Empirically contrasting urine drug screening-based opioid use disorder treatment outcome definitions.

BACKGROUND AND AIMS: A lack of consensus on the optimal outcome measures to assess opioid use disorder (OUD) treatment efficacy and their precise definition and computation has hampered the pooling of research data for evidence synthesis and meta-analyses. This study aimed to empirically contrast multiple clinical trial definitions of treatment success by applying them to the same dataset. METHODS: Data analysis used a suite of functions, developed as a software package for the R language, to operationalize 61 treatment outcome definitions based on urine drug screening (UDS) results. Outcome definitions were derived from clinical trials that are among the most influential in the OUD treatment field. Outcome functions were applied to a harmonized dataset from three large-scale National Drug Abuse Treatment Clinical Trials Network (CTN) studies, which tested various medication for OUD (MOUD) options (n = 2492). Hierarchical clustering was employed to empirically contrast outcome definitions. RESULTS: The optimal number of clusters identified was three. Cluster 1, comprising eight definitions focused on detecting opioid-positive UDS, did not include missing UDS in outcome calculations, potentially resulting in inflated rates of treatment success. Cluster 2, with the highest variability, included 10 definitions characterized by strict criteria for treatment success, relying heavily on UDS results from either a brief period or a single study visit. The 43 definitions in Cluster 3 represented a diverse range of outcomes, conceptualized as measuring abstinence, use reduction and relapse. These definitions potentially offer more balanced measures of treatment success or failure, as they avoid the extreme methodologies characteristic of Clusters 1 and 2. CONCLUSIONS: Clinical trials using urine drug screening (UDS) for objective substance use assessment in outcome definitions should consider (1) incorporating missing UDS data in outcome computation and (2) avoiding over-reliance on UDS data confined to a short time frame or the occurrence of a single positive urine test following a period of abstinence.

Disadvantaged groups have greater spatial access to pharmacies in New York state.

BACKGROUND: The accessibility of pharmacies has been associated with overall health and wellbeing. Past studies have suggested that low income and racial minority communities are underserved by pharmacies. However, the literature is inconsistent in finding links between area-level income or racial and ethnic composition and access to pharmacies. Here we aim to assess area-level spatial access to pharmacies across New York State (NYS), hypothesizing that Census Tracts with higher poverty rates and higher percentages of Black and Hispanic residents would have lower spatial access. METHODS: The population weighted mean shortest road network distance (PWMSD) to a pharmacy in 2018 was calculated for each Census Tract in NYS. This statistic was calculated from the shortest road network distance to a pharmacy from the centroid of each Census block within a tract, with the mean across census blocks weighted by the population of the census block. Cross-sectional analyses were conducted to assess links between Tract-level socio demographic characteristics and Tract-level PWMSD to a pharmacy. RESULTS: Overall the mean PWMSD to a pharmacy across Census tracts in NYS was 2.07 Km (SD = 3.35, median 0.85 Km). Shorter PWMSD to a pharmacy were associated with higher Tract-level % poverty, % Black/African American (AA) residents, and % Hispanic/Latino residents and with lower Tract-level % of residents with a college degree. Compared to tracts in the lowest quartile of % Black/AA residents, tracts in the highest quartile had a 70.7% (95% CI 68.3-72.9%) shorter PWMSD to a pharmacy. Similarly, tracts in the highest quartile of % poverty had a 61.3% (95% CI 58.0-64.4%) shorter PWMSD to a pharmacy than tracts in the lowest quartile. CONCLUSION: The analyses show that tracts in NYS with higher racial and ethnic minority populations and higher poverty rates have higher spatial access to pharmacies.

Impact of the Communities That HEAL Intervention on Buprenorphine-Waivered Practitioners and Buprenorphine Prescribing: A Prespecified Secondary Analysis of the HCS Randomized Clinical Trial.

