Association between trajectories of adherence to endocrine therapy and risk of treated breast cancer recurrence among US nonmetastatic breast cancer survivors.

BACKGROUND: Endocrine therapy is the mainstay treatment for breast cancer (BC) to reduce BC recurrence risk. During the first year of endocrine therapy use, nearly 30% of BC survivors are nonadherent, which may increase BC recurrence risk. This study is to examine the association between endocrine therapy adherence trajectories and BC recurrence risk in nonmetastatic BC survivors. METHODS: This retrospective cohort study included Medicare beneficiaries in the United States (US) with incident nonmetastatic BC followed by endocrine therapy initiation in 2010-2019 US Surveillance, Epidemiology, and End Results linked Medicare data. We calculated monthly fill-based proportion of days covered in the first year of endocrine therapy. We applied group-based trajectory models to identify distinct endocrine therapy adherence patterns. After the end of the first-year endocrine therapy trajectory measurement period, we estimated the risk of time to first treated BC recurrence within 4 years using Cox proportional hazards models. RESULTS: We identified 5 trajectories of adherence to endocrine therapy in BC Stages 0-I subgroup (n = 28,042) and in Stages II-III subgroup (n = 7781). A trajectory of discontinuation before 6 months accounted for 7.0% in Stages 0-I and 5.8% in Stages II-III subgroups, and this trajectory was associated with an increased treated BC recurrence risk compared to nearly perfect adherence (Stages 0-I: adjusted hazard [aHR] = 1.84, 95% CI = 1.46-2.33; Stages II-III: aHR = 1.38, 95% CI = 1.07-1.77). CONCLUSIONS: Nearly 7% of BC survivors who discontinued before completing 6 months of treatment was associated with an increased treated BC recurrence risk compared to those with nearly perfect adherence among Medicare nonmetastatic BC survivors.

Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias.

OBJECTIVE: To develop a natural language processing (NLP) package to extract social determinants of health (SDoH) from clinical narratives, examine the bias among race and gender groups, test the generalizability of extracting SDoH for different disease groups, and examine population-level extraction ratio. METHODS: We developed SDoH corpora using clinical notes identified at the University of Florida (UF) Health. We systematically compared 7 transformer-based large language models (LLMs) and developed an open-source package - SODA (i.e., SOcial DeterminAnts) to facilitate SDoH extraction from clinical narratives. We examined the performance and potential bias of SODA for different race and gender groups, tested the generalizability of SODA using two disease domains including cancer and opioid use, and explored strategies for improvement. We applied SODA to extract 19 categories of SDoH from the breast (n = 7,971), lung (n = 11,804), and colorectal cancer (n = 6,240) cohorts to assess patient-level extraction ratio and examine the differences among race and gender groups. RESULTS: We developed an SDoH corpus using 629 clinical notes of cancer patients with annotations of 13,193 SDoH concepts/attributes from 19 categories of SDoH, and another cross-disease validation corpus using 200 notes from opioid use patients with 4,342 SDoH concepts/attributes. We compared 7 transformer models and the GatorTron model achieved the best mean average strict/lenient F1 scores of 0.9122 and 0.9367 for SDoH concept extraction and 0.9584 and 0.9593 for linking attributes to SDoH concepts. There is a small performance gap (∼4%) between Males and Females, but a large performance gap (>16 %) among race groups. The performance dropped when we applied the cancer SDoH model to the opioid cohort; fine-tuning using a smaller opioid SDoH corpus improved the performance. The extraction ratio varied in the three cancer cohorts, in which 10 SDoH could be extracted from over 70 % of cancer patients, but 9 SDoH could be extracted from less than 70 % of cancer patients. Individuals from the White and Black groups have a higher extraction ratio than other minority race groups. CONCLUSIONS: Our SODA package achieved good performance in extracting 19 categories of SDoH from clinical narratives. The SODA package with pre-trained transformer models is available at https://github.com/uf-hobi-informatics-lab/SODA_Docker.

Coccidioides Serologic Screening Practices in Individuals With Rheumatic and Autoimmune Diseases.

OBJECTIVE: We aimed to estimate Coccidioides serologic screening rates before initiation of biologic disease-modifying antirheumatic drugs including tofacitinib (b/tsDMARDs), conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), and/or noninhaled corticosteroids. METHODS: This retrospective cohort study used 2011 to 2016 US Medicare claims data and included beneficiaries with rheumatic or autoimmune disease residing in regions within Arizona, California, and Texas endemic for Coccidioides spp. with ≥1 prescription for a b/tsDMARD, csDMARD, and/or noninhaled corticosteroid. We estimated prior-year serologic screening incidence before initiating b/tsDMARDs, csDMARD, and/or noninhaled corticosteroid. RESULTS: During 2012 to 2016, 4,331 beneficiaries filled 64,049 prescriptions for b/tsDMARDs, csDMARDs, and noninhaled corticosteroids. Arizona's estimated screening rate was 20.1% (95% confidence interval [95% CI] 14.5-25.7) in the year before prescription initiation for b/tsDMARDs, 8.1% (95% CI 6.5-9.7) before csDMARDs, and 6.9% (95% CI: 5.6-8.2) before corticosteroids. Screening rates for b/tsDMARDs (2.8%, 95% CI 0.0-6.7), csDMARDs (1.0%, 95% CI 0.0-2.0), and corticosteroids (0.8%, 95% CI: 0.4-1.1) were negligible in California and undetected in Texas. Adjusted screening rate before prescription for b/tsDMARDs in Arizona increased from 14.5% (95% CI 7.5-21.5) in 2012 to 26.7% (95% CI 17.6-35.8) in 2016. Rheumatologists prescribing b/tsDMARDs in Arizona screened more than other providers (20.9% [95% CI 13.9-27.9] vs 12.9% [95% CI 5.9-20.0]). CONCLUSION: Coccidioides serologic screening rates among Medicare beneficiaries with rheumatic/autoimmune diseases on b/tsDMARDs, csDMARDs, and noninhaled corticosteroids was low in Coccidioides spp.-US endemic regions between 2012 and 2016. Alignment of screening recommendations and clinical practice is needed.

Risk of Coccidioidomycosis Infection Among Individuals Using Biologic Response Modifiers, Corticosteroids, and Oral Small Molecules.

OBJECTIVE: The study objective was to examine associations between the use of biologic response modifiers (BRMs), corticosteroids, and oral small molecules (OSMs) and subsequent coccidioidomycosis infection risk among US Medicare beneficiaries with rheumatic or autoimmune diseases. METHODS: This retrospective cohort study used US 2011 to 2016 Medicare claims data. We identified geographic areas with endemic coccidioidomycosis (≥25 cases per 10,000 beneficiaries). Among beneficiaries having any rheumatic/autoimmune diseases, we identified those initiating BRMs, corticosteroids, and OSMs. Based on refill days supplied, we created time-varying exposure variables for BRMs, corticosteroids, and OSMs with a 90-day lag period after drug cessation. We examined BRMs, corticosteroids, and OSMs and subsequent coccidioidomycosis infection risk using multivariable Cox proportional hazard regression. RESULTS: Among 135,237 beneficiaries (mean age: 67.8 years; White race: 83.1%; Black race: 3.6%), 5,065 had rheumatic or autoimmune diseases, of which 107 individuals were diagnosed with coccidioidomycosis during the study period (6.1 per 1,000 person-years). Increased risk of coccidioidomycosis was observed among beneficiaries prescribed any BRMs (17.7 per 1,000 person-years; adjusted hazard ratio [aHR] 3.94; 95% confidence interval [CI] 1.18-13.16), followed by individuals treated with only corticosteroids (12.2 per 1,000 person-years; aHR 2.29; 95% CI 1.05-5.03) compared to those treated with only OSMs (4.2 per 1,000 person-years). The rate of those treated with only OSMs was the same as that of beneficiaries without these medications. CONCLUSION: Incidence of coccidioidomycosis was low among 2011 to 2016 Medicare beneficiaries with rheumatic or autoimmune diseases. BRM and corticosteroid users may have higher risks of coccidioidomycosis compared to nonusers, warranting consideration of screening for patients on BRMs and corticosteroids in coccidioidomycosis endemic areas.

Association between trajectories of prescription opioid use and risk of opioid use disorder and overdose among US nonmetastatic breast cancer survivors.

PURPOSE: To examine the association between prescription opioid use trajectories and risk of opioid use disorder (OUD) or overdose among nonmetastatic breast cancer survivors by treatment type. METHODS: This retrospective cohort study included female nonmetastatic breast cancer survivors with at least 1 opioid prescription fill in 2010-2019 Surveillance, Epidemiology and End Results linked Medicare data. Opioid mean daily morphine milligram equivalents (MME) calculated within 1.5 years after initiating active breast cancer therapy. Group-based trajectory models identified distinct opioid use trajectory patterns. Risk of time to first OUD/overdose event within 1 year after the trajectory period was calculated for distinct trajectory groups using Cox proportional hazards models. Analyses were stratified by treatment type. RESULTS: Four opioid use trajectories were identified for each treatment group. For 38,030 survivors with systemic endocrine therapy, 3 trajectories were associated with increased OUD/overdose risk compared with early discontinuation: minimal dose (< 5 MME; adjusted hazard ratio [aHR] = 1.73 [95% CI 1.43-2.09]), very low dose (5-25 MME; 2.67 [2.05-3.48]), and moderate dose (51-90 MME; 6.20 [4.69-8.19]). For 9477 survivors with adjuvant chemotherapy, low-dose opioid use was associated with higher OUD/overdose risk (aHR = 7.33 [95% CI 2.52-21.31]) compared with early discontinuation. For 3513 survivors with neoadjuvant chemotherapy, the differences in OUD/OD risks across the 4 trajectories were not significant. CONCLUSIONS: Among Medicare nonmetastatic breast cancer survivors receiving systemic endocrine therapy or adjuvant chemotherapy, compared with early discontinuation, low-dose or moderate-dose opioid use were associated with six- to sevenfold higher OUD/overdose risk. Breast cancer survivors at high-risk of OUD/overdose may benefit from targeted interventions (e.g., pain clinic referral).

Patterns of Cough Medication Prescribing among Patients with Chronic Cough in Florida: 2012-2021.

Among patients with chronic cough (CC) in the 2012-2021 statewide OneFlorida Clinical Research Consortium database, we examined trends in cough medication (CM) prescribing prevalence over time in repeated cross-sectional analyses and identified distinct CM utilization trajectories using group-based trajectory modeling (GBTM) in a retrospective cohort study. Among eligible adults (≥18 years) without cancer/benign respiratory tumor diagnoses, we identified CC patients and non-CC patients with any cough-related diagnosis. In the GBTM analysis, we calculated the number of monthly prescriptions for any CMs (excluding gabapentinoids) during the 12 months from the first qualifying cough event to identify distinct utilization trajectories. From 2012 to 2021, benzonatate (9.6% to 26.1%), dextromethorphan (5.2% to 8.6%), and gabapentinoid (5.3% to 14.4%) use increased among CC patients, while opioid antitussive use increased from 2012 to 2015 and decreased thereafter (8.4% in 2012, 14.7% in 2015, 6.7% in 2021; all p < 0.001). Of 15,566 CC patients and 655,250 non-CC patients identified in the GBTM analysis, CC patients had substantial burdens of respiratory/non-respiratory comorbidities and healthcare service and concomitant medication use compared to non-CC patients. Among CC patients, GBTM identified three distinct CM utilization trajectories: (1) no CM use (n = 11,222; 72.1%); (2) declining CM use (n = 4105; 26.4%); and (3) chronic CM use (n = 239; 1.5%). CC patients in Florida had limited CM use with increasing trends in use of benzonatate, dextromethorphan, and gabapentinoids and a decreasing trend in opioid antitussive use. CC patients, particularly with chronic prescription CM use, experienced substantial disease burden.

Association between Antidepressants and Dementia Risk in Older Adults with Depression: A Systematic Review and Meta-Analysis.

Depression, commonly treated with antidepressants, is associated with an increased risk of dementia, especially in older adults. However, the association between antidepressant use and dementia risk is unclear. We searched for randomized controlled trials and observational studies from PubMed, Embase, and Cochrane on 1 February 2022, restricting to full texts in English. Since dementia is a chronic disease requiring a long induction time, we restricted studies with ≥1 year follow-up. We extracted the relative risk (RR) adjusted for the most variables from each study and evaluated the heterogeneity using I square (I2). The protocol was registered in the PROSPERO International Register of Systematic Reviews (CRD42022338038). We included six articles in the systematic review, of which the sample size ranged from 716 to 141,740, and the median length of follow-up was 5 years. The pooled RR was 1.21 (95% CI = 1.12-1.29) with an I2 of 71%. Our findings suggest that antidepressant use was associated with an increased risk of dementia in older adults with depression, yet moderate to high heterogeneity existed across studies. Future work accounting for the depression progression is needed to differentiate the effect of depression and antidepressants on dementia risk.

Trajectories of adherence to extended treatment with direct oral anticoagulants and risks of recurrent venous thromboembolism and major bleeding.

BACKGROUND: Little is known about medication adherence patterns and their association with effectiveness and safety among patients with venous thromboembolism (VTE) receiving direct oral anticoagulant (DOAC) therapy beyond 3-6 months of initial treatment. OBJECTIVE: To examine the associations between adherence trajectories