Simulating the Simultaneous Impact of Medication for Opioid Use Disorder and Naloxone on Opioid Overdose Death in Eight New York Counties.

BACKGROUND: The United States is in the midst of an opioid overdose epidemic; 28.3 per 100,000 people died of opioid overdose in 2020. Simulation models can help understand and address this complex, dynamic, and nonlinear social phenomenon. Using the HEALing Communities Study, aimed at reducing opioid overdoses, and an agent-based model, Simulation of Community-Level Overdose Prevention Strategy, we simulated increases in buprenorphine initiation and retention and naloxone distribution aimed at reducing overdose deaths by 40% in New York Counties. METHODS: Our simulations covered 2020-2022. The eight counties contrasted urban or rural and high and low baseline rates of opioid use disorder treatment. The model calibrated agent characteristics for opioid use and use disorder, treatments and treatment access, and fatal and nonfatal overdose. Modeled interventions included increased buprenorphine initiation and retention, and naloxone distribution. We predicted a decrease in the rate of fatal opioid overdose 1 year after intervention, given various modeled intervention scenarios. RESULTS: Counties required unique combinations of modeled interventions to achieve a 40% reduction in overdose deaths. Assuming a 200% increase in naloxone from current levels, high baseline treatment counties achieved a 40% reduction in overdose deaths with a simultaneous 150% increase in buprenorphine initiation. In comparison, low baseline treatment counties required 250-300% increases in buprenorphine initiation coupled with 200-1000% increases in naloxone, depending on the county. CONCLUSIONS: Results demonstrate the need for tailored county-level interventions to increase service utilization and reduce overdose deaths, as the modeled impact of interventions depended on the county's experience with past and current interventions.

Evaluation of respondent-driven sampling in seven studies of people who use drugs from rural populations: findings from the Rural Opioid Initiative.

BACKGROUND: Accurate prevalence estimates of drug use and its harms are important to characterize burden and develop interventions to reduce negative health outcomes and disparities. Lack of a sampling frame for marginalized/stigmatized populations, including persons who use drugs (PWUD) in rural settings, makes this challenging. Respondent-driven sampling (RDS) is frequently used to recruit PWUD. However, the validity of RDS-generated population-level prevalence estimates relies on assumptions that should be evaluated. METHODS: RDS was used to recruit PWUD across seven Rural Opioid Initiative studies between 2018-2020. To evaluate RDS assumptions, we computed recruitment homophily and design effects, generated convergence and bottleneck plots, and tested for recruitment and degree differences. We compared sample proportions with three RDS-adjusted estimators (two variations of RDS-I and RDS-II) for five variables of interest (past 30-day use of heroin, fentanyl, and methamphetamine; past 6-month homelessness; and being positive for hepatitis C virus (HCV) antibody) using linear regression with robust confidence intervals. We compared regression estimates for the associations between HCV positive antibody status and (a) heroin use, (b) fentanyl use, and (c) age using RDS-1 and RDS-II probability weights and no weights using logistic and modified Poisson regression and random-effects meta-analyses. RESULTS: Among 2,842 PWUD, median age was 34 years and 43% were female. Most participants (54%) reported opioids as their drug of choice, however regional differences were present (e.g., methamphetamine range: 4-52%). Many recruitment chains were not long enough to achieve sample equilibrium. Recruitment homophily was present for some variables. Differences with respect to recruitment and degree varied across studies. Prevalence estimates varied only slightly with different RDS weighting approaches, most confidence intervals overlapped. Variations in measures of association varied little based on weighting approach. CONCLUSIONS: RDS was a useful recruitment tool for PWUD in rural settings. However, several violations of key RDS assumptions were observed which slightly impacts estimation of proportion although not associations.

Text Analysis of Trends in Health Equity and Disparities From the Internal Revenue Service Tax Documentation Submitted by US Nonprofit Hospitals Between 2010 and 2019: Exploratory Study.

BACKGROUND: Many US hospitals are classified as nonprofits and receive tax-exempt status partially in exchange for providing benefits to the community. Proof of compliance is collected with the Schedule H form submitted as part of the annual Internal Revenue Service Form 990 (F990H), including a free-response text section that is known for being ambiguous and difficult to audit. This research is among the first to use natural language processing approaches to evaluate this text section with a focus on health equity and disparities. OBJECTIVE: This study aims to determine the extent to which the free-response text in F990H reveals how nonprofit hospitals address health equity and disparities, including alignment with public priorities. METHODS: We used free-response text submitted by hospital reporting entities in Part V and VI of the Internal Revenue Service Form 990 Schedule H between 2010 and 2019. We identified 29 main themes connected to health equity and disparities, and 152 related key phrases. We tallied occurrences of these phrases through term frequency analysis, calculated the Moran I statistic to assess geographic variation in 2018, analyzed Google Trends use for the same terms during the same period, and used semantic search with Sentence-BERT in Python to understand contextual use. RESULTS: We found increased use from 2010 to 2019 across all the 29 phrase themes related to health equity and disparities. More than 90% of hospital reporting entities used terms in 2018 and 2019 related to affordability (2018: 2117/2131, 99.34%; 2019: 1620/1627, 99.57%), government organizations (2018: 2053/2131, 96.33%; 2019: 1577/1627, 96.93%), mental health (2018: 1937/2131, 90.9%; 2019: 1517/1627, 93.24%), and data collection (2018: 1947/2131, 91.37%; 2019: 1502/1627, 92.32%). The themes with the largest relative increase were LGBTQ (lesbian, gay, bisexual, transgender, and queer; 1676%; 2010: 12/2328, 0.51%; 2019: 149/1627, 9.16%) and social determinants of health (958%; 2010: 68/2328, 2.92%; 2019: 503/1627, 30.92%). Terms related to homelessness varied geographically from 2010 to 2018, and terms related to equity, health IT, immigration, LGBTQ, oral health, rural, social determinants of health, and substance use showed statistically significant (P<.05) geographic variation in 2018. The largest percentage point increase was for terms related to substance use (2010: 403/2328, 17.31%; 2019: 1149/1627, 70.62%). However, use in themes such as LGBTQ, disability, oral health, and race and ethnicity ranked lower than public interest in these topics, and some increased mentions of themes were to explicitly say that no action was taken. CONCLUSIONS: Hospital reporting entities demonstrate an increasing awareness of health equity and disparities in community benefit tax documentation, but these do not necessarily correspond with general population interests or additional action. We propose further investigation of alignment with community health needs assessments and make suggestions for improvements to F990H reporting requirements.

Examining buprenorphine diversion through a harm reduction lens: an agent-based modeling study.

BACKGROUND: Recent policies have lessened restrictions around prescribing buprenorphine-naloxone (buprenorphine) for the treatment of opioid use disorder (OUD). The primary concern expressed by critics of these policies is the potential for buprenorphine diversion. However, the population-level effects of increased buprenorphine diversion are unclear. If replacing the use of heroin or fentanyl, use of diverted buprenorphine could be protective. METHODS: Our study aim was to estimate the impact of buprenorphine diversion on opioid overdose using an agent-based model calibrated to North Carolina. We simulated the progression of opioid misuse and opioid-related outcomes over a 5-year period. Our status quo scenario assumed that 50% of those prescribed buprenorphine diverted at least one dose per week to other individuals with OUD and 10% of individuals with OUD used diverted buprenorphine at least once per week. A controlled prescription only scenario assumed that no buprenorphine would be diverted, while an increased diversion scenario assumed that 95% of those prescribed buprenorphine diverted and 50% of individuals with OUD used diverted buprenorphine. We assumed that use of diverted buprenorphine replaced the use of other opioids for that day. Sensitivity analyses increased the risk of overdose when using diverted buprenorphine, increased the frequency of diverted buprenorphine use, and simulated use of diverted buprenorphine by opioid-naïve individuals. Scenarios were compared on opioid overdose-related outcomes over the 5-year period. RESULTS: Our status quo scenario predicted 10,658 (credible interval [CI]: 9699-11,679) fatal opioid overdoses. A scenario simulating controlled prescription only of buprenorphine (i.e., no diversion) resulted in 10,741 (9895-11,650) fatal opioid overdoses versus 10,301 (9439-11,244) within a scenario simulating increased diversion. Compared to the status quo, the controlled prescription only scenario resulted in a similar number of fatal overdoses, while the scenario with increased diversion of buprenorphine resulted in 357 (3.35%) fewer fatal overdoses. Even when increasing overdose risk while using diverted buprenorphine and incorporating use by opioid naïve individuals, increased diversion did not increase overdoses compared to a scenario with no buprenorphine diversion. CONCLUSIONS: A similar number of opioid overdoses occurred under modeling conditions with increased rates of buprenorphine diversion among persons with OUD, with non-statistical trends toward lower opioid overdoses. These results support existing calls for low- to no-barrier access to buprenorphine for persons with OUD.

Pharmacotherapy for Alcohol Use Disorder: A Systematic Review and Meta-Analysis.

Importance: Alcohol use disorder affects more than 28.3 million people in the United States and is associated with increased rates of morbidity and mortality. Objective: To compare efficacy and comparative efficacy of therapies for alcohol use disorder. Data Sources: PubMed, the Cochrane Library, the Cochrane Central Trials Registry, PsycINFO, CINAHL, and EMBASE were searched from November 2012 to September 9, 2022 Literature was subsequently systematically monitored to identify relevant articles up to August 14, 2023, and the PubMed search was updated on August 14, 2023. Study Selection: For efficacy outcomes, randomized clinical trials of at least 12 weeks' duration were included. For adverse effects, randomized clinical trials and prospective cohort studies that compared drug therapies and reported health outcomes or harms were included. Data Extraction and Synthesis: Two reviewers evaluated each study, assessed risk of bias, and graded strength of evidence. Meta-analyses used random-effects models. Numbers needed to treat were calculated for medications with at least moderate strength of evidence for benefit. Main Outcomes and Measures: The primary outcome was alcohol consumption. Secondary outcomes were motor vehicle crashes, injuries, quality of life, function, mortality, and harms. Results: Data from 118 clinical trials and 20 976 participants were included. The numbers needed to treat to prevent 1 person from returning to any drinking were 11 (95% CI, 1-32) for acamprosate and 18 (95% CI, 4-32) for oral naltrexone at a dose of 50 mg/d. Compared with placebo, oral naltrexone (50 mg/d) was associated with lower rates of return to heavy drinking, with a number needed to treat of 11 (95% CI, 5-41). Injectable naltrexone was associated with fewer drinking days over the 30-day treatment period (weighted mean difference, -4.99 days; 95% CI, -9.49 to -0.49 days) Adverse effects included higher gastrointestinal distress for acamprosate (diarrhea: risk ratio, 1.58; 95% CI, 1.27-1.97) and naltrexone (nausea: risk ratio, 1.73; 95% CI, 1.51-1.98; vomiting: risk ratio, 1.53; 95% CI, 1.23-1.91) compared with placebo. Conclusions and Relevance: In conjunction with psychosocial interventions, these findings support the use of oral naltrexone at 50 mg/d and acamprosate as first-line pharmacotherapies for alcohol use disorder.

Exploration of the Impact of Combining Risk Phenotypes on the Likelihood of Alcohol Problems in Young Adults.

AIMS: We tested the hypothesis that high novelty seeking (NS-an externalizing trait), sweet-liking (SL-a phenotype that may reflect processing of hedonic stimuli) and initial insensitivity to the impairing effects of alcohol (SRE-A) act independently and synergistically to increase the likelihood of having alcohol-related problems in young adults. METHODS: A sample of 145 young adults, ages 18-26, balanced for gender and alcohol use disorders identification test (AUDIT) scores <8 or ≥8 were selected from a prior sample. NS, SL and SRE-A were assessed along with AUDIT score and family history of alcoholism (FH). The effect of phenotypes and their interaction on the likelihood of alcohol problems was assessed. RESULTS: All three phenotypes contribute to the total AUDIT score. The best-fitting model explaining 35.8% of AUDIT variance includes all three phenotypes and an interaction between NS and SL/sweet-disliking (SDL) status. The addition of FH to the model explains an additional 4% of variance in both models. Classification and regression tree analysis showed that the main phenotype influencing AUDIT score is NS. The SL/SDL phenotype is a strong modifying factor for high NS. SRE-A was shown to be a weak modifier for individuals with low NS. CONCLUSION: The evidence supports the hypothesis that the presence of multiple alcohol use disorders (AUD) risk phenotypes with different underlying neurobiological mechanisms within an individual (SL, NS and SRE-A) represents a higher likelihood for developing alcohol-related problems and may allow for a graded assessment of risk for AUD and offer the possibility for early intervention strategies.

Predictive model of multiple emergency department visits among adults: analysis of the data from the National Survey of Drug Use and Health (NSDUH).

BACKGROUND: In this methodological paper, we use a novel, predictive approach to examine how demographics, substance use, mental and other health indicators predict multiple visits (≥3) to emergency departments (ED) within a year. METHODS: State-of-the-art predictive methods were used to evaluate predictive ability and factors predicting multiple visits to ED within a year and to identify factors that influenced the strength of the prediction. The analysis used public-use datasets from the 2015-2018 National Surveys on Drug Use and Health (NSDUH), which used the same questionnaire on the variables of interest. Analysis focused on adults aged ≥18 years. Several predictive models (regressions, trees, and random forests) were validated and compared on independent datasets. RESULTS: Predictive ability on a test set for multiple ED visits (≥3 times within a year) measured as the area under the receiver operating characteristic (ROC) reached 0.8, which is good for a national survey. Models revealed consistency in predictive factors across the 4 survey years. The most influential variables for predicting ≥3 ED visits per year were fair/poor self-rated health, being nervous or restless/fidgety, having a lower income, asthma, heart condition/disease, having chronic obstructive pulmonary disease (COPD), nicotine dependence, African-American race, female sex, having diabetes, and being of younger age (18-20). CONCLUSIONS: The findings reveal the need to address behavioral and mental health contributors to ED visits and reinforce the importance of developing integrated care models in primary care settings to improve mental health for medically vulnerable patients. The presented modeling approach can be broadly applied to national and other large surveys.

Feasibility of needle and syringe programs in Tajikistan distributing low dead space needles.

BACKGROUND: In 2012, the World Health Organization recommended that needle and syringe programs offer their clients low dead space insulin syringes with permanently attached needles. However, in many countries, these syringes are not acceptable to a majority of people who inject drugs. This study assessed the feasibility of working with needle and syringe programs to implement the WHO recommendation using low dead space detachable needles. The study also assessed the acceptability of the needles. METHODS: Two needle and syringe programs in Tajikistan-one in Kulob and one in Khudjand-received 25,000 low dead space detachable needles each. The programs distributed low dead space detachable needles and a marketing flyer that emphasized the relative advantages of the needles. Each program also enrolled 100 participants, and each participant completed a baseline interview and a 2-month follow-up interview. RESULTS: At follow-up, 100% of participants reported trying the low dead space detachable needles, and 96% reported that they liked using the needles. Both needle and syringe programs distributed all their needles within the first 60 days of the project indicating use of the needles, even among clients who did not participate in the study. CONCLUSIONS: This project demonstrates that it is feasible for needle and syringe programs to offer and promote low dead space needles to their clients. The findings indicate that low dead space needles are acceptable to needle and syringe program clients in these Tajikistan cities. To reduce HIV and hepatitis C virus transmission, needle and syringe programs should offer low dead space needles, low dead space insulin syringes in addition to standard needles, and syringes to their clients.

Options for reducing HIV transmission related to the dead space in needles and syringes.

BACKGROUND: When shared by people who inject drugs, needles and syringes with different dead space may affect the probability of HIV and hepatitis C virus (HCV) transmission differently. METHODS: We measured dead space in 56 needle and syringe combinations obtained from needle and syringe programs across 17 countries in Europe and Asia. We also calculated the amounts of blood and HIV that would remain in different combinations following injection and rinsing. RESULTS: Syringe barrel capacities ranged from 0.5 to 20 mL. Needles ranged in length from 8 to 38 mm. The average dead space was 3 µL in low dead space syringes with permanently attached needles, 13 µL in high dead space syringes with low dead space needles, 45 µL in low dead space syringes with high dead space needles, and 99 µL in high dead space syringes with high dead space needles. Among low dead space designs, calculated volumes of blood and HIV viral burden were lowest for low dead space syringes with permanently attached needles and highest for low dead space syringes with high dead space needles. CONCLUSION: The dead space in different low dead space needle and syringe combinations varied substantially. To reduce HIV transmission related to syringe sharing, needle and syringe programs need to combine this knowledge with the needs of their clients.

Personalized medicine for prevention: can risk stratified screening decrease colorectal cancer mortality at an acceptable cost?

PURPOSE: Tailored health care interventions are expected to transform clinical practice. The objective of this study was to develop an innovative model to assess the effectiveness, cost, and harms of risk stratified colorectal cancer screening. METHODS: We updated a previously validated microsimulation model consisting of three interlinked components: risk assessment, natural history, and screening/treatment modules. We used data from representative national surveys and the literature to create a synthetic population that mimics the family history and genetic profile of the US population. We applied risk stratification based on published risk assessment tools to triage individuals into five risk categories: high, increased, medium, decreased, and low. RESULTS: On average, the incremental cost of risk stratified screening for colorectal cancer compared to the current approach at 60% and 80% compliance rates is $18,342 and $23,961 per life year gained. The harms in terms of false positives and perforations are consistently lower for personalized scenarios across all compliance rates. False positives are reduced by more than 47.0% and perforations by at least 9.9%. There is considerable uncertainty in the life years gained, but the reduction in harms remains stable under all scenarios. CONCLUSION: A key finding is that risk stratified screening can reduce harms at all levels of compliance. Therefore, selection of screening scenarios should include comprehensive comparisons of mortality, harms from screening, and cost. This study provides guidance for evaluating risk stratified cancer screening and further research is required to identify optimal implementation approaches in the real-world setting.

User testing of an adaptation of fishbone diagrams to depict results of systematic reviews.

BACKGROUND: Summary of findings tables in systematic reviews are highly informative but require epidemiological training to be interpreted correctly. The usage of fishbone diagrams as graphical displays could offer researchers an effective approach to simplify content for readers with limited epidemiological training. In this paper we demonstrate how fishbone diagrams can be applied to systematic reviews and present the results of an initial user testing. METHODS: Findings from two systematic reviews were graphically depicted in the form of the fishbone diagram. To test the utility of fishbone diagrams compared with summary of findings tables, we developed and pilot-tested an online survey using Qualtrics. Respondents were randomized to the fishbone diagram or a summary of findings table presenting the same body of evidence. They answered questions in both open-ended and closed-answer formats; all responses were anonymous. Measures of interest focused on first and second impressions, the ability to find and interpret critical information, as well as user experience with both displays. We asked respondents about the perceived utility of fishbone diagrams compared to summary of findings tables. We analyzed quantitative data by conducting t-tests and comparing descriptive statistics. RESULTS: Based on real world systematic reviews, we provide two different fishbone diagrams to show how they might be used to display complex information in a clear and succinct manner. User testing on 77 students with basic epidemiological training revealed that participants preferred summary of findings tables over fishbone diagrams. Significantly more participants liked the summary of findings table than the fishbone diagram (71.8% vs. 44.8%; p < .01); significantly more participants found the fishbone diagram confusing (63.2% vs. 35.9%, p < .05) or indicated that it was difficult to find information (65.8% vs. 45%; p < .01). However, more than half of the participants in both groups were unable to find critical information and answer three respective questions correctly (52.6% in the fishbone group; 51.3% in the summary of findings group). CONCLUSIONS: Fishbone diagrams are compact visualizations that, theoretically, may prove useful for summarizing the findings of systematic reviews. Initial user testing, however, did not support the utility of such graphical displays.

Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California.

BACKGROUND: Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks. OBJECTIVES: This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California. METHODS: From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities. RESULTS: The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles. CONCLUSIONS: The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time.

Event-level analyses of sex-risk and injection-risk behaviors among nonmedical prescription opioid users.

BACKGROUND: Nonmedical prescription opioid use has been linked to hepatitis C virus (HCV) infection among people who inject drugs and with using high dead space syringes that retain more blood and transfer more HIV if shared. Little is known regarding its effects on sex-risk behaviors. OBJECTIVES: This paper examines event-level associations between nonmedical prescription opioid use and sharing high dead space syringes (injection risk) and unprotected intercourse (sex risk) behaviors. METHODS: We recruited 1,985 participants from two overlapping risk groups-drug users and men who have sex with men (MSM)-and their sex partners. Participants completed an interview that included event-level sex questions with recent sex partners and injection questions with recent injection partners. We used multivariable generalized estimating equations (GEE) to assess the associations between nonmedical prescription opioid use and unprotected intercourse during sexual encounters and sharing syringes during injection episodes, while adjusting for within-person correlations. RESULTS: When both partners used nonmedical prescription opioids, its use was independently associated with unprotected intercourse in sexual encounters (OR = 2.24; 95% CI = 1.12, 4.49). The use of nonmedical prescription opioids was also associated with sharing high dead space syringes during injection episodes (OR = 6.57; 95% CI = 1.63, 26.51). CONCLUSION: Nonmedical prescription opioid use is associated with an increase in the risk of unprotected sex and sharing high dead space syringes. HIV and HCV prevention interventions for nonmedical prescription opioid users should address sex-risk behaviors and encourage the use of acceptable low dead space needles and syringes.

Factors that influence the characteristics of needles and syringes used by people who inject drugs in Tajikistan.

BACKGROUND: "Low dead space" syringes with permanently attached needles retain less fluid, blood, and HIV after use than standard "high dead space" syringes. This reduces the probability of HIV transmission if they are shared by people who inject drugs (PWID). The World Health Organization recently recommended that needle and syringe programs (NSP) offer clients low dead space syringes. The success of this recommendation will depend on PWID switching to low dead space needles and syringes. This paper examines the needles and syringes that PWID in Tajikistan use and factors that influence their choices. METHODS: In May 2014, we conducted six focus groups in Kulob and six in Khorog, Tajikistan, with a total of 100 participants. NSP staff members recruited participants. Focus group topics included the needles and syringes used and factors that influence choice of needles and syringes. Focus groups were conducted in Russian and Tajik, audio recorded, transcribed, and translated into English. The translated files were imported into NVivo 10 for coding and analysis. RESULTS: All participants in both cities were male and reported injecting heroin. Everyone also reported using syringes with detachable needles almost exclusively. The most popular syringe sizes were 2 and 5 ml. Needles ranged in gauge from 25 to 21 g. Needle gauge was influenced by the size of the vein, the viscosity of drug solution to be injected, and problems with blood clotting. Needles ranged in length from 12 to 38 mm, with 25 and 32 mm being the most popular. Needle length was influenced by the depth of the vein being used. Many PWID inject volumes of fluid greater than 1 ml into deep veins that require needles at least 25 mm long and 25 g in diameter. CONCLUSION: Most low dead space syringes are 1-ml insulin syringes with 12 mm 28 g permanently attached needles. Findings from this project suggest that these will not be acceptable to PWID who need larger syringes and longer and thicker needles that are detachable. Low dead space detachable needles appear to be an acceptable option that could overcome barriers to the widespread use of low dead space equipment for reducing HIV and HCV transmission.

Sweet-liking is associated with transformation of heavy drinking into alcohol-related problems in young adults with high novelty seeking.

BACKGROUND: We tested the hypothesis that high novelty seeking (NS) (a trait that promotes experimentation) and sweet-liking (SL) (a phenotype that may reflect processing of hedonic stimuli) act independently and synergistically to increase the risk of having alcohol-related problems in young adults. METHODS: A sample of 163 young adults, ages 18 to 26, was recruited and balanced for gender and evidence for presence of alcohol problems to yield 150 evaluable participants. NS was evaluated using the Tridimensional Personality Questionnaire. Pleasurable response to sweet taste was tested to identify sweet-likers and sweet-dislikers. Alcohol use and problems were assessed by the Alcohol Use Disorders Identification Test and the Rutgers Alcohol Problem Index. RESULTS: NS, but not SL, was positively and significantly associated with alcohol consumption and alcohol problems; however, the effect of NS on alcohol problems was significantly enhanced in the presence of the SL phenotype, thus showing a strong synergistic interaction. The combination of SL and high NS was associated with increased odds of having alcohol problems -20.64 (95% CI: -89.98, 4.74) compared to those with low NS and sweet-disliking. Other combinations did not produce such odds ratios. SL and low NS showed OR = 1.88 (95% CI 0.44, 7.99), and sweet-dislikers and high novelty seekers had OR = 4.07 (95%, CI 1.01, 16.46). CONCLUSIONS: These results support and extend our hypothesis that as clinically distinct phenotypes, high NS and the SL phenotype are associated with risk of alcohol-related problems. High NS is associated with the use of alcohol, and the presence of the SL phenotype appears to bias an individual to alcohol problems once alcohol use is initiated. Understanding the biology and phenomenology of these phenotypes will allow a more complete picture of the processes that lead to alcohol problems.

Pharmacotherapy for adults with alcohol use disorders in outpatient settings: a systematic review and meta-analysis.

IMPORTANCE: Alcohol use disorders cause substantial morbidity and early mortality yet remain greatly undertreated. Medications are considerably underused. OBJECTIVE: To conduct a systematic review and meta-analysis of the benefits and harms of medications (US FDA-approved and others) for adults with alcohol use disorders. DATA SOURCES: PubMed, Cochrane Library, PsycINFO, CINAHL, EMBASE, FDA website, and clinical trials registries (January 1, 1970, to March 1, 2014). STUDY SELECTION: Two reviewers selected randomized clinical trials (RCTs) with at least 12 weeks' duration that reported eligible outcomes and head-to-head prospective cohort studies reporting health outcomes or harms. DATA EXTRACTION AND SYNTHESIS: We conducted meta-analyses using random-effects models and calculated numbers needed to treat for benefit (NNTs) or harm (NNHs). MAIN OUTCOMES AND MEASURES: Alcohol consumption, motor vehicle crashes, injuries, quality of life, function, mortality, and harms. RESULTS: We included 122 RCTs and 1 cohort study (total 22,803 participants). Most assessed acamprosate (27 studies, n = 7519), naltrexone (53 studies, n = 9140), or both. The NNT to prevent return to any drinking for acamprosate was 12 (95% CI, 8 to 26; risk difference [RD], -0.09; 95% CI, -0.14 to -0.04) and was 20 (95% CI, 11 to 500; RD, -0.05; 95% CI, -0.10 to -0.002) for oral naltrexone (50 mg/d). The NNT to prevent return to heavy drinking was 12 (95% CI, 8 to 26; RD -0.09; 95% CI, -0.13 to -0.04) for oral naltrexone (50 mg/d). Meta-analyses of trials comparing acamprosate to naltrexone found no statistically significant difference between them for return to any drinking (RD, 0.02; 95% CI, -0.03 to 0.08) or heavy drinking (RD, 0.01; 95% CI, -0.05 to 0.06). For injectable naltrexone, meta-analyses found no association with return to any drinking (RD, -0.04; 95% CI, -0.10 to 0.03) or heavy drinking (RD, -0.01; 95% CI, -0.14 to 0.13) but found an association with reduction in heavy drinking days (weighted mean difference [WMD], -4.6%; 95% CI, -8.5% to -0.56%). Among medications used off-label, moderate evidence supports an association with improvement in some consumption outcomes for nalmefene (heavy drinking days per month: WMD, -2.0; 95% CI, -3.0 to -1.0; drinks per drinking day: WMD, -1.02; 95% CI, -1.77 to -0.28) and topiramate (% heavy drinking days: WMD, -9.0%; 95% CI, -15.3% to -2.7%; drinks per drinking day: WMD, -1.0; 95% CI, -1.6 to -0.48). For naltrexone and nalmefene, NNHs for withdrawal from trials due to adverse events were 48 (95% CI, 30 to 112) and 12 (95% CI, 7 to 50), respectively; risk was not significantly increased for acamprosate or topiramate. CONCLUSIONS AND RELEVANCE: Both acamprosate and oral naltrexone were associated with reduction in return to drinking. When directly compared with one another, no significant differences were found between acamprosate and naltrexone for controlling alcohol consumption. Factors such as dosing frequency, potential adverse events, and availability of treatments may guide medication choice.

Comparing methods for risk prediction of multicategory outcomes: dichotomized logistic regression vs. multinominal logit regression.

Background: Medical outcomes of interest to clinicians may have multiple categories. Researchers face several options for risk prediction of such outcomes, including dichotomized logistic regression and multinomial logit regression modeling. We aimed to compare these methods and provide practical guidance needed. Methods: We described dichotomized logistic regression and competing risks regression, and an alternative to standard multinomial logit regression, continuation-ratio logit regression for ordinal outcomes. We then applied these methods to develop prediction models of survival and growth outcomes based on the NICHD Extremely Preterm Birth Outcome Tool model. The statistical and practical advantages and flaws of these methods were examined and both discrimination and calibration of the estimated models were assessed. Results: The dichotomized logistic models and multinomial continuation-ratio logit model had similar discrimination and calibration in predicting death and survival without neurodevelopmental impairment. But the continuation-ratio logit model had better discrimination and calibration in predicting probabilities of neurodevelopmental impairment. The sum of predicted probabilities of outcome categories from the logistic models did not equal 100% for about half of the study infants, ranging from 87.7% to 124.0%, and the logistic model of neurodevelopmental impairment greatly overpredicted the risk among low-risk infants and underpredicted among high-risk infants. Conclusions: Estimating multiple logistic regression models of dichotomized outcomes may result in poorly calibrated predictions. For an outcome with multiple ordinal categories, continuation-ratio logit regression is a useful alternative to standard multinomial logit regression. It produces better calibrated predictions and has the advantages of simplicity in model interpretation and flexibility to include outcome category-specific predictors and random-effect terms for patient heterogeneity by hospital.

Simulated impact of medicaid expansion on the economic burden of opioid use disorder in North Carolina.

BACKGROUND: Opioid use disorder (OUD) imposes significant costs on state and local governments. Medicaid expansion may lead to a reduction in the cost burden of OUD to the state. METHODS: We estimated the health care, criminal justice and child welfare costs, and tax revenue losses, attributable to OUD and borne by the state of North Carolina in 2022, and then estimated changes in the same domains following Medicaid expansion in North Carolina (adopted in December 2023). Analyses used existing literature on the national and state-level costs attributable to OUD to estimate individual-level health care, criminal justice, and child welfare system costs, and lost tax revenues. We combined Individual-level costs and prevalence estimates to estimate costs borne by the state before Medicaid expansion. Changes in costs after expansion were computed based on a) medication for opioid use disorder (MOUD) access for new enrollees and b) shifting of responsibility for some health care costs from the state to the federal government. Monte Carlo simulation accounted for the impact of parameter uncertainty. Dollar estimates are from the 2022 price year, and costs following the first year were discounted at 3 %. RESULTS: In 2022, North Carolina incurred costs of $749 million (95 % credible interval [CI]: $305 M-$1,526 M) associated with OUD (53 % in health care, 36 % in criminal justice, 7 % in lost tax revenue, and 4 % in child welfare costs). Expanding Medicaid lowered the cost burden of OUD incurred by the state. The state was predicted to save an estimated $72 million per year (95 % CI: $6 M-$241 M) for the first two years and $30 million per year (95 % CI: -$28 M-$176 M) in subsequent years. Over five years, savings totaled $224 million (95 % CI: -$47 M-$949 M). CONCLUSION: Medicaid expansion has the potential to decrease the burden of OUD in North Carolina, and policymakers should expedite its implementation.

Racial/Ethnic disparities in exposure to neighborhood violence and lung cancer risk in Chicago.

BACKGROUND: Despite the lower prevalence and frequency of smoking, Black adults are disproportionately affected by lung cancer. Exposure to chronic stress generates heightened immune responses, which creates a cell environment conducive to lung cancer development. Residents in poor and segregated neighborhoods are exposed to increased neighborhood violence, and chronic exposure to violence may have downstream physiological stress responses, which may explain racial disparities in lung cancer in predominantly Black urban communities. METHODS: We utilized retrospective electronic medical records of patients who underwent a screening or diagnostic test for lung cancer at an academic medical center in Chicago to examine the associations between lung cancer diagnosis and individual characteristics (age, gender, race/ethnicity, and smoking status) and neighborhood-level homicide rate. We then used a synthetic population to estimate the neighborhood-level lung cancer risk to understand spatial clusters of increased homicide rates and lung cancer risk. RESULTS: Older age and former/current smoking status were associated with increased odds of lung cancer diagnosis. Hispanic patients were more likely than White patients to be diagnosed with lung cancer, but there was no statistical difference between Black and White patients in lung cancer diagnosis. The odds of being diagnosed with lung cancer were significantly higher for patients living in areas with the third and fourth quartiles of homicide rates compared to the second quartile of homicide rates. Furthermore, significant spatial clusters of increased lung cancer risk and homicide rates were observed on Chicago's South and West sides. CONCLUSIONS: Neighborhood violence was associated with an increased risk of lung cancer. Black residents in Chicago are disproportionately exposed to neighborhood violence, which may partially explain the existing racial disparity in lung cancer. Incorporating neighborhood violence exposure into lung cancer risk models may help identify high-risk individuals who could benefit from lung cancer screening.

Random forest methodology for model-based recursive partitioning: the mobForest package for R.

BACKGROUND: Recursive partitioning is a non-parametric modeling technique, widely used in regression and classification problems. Model-based recursive partitioning is used to identify groups of observations with similar values of parameters of the model of interest. The mob() function in the party package in R implements model-based recursive partitioning method. This method produces predictions based on single tree models. Predictions obtained through single tree models are very sensitive to small changes to the learning sample. We extend the model-based recursive partition method to produce predictions based on multiple tree models constructed on random samples achieved either through bootstrapping (random sampling with replacement) or subsampling (random sampling without replacement) on learning data. RESULTS: Here we present an R package called "mobForest" that implements bagging and random forests methodology for model-based recursive partitioning. The mobForest package constructs large number of model-based trees and the predictions are aggregated across these trees resulting in more stable predictions. The package also includes functions for computing predictive accuracy estimates and plots, residuals plot, and variable importance plot. CONCLUSION: The mobForest package implements a random forest type approach for model-based recursive partitioning. The R package along with it source code is available at http://CRAN.R-project.org/package=mobForest.