Importance: Buprenorphine significantly reduces opioid-related overdose mortality. From 2002 to 2022, the Drug Addiction Treatment Act of 2000 (DATA 2000) required qualified practitioners to receive a waiver from the Drug Enforcement Agency to prescribe buprenorphine for treatment of opioid use disorder. During this period, waiver uptake among practitioners was modest; subsequent changes need to be examined. Objective: To determine whether the Communities That HEAL (CTH) intervention increased the rate of practitioners with DATA 2000 waivers and buprenorphine prescribing. Design, Setting, and Participants: This prespecified secondary analysis of the HEALing Communities Study, a multisite, 2-arm, parallel, community-level, cluster randomized, open, wait-list-controlled comparison clinical trial was designed to assess the effectiveness of the CTH intervention and was conducted between January 1, 2020, to December 31, 2023, in 67 communities in Kentucky, Massachusetts, New York, and Ohio, accounting for approximately 8.2 million adults. The participants in this trial were communities consisting of counties (n = 48) and municipalities (n = 19). Trial arm randomization was conducted using a covariate constrained randomization procedure stratified by state. Each state was balanced by community characteristics including urban/rural classification, fatal opioid overdose rate, and community population. Thirty-four communities were randomized to the intervention and 33 to wait-list control arms. Data analysis was conducted between March 20 and September 29, 2023, with a focus on the comparison period from July 1, 2021, to June 30, 2022. Intervention: Waiver trainings and other educational trainings were offered or supported by the HEALing Communities Study research sites in each state to help build practitioner capacity. Main Outcomes and Measures: The rate of practitioners with a DATA 2000 waiver (overall, and stratified by 30-, 100-, and 275-patient limits) per 100 000 adult residents aged 18 years or older during July 1, 2021, to June 30, 2022, were compared between the intervention and wait-list control communities. The rate of buprenorphine prescribing among those waivered practitioners was also compared between the intervention and wait-list control communities. Intention-to-treat and per-protocol analyses were performed. Results: A total of 8 166 963 individuals aged 18 years or older were residents of the 67 communities studied. There was no evidence of an effect of the CTH intervention on the adjusted rate of practitioners with a DATA 2000 waiver (adjusted relative rate [ARR], 1.04; 95% CI, 0.94-1.14) or the adjusted rate of practitioners with a DATA 2000 waiver who actively prescribed buprenorphine (ARR, 0.97; 95% CI, 0.86-1.10). Conclusions and Relevance: In this randomized clinical trial, the CTH intervention was not associated with increases in the rate of practitioners with a DATA 2000 waiver or buprenorphine prescribing among those waivered practitioners. Supporting practitioners to prescribe buprenorphine remains a critical yet challenging step in the continuum of care to treat opioid use disorder. Trial Registration: ClinicalTrials.gov Identifier: NCT04111939.

PrEP and Behavioral Health Treatment Referral Among HIV Test Counselors in Miami-Dade County: A Rapid Qualitative Study Using the Consolidated Framework for Implementation Research.

HIV test counselors are well positioned to refer individuals to pre-exposure prophylaxis (PrEP) and behavioral health treatments. HIV test counselors in Miami-Dade County (N = 20), a priority jurisdiction for Ending the HIV Epidemic, completed interviews to assess determinants of PrEP and behavioral health treatment referrals. To identify determinants, we used a rapid deductive qualitative analysis approach and the Consolidated Framework for Implementation Research (CFIR). Identified determinants sometimes served as facilitators (e.g., relative priority, leadership importance) and sometimes as barriers (e.g., lack of access to knowledge and information, available resources for referrals) to making referrals. We also observed differences in determinants between PrEP and behavioral health referrals. For example, complexity (perceived difficulty of the referral) was a barrier to behavioral health more often than PrEP referral. Our findings suggest that determinants across many CFIR domains affect referral implementation, and the corresponding need for multiple implementation strategies to improve implementation of PrEP and behavioral health referrals in the context of HIV testing.

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

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 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. 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.

Predictors of outcomes in patients with obesity following mitral valve surgery.

Objective: Few studies have assessed the outcomes of mitral valve surgery in patients with obesity. We sought to study factors that determine the in-hospital outcomes of this population to help clinicians provide optimal care. Methods: A retrospective analysis of adult patients with obesity who underwent open mitral valve replacement or repair between January 1, 2012, and December 31, 2020, was conducted using the National Inpatient Sample. Weighted logistic regression and random forest analyses were performed to assess factors associated with mortality and the interaction of each variable. Results: Of the 48,775 patients with obesity, 34% had morbid obesity (body mass index ≥40), 55% were women, 66% underwent elective surgery, and 55% received isolated open mitral valve replacement or repair. In-hospital mortality was 5.0% (n = 2430). After adjusting for important covariates, a greater risk of mortality was associated with older patients (adjusted odds ratio [aOR], 1.24; 95% CI, 1.08-1.43), higher Elixhauser comorbidity score (aOR, 2.10; 95% CI, 1.87-2.36), prior valve surgery (aOR, 1.63; 95% CI, 1.01-2.63), and more than 2 concomitant procedures (aOR, 2.83; 95% CI, 2.07-3.85). Lower mortality was associated with elective admissions (aOR, 0.70; 95% CI, 0.56-0.87) and valve repair (aOR, 0.58; 95% CI, 0.46-0.73). Machine learning identified several interactions associated with early mortality, such as Elixhauser score, female sex, body mass index ≥40, and kidney failure. Conclusions: The complexity of presentation, comorbidities in older and female patients, and morbid obesity are independently associated with an increased risk of mortality in patients undergoing open mitral valve replacement or repair. Morbid obesity and sex disparity should be recognized in this population, and physicians should consider older patients and females with multiple comorbidities for earlier and more opportune treatment windows.

Capturing drug use patterns at a glance: An n-ary word sufficient statistic for repeated univariate categorical values.

INTRODUCTION: The efficacy of treatments for substance use disorders (SUD) is tested in clinical trials in which participants typically provide urine samples to detect whether the person has used certain substances via urine drug screenings (UDS). UDS data form the foundation of treatment outcome assessment in the vast majority of SUD clinical trials. However, existing methods to calculate treatment outcomes are not standardized, impeding comparability between studies and prohibiting reproducibility of results. METHODS: We extended the concept of a binary UDS variable to multiple categories: "+" [positive for substance(s) of interest], "-" [negative for substance(s)], "o" [patient failed to provide sample], "*" [inconclusive or mixed results], and "_" [no specimens required per study design]. This construct can be used to create a standardized and sufficient representation of UDS datastreams and sufficiently collapses longitudinal records into a single, compact "word", which preserves all information contained in the original data. RESULTS: We developed the R software package CTNote (available on CRAN) as a tool to enable computers to parse these "words". The software package contains five groups of routines: detect a substance use pattern, account for a specific trial protocol, handle missing UDS data, measure the longest period of consecutive behavior, and count substance use events. Executing permutations of these routines result in algorithms which can define SUD clinical trial endpoints. As examples, we provide three algorithms to define primary endpoints from seminal SUD clinical trials. DISCUSSION: Representing substance use patterns as a "word" allows researchers and clinicians an "at a glance" assessment of participants' responses to treatment over time. Further, machine readable use pattern summaries are a standardized method to calculate treatment outcomes and are therefore useful to all future SUD clinical trials. We discuss some caveats when applying this data summarization technique in practice and areas of future study.

Hyperlocal disparities in breast, cervical, and colorectal cancer screening: An ecological study of social vulnerability in Miami-Dade county.

Neighborhoods have been identified as important determinants of health-related outcomes, but limited research has assessed the influence of neighborhood context along the cancer continuum. This study used census tract-level data from the United States Census Bureau and Centers for Disease Control and Prevention to characterize Miami-Dade County census tracts (n = 492) into social vulnerability clusters and assess their associated breast, cervical, and colorectal cancer screening participation rates. We identified disparities by social vulnerability cluster in cancer screening participation rates. Further investigation of geographic disparities in social vulnerability and cancer screening participation could inform equity-focused cancer control efforts.

Risks of returning to opioid use at treatment entry and early in opioid use disorder treatment: Role of non-opioid substances.

OBJECTIVE: Patients in treatment with medications for opioid use disorder (MOUD) often report use of other substances in addition to opioids. Few studies exist that examine the relationship between use at treatment entry and early non-opioid use in opioid treatment outcome. METHODOLOGY: We combined and harmonized three randomized, controlled MOUD clinical trials from the National Institutes of Drug Abuse (NIDA) Clinical Trials Network (CTN) (N=2197) and investigated the association of non-opioid substance use at treatment entry and during early treatment with a return to opioid use. The trials compared MOUD treatment (buprenorphine, methadone, extended-release naltrexone) in populations with opioid use disorder (OUD). Non-opioid substances were identified through harmonizing self-reported use. The primary outcomes were markers of return to opioid use by 12 weeks. RESULTS: When treatment cohorts were adjusted, no association between self-reported treatment entry use of non-opioid substances and week-12 opioid use was detected. During the first month of treatment, higher use of cocaine (OR 1.41 [1.18-1.69]) and amphetamine (OR 1.70 [1.27-2.26]) was found to be associated with higher likelihood of illicit opioid use by week 12. Exploratory analyses of potential treatment cohort-by-predictor interactions showed that those with heavier cocaine use had a lower rate of returning to opioid use in the extended-release naltrexone group than in the methadone group. CONCLUSION: Substance use other than opioids at treatment entry is not associated with relapse. Use of cocaine or amphetamines during the first few weeks of MOUD treatment may signal a worse outcome, suggesting a need for additional interventions.

Identifying Neighborhoods with Cervical Cancer Disparities for Targeted Community Outreach and Engagement by an NCI-Designated Cancer Center: A Geospatial Approach.

BACKGROUND: Cervical cancer disparities exist in the United States with the highest incidence in Hispanic women and the highest mortality in Black women. Effective control of cervical cancer in the population requires targeted interventions tailored to community composition in terms of race, ethnicity, and social determinants of health (SDOH). METHODS: Using cancer registry and SDOH data, geospatial hot spot analyses were carried out to identify statistically significant neighborhood clusters with high numbers of cervical cancer cases within the catchment area of an NCI-Designated Cancer Center. The locations, racial and ethnic composition, and SDOH resources of these hot spots were used by the center's community outreach and engagement office to deploy mobile screening units (MSU) for intervention in communities with women facing heightened risk for cervical cancer. RESULTS: Neighborhood hot spots with high numbers of cervical cancer cases in south Florida largely overlap with locations of poverty. Cervical cancer hot spots are associated with a high percentage of Hispanic cases and low SDOH status, including low income, housing tenure, and education attainment. CONCLUSIONS: A geospatially referenced cancer surveillance platform integrating cancer registry, SDOH, and cervical screening data can effectively identify targets for cervical cancer intervention in neighborhoods experiencing disparities. IMPACT: Guided with a data-driven surveillance system, MSUs proactively bringing prevention education and cervical screening to communities with more unscreened, at-risk women are an effective means for addressing disparities associated with cervical cancer control.

Stimulant use, HIV, and immune dysregulation among sexual minority men.

BACKGROUND: Sexual minority men (SMM) report high rates of stimulant use (e.g., crystal methamphetamine, cocaine) and HIV infection. Stimulant use contributes to immune dysfunction, which enhances risk for HIV acquisition and pathogenesis. Research is needed to examine the independent and interactive relationships of stimulant use and HIV infection with systemic immune dysregulation among SMM, especially during the COVID-19 pandemic. METHODS: From 2020-2022, 75 SMM in Miami, Florida with and without HIV completed an online survey and provided biospecimens to assess HIV status and viral load (VL), recent stimulant use, and soluble markers of immune activation and inflammation in plasma, including soluble CD14 (sCD14) and elevated high-sensitivity C-reactive protein (hs-CRP > 1.0mg/L). Sociodemographics and prior SARS-CoV-2 infection were compared across HIV status/stimulant use groups. Moderation models examined the independent and interactive associations of stimulant use and HIV status with sCD14 and elevated hs-CRP. RESULTS: Thirty participants were persons living with HIV (PWH) (50% with stimulant use), and 45 were HIV-negative (44% with stimulant use). SARS-CoV-2 infection was not associated with stimulant use/HIV groups or immune outcomes. HIV-negative SMM without stimulant use had lower sCD14 compared to other SMM, as well as lower odds of elevated hs-CRP compared to PWH who used stimulants. Stimulant use showed independent associations with immune dysregulation that persisted after controlling for HIV status and VL, whereas HIV status was only independently associated with elevated hs-CRP in one model not controlling for VL. CONCLUSIONS: Among SMM, stimulant use was independently associated with elevated immune activation and inflammation.

Comorbidity burden and health-related quality of life in men with advanced prostate cancer.

PURPOSE: Identifying clinically relevant comorbidities and their effect on health-related quality of life (HRQoL) outcomes among men with advanced prostate cancer (APC) can inform patient care and improve outcomes; however, this is poorly understood. The aim of this observational study was to examine the prevalence of comorbidities, and the relationship of comorbidity burden to HRQoL and other patient-reported outcomes (PROs) among men with APC. METHODS: Participants were 192 men (average age 68.8) with APC (stage III or IV) who completed a psychosocial battery including measures of sociodemographic factors, HRQoL and other PROs, and the Charlson Comorbidity Index (CCI). Hierarchical multiple regression analysis was used to examine the relationships between CCI, HRQOL, and PROs. RESULTS: The vast majority (82%) of participants had at least one comorbidity, with the most common being: hypertension (59%), connective tissue disease or arthritis (31%), diabetes (24%), and problems with kidneys, vision, or another organ (24%). After controlling for covariates, regressions showed that a higher CCI score was significantly associated with worse HRQoL (p < 0.001), lower levels of positive affect (p < 0.05), and higher levels of depression (p < 0.05), fatigue (p < 0.001), pain (p < 0.01), stress (p < 0.01), and cancer-specific distress (p < 0.05). CONCLUSIONS: Comorbidities were common among men with APC, and a greater CCI score was associated with detriments in several domains of HRQoL and other PROs. Our findings show the need to address comorbidities in the presence of a cancer diagnosis and subsequent treatment. TRIAL REGISTRATION CLINICALTRIALS. GOV IDENTIFIER: NCT03149185.

Risk of Experiencing an Overdose Event for Patients Undergoing Treatment With Medication for Opioid Use Disorder.

OBJECTIVE: Overdose risk during a course of treatment with medication for opioid use disorder (MOUD) has not been clearly delineated. The authors sought to address this gap by leveraging a new data set from three large pragmatic clinical trials of MOUD. METHODS: Adverse event logs, including overdose events, from the three trials (N=2,199) were harmonized, and the overall risk of having an overdose event in the 24 weeks after randomization was compared for each study arm (one methadone, one naltrexone, and three buprenorphine groups), using survival analysis with time-dependent Cox proportional hazard models. RESULTS: By week 24, 39 participants had ≥1 overdose event. The observed frequency of having an overdose event was 15 (5.30%) among 283 patients assigned to naltrexone, eight (1.51%) among 529 patients assigned to methadone, and 16 (1.15%) among 1,387 patients assigned to buprenorphine. Notably, 27.9% of patients assigned to extended-release naltrexone never initiated the medication, and their overdose rate was 8.9% (7/79), compared with 3.9% (8/204) among those who initiated naltrexone. Controlling for sociodemographic and time-varying medication adherence variables and baseline substance use, a proportional hazard model did not show a significant effect of naltrexone assignment. Significantly higher probabilities of experiencing an overdose event were observed among patients with baseline benzodiazepine use (hazard ratio=3.36, 95% CI=1.76, 6.42) and those who either were never inducted on their assigned study medication (hazard ratio=6.64, 95% CI=2.12, 19.54) or stopped their medication after initial induction (hazard ratio=4.04, 95% CI=1.54, 10.65). CONCLUSIONS: Among patients with opioid use disorder seeking medication treatment, the risk of overdose events over the next 24 weeks is elevated among those who fail to initiate or discontinue medication and those who report benzodiazepine use at baseline.

Comorbidity burden and health-related quality of life in men with advanced prostate cancer.

Purpose: Identifying clinically relevant comorbidities and their effect on health-related quality of life (HRQoL) outcomes among men with advanced prostate cancer (APC) can inform patient care and improve outcomes; however, this is poorly understood. The aim of this observational study was to examine the prevalence of comorbidities, and the relationship of comorbidity burden to HRQoL and other patient-reported outcomes (PROs) among men with APC. Methods: Participants were 192 men (average age 68.8) with APC (stage III or IV) who completed a psychosocial battery including measures of sociodemographic factors, HRQoL and other PROs, and the Charlson Comorbidity Index (CCI). Hierarchical multiple regression analysis was used to examine the relationships between CCI, HRQOL, and PROs. Results: The vast majority (82%) of participants had at least one comorbidity, with the most common being: hypertension (59%), connective tissue disease or arthritis (31%), diabetes (24%), and problems with kidneys, vision, or another organ (24%). After controlling for covariates, regressions showed that a higher CCI score was significantly associated with worse HRQoL ( p < 0.001), lower levels of positive affect ( p < 0.05), and higher levels of depression ( p < 0.05), fatigue ( p < 0.001), pain ( p < 0.01), stress ( p < 0.01), and cancer-specific distress ( p < 0.05). Conclusions: Comorbidities were common among men with APC, and a greater CCI score was associated with detriments in several domains of HRQoL and other PROs. Our findings show the need to address comorbidities in the presence of a cancer diagnosis and subsequent treatment.

Impacts of the New York State COVID-19 disaster emergency orders on prescription dispensing for opioids and medication for opioid use disorder.

AIMS: The aim of this study is to examine whether the March 2020 New York State (NYS) SARS-CoV-2 emergency orders were associated with an initial surge in opioid dispensing and a longer-term reduction in access to medications for opioid use disorder (MOUD). DESIGN: Time-series analyses of the dispensing of non-MOUD opioid and MOUD prescriptions using IQVIA's longitudinal prescription claims database (n = 16 087 429) in NYS by week, from 1 January 2018 to 31 July 2020. IQVIA is a multi-national company that provides biopharmaceutical development and commercial outsourcing services. SETTING AND PARTICIPANTS: NYS Zone Improvement Plan (ZIP) codes (n = 1218) in which prescriptions were dispensed. MEASUREMENT: For each ZIP code, for each week, the following dispensing measures were calculated: total weekly morphine milligram equivalents/day (MME/day), total weekly MME/day dispensed via prescriptions for ≤ 7 days and the count of MOUD prescriptions dispensed. Differences in dispensing metrics, comparing each week in 2020 with corresponding weeks in 2019, were calculated for each ZIP code. RESULTS: During the study period, weekly MME/day per ZIP code of dispensed non-MOUD opioids steadily declined. Compared with the difference in dispensing between 2019 and 2020 during the first week in 2020, there was a significantly larger drop in dispensed weekly total MME/day beginning 21 March 2020, and lasting until the week of 17 April (P < 0.05 for each week). Mean weekly total MME/day dispensed from 21 March to 17 April 2020 was 17.07% lower [95% confidence interval (CI) = 13.97%, 20.17%] than in the 4 weeks before 21 March almost entirely due to a drop in MME/day dispensed for prescriptions of ≤ 7 days. There was not a discernable drop in MOUD dispensing associated with the period of the emergency orders. CONCLUSIONS: New York State emergency orders in March 2020 to reduce SARS-CoV-2 transmission and preserve hospital capacity appeared to be associated with a decline in dispensing of opioids not used as MOUD. Access to MOUD appeared to be unaffected by the orders, probably because of policy initiatives by the Substance Abuse and Mental Health Services Administration.

Factors associated with latino sexual minority men's likelihood and motivation for obtaining a COVID-19 vaccine: a mixed-methods study.

Minoritized communities are underreached by biomedical interventions, such as the COVID-19 vaccine. This mixed-methods study identified factors associated with vaccine likelihood (VL) and uptake (VU) among 187 Latino sexual minority men (LSMM) in South Florida. Regression models with LASSO variable selection and Classification and Regression Trees (CART) assessed determinants of VL and VU while open-ended questions were evaluated using thematic content analysis. VL (range 1-7; M = 6.00, SD = 1.84) and VU (63.6%) was high. LASSO modeling identified being insured, worrying about others, fear of transmitting COVID-19, and financial stress as the most influential factors for VL; working remotely from home was important for VU. Time (weeks) since addition of COVID-19 vaccination-related questions (December 2nd, 2020) was associated with both outcomes across both modeling techniques. Convergence between data suggests capitalizing on altruistic motivations and improving accessibility to vaccine campaigns are valuable assets to increase LSMM's vaccine confidence.

Impact of COVID-19 on HIV service delivery in Miami-Dade County: a mixed methods study.

BACKGROUND: Facilitating access to HIV prevention and treatment is imperative in Miami-Dade County (MDC), a U.S. HIV epicenter. With COVID-19, disruptions to these services have occurred, leading HIV organizations to innovate and demonstrate resilience. This study documented COVID-19 related disruptions and resilient innovations in HIV services within MDC. METHODS: This mixed methods cross-sectional study included HIV test counselors in MDC. In the quantitative component (N=106), participants reported COVID-19 impacts on HIV service delivery. Data visualization examined patterns within organizations and throughout the study period. Generalized estimating equation modeling examined differences in service disruptions and innovations. In the qualitative component, participants (N=20) completed interviews regarding COVID-19 impacts on HIV services. Rapid qualitative analysis was employed to analyze interviews. RESULTS: Quantitative data showed that innovations generally matched or outpaced disruptions, demonstrating resilience on HIV service delivery during COVID-19. HIV testing (36%, 95%CI[28%, 46%]) and STI testing (42%, 95%CI[33%, 52%]) were most likely to be disrupted. Sexual/reproductive health (45%, 95%CI[35%, 55%]), HIV testing (57%, 95%CI[47%,66%]), HIV case management (51%, 95%CI[41%, 60%]), PrEP initiation (47%, 95%CI[37%,57%]), and STI testing (47%, 95%CI[37%, 57%]) were most likely to be innovated. Qualitative analysis revealed three orthogonal themes related to 1) disruptions (with five sub-components), 2) resilient innovations (with four sub-components), and 3) emerging and ongoing health disparities. CONCLUSIONS: HIV organizations faced service disruptions during COVID-19 while also meaningfully innovating. Our findings point to potential changes in policy and practice that could be maintained beyond the immediate impacts of COVID-19 to enhance the resilience of HIV services. Aligning with the US Ending the HIV Epidemic Plan and the National Strategy for HIV/AIDS, capitalizing on the observed innovations would facilitate improved HIV-related health services for people living in MDC and beyond.

Perceptions of Practitioner Support for Patient Autonomy are Associated with Delayed Health Care Seeking among Haitian Immigrant Women in South Florida.

Few empirical studies have evaluated how perceptions of the patient-provider relationship affect health care seeking among Haitian immigrants. In this cross-sectional study, we examined whether perceptions of practitioner support for patient autonomy facilitate or hinder health care seeking among Haitian women enrolled in a cervical self-sampling trial. Perceived autonomy support was measured using an adapted health care climate questionnaire. Associations between perceived autonomy support and health care seeking were modeled using logistic regression and classification and regression trees. Covariates included socioeconomic and structural access indicators. Dependent variables included receipt of any medical care in the past year and delayed health care seeking. Having a usual source of care was strongly associated with both dependent variables. Lower perceived autonomy support was associated with delayed health care seeking in regression models and classification and regression trees. Addressing the capacity of health workers to deliver autonomy-supportive care is essential for improving health services utilization in vulnerable populations.

Structural Racism and Breast Cancer-specific Survival: Impact of Economic and Racial Residential Segregation.

OBJECTIVE: To analyze the effect of economic and racial/ethnic residential segregation on breast cancer-specific survival (BCSS) in South Florida, a diverse metropolitan area that mirrors the projected demographics of many United States regions. SUMMARY BACKGROUND DATA: Despite advances in diagnosis and treatment, racial and economic disparities in BCSS. This study evaluates these disparities through the lens of racial and economic residential segregation, which approximate the impact of structural racism. METHODS: Retrospective cohort study of stage I to IV breast cancer patients treated at our institution from 2005 to 2017. Our exposures include index of concentration at the extremes, a measurement of economic and racial neighborhood segregation, which was computed at the census-tract level using American Community Survey data. The primary outcome was BCSS. RESULTS: Random effects frailty models predicted that patients living in low-income neighborhoods had higher mortality compared to those living in high-income neighborhoods [hazard ratios (HR): 1.56, 95% confidence interval (CI): 1.23-2.00]. Patients living in low-income non-Hispanic Black and Hispanic neighborhoods had higher mortality compared to those living in high-income non-Hispanic White (NHW) neighborhoods (HR: 2.43, 95%CI: 1.72, 3.43) and (HR: 1.99, 95%CI: 1.39, 2.84), after controlling for patient characteristics, respectively. In adjusted race-stratified analysis, NHWs living in low-income non-Hispanic Black neighborhoods had higher mortality compared to NHWs living in high-income NHW neighborhoods (HR: 4.09, 95%CI: 2.34-7.06). CONCLUSIONS: Extreme racial/ethnic and economic segregation were associated with lower BCSS. We add novel insight regarding NHW and Hispanics to a growing body of literature that demonstrate how the ecological effects of structural racism-expressed through poverty and residential segregation-shape cancer survival.

Specific polysubstance use patterns predict relapse among patients entering opioid use disorder treatment.

Introduction: While polysubstance use has consistently been associated with higher rates of relapse, few studies have examined subgroups with specific combinations and time course of polysubstance use (i.e., polysubstance use patterns). This study aimed to classify and compare polysubstance use patterns, and their associations with relapse to regular opioid use in 2637 participants in three large opioid use disorder (OUD) treatment trials. Methods: We explored the daily patterns of self-reported substance use in the 28 days prior to treatment entry. Market basket analysis (MBA) and repeated measure latent class analysis (RMLCA) were used to examine the subgroups of polysubstance use patterns, and multiple logistic regression was used to examine associations between identified classes and relapse. Results: MBA and RMLCA identified 34 "associations rules " and 6 classes, respectively. Specific combinations of polysubstance use and time course (high baseline use and rapid decrease of use prior to initiation) predicts a worse relapse outcome. MBA showed individuals who co-used cocaine, heroin, prescription opioids, and cannabis had a higher risk for relapse (OR = 2.82, 95%CI = 1.13, 7.03). In RMLCA, higher risk of relapse was observed in individuals who presented with high baseline prescription opioid (OR = 1.9, 95% CI = 1.3, 2.76) or heroin use (OR = 3.54, 95%CI = 1.86, 6.72), although use decreased in both cases prior to treatment initiation. Conclusions: Our analyses identified subgroups with distinct patterns of polysubstance use. Different patterns of polysubstance use differentially predict relapse outcomes. Interventions tailored to these individuals with specific polysubstance use patterns prior to treatment initiation may increase the effectiveness of relapse prevention.