically Significant Prostate Cancer on Biopsy.

OBJECTIVE: To evaluate the predictive value of magnetic resonance imaging (MRI)-defined prostate-specific antigen (PSA) density and MRI interpretation for the detection of clinically significant prostate cancer (PCa). METHODS: We retrospectively reviewed our institutional database of men who received prostate MRI prior to biopsy at our institution between September 2014 and December 2016, excluding those on active surveillance (n = 372). Logistic regression models to predict clinically significant PCa on biopsy were developed using (1) MRI-defined PSA density; (2) PSA alone; and (3) the Prostate Cancer Prevention Trial (PCPT) risk calculator. Additional logistic regression models were then generated by combining the previous clinical variables with MRI interpretation (ie, prostate imaging reporting and data system [PI-RADS] classification): (1) MRI-defined PSA density + MRI interpretation; (2) PSA + MRI interpretation; and (3) PCPT + MRI interpretation. Receiving operator characteristic curves for each of the 6 models were generated, and the area under the curves (AUC) were compared. RESULTS: MRI-defined PSA density (AUCPSAD = 0.77) significantly outperformed the PSA (AUCPSA = 0.66, P < .01) and PCPT models (AUCPCPT = 0.70, P < .01). When combined with MRI interpretation (ie, PI-RADS classification), the MRI-defined PSA density model (AUCPSAD + MRI = 0.80) significantly outperformed the PSA (AUCPSA + MRI = 0.75, P < .01) and PCPT models (AUCPCPT + MRI = 0.76, P = .01). CONCLUSION: In addition to the PI-RADS classification, prebiopsy multiparametric magnetic resonance imaging also provides an accurate assessment of prostate volume. By utilizing this additional data to determine MRI-defined PSA density, we find that risk discrimination for clinically significant PCa on biopsy can be significantly improved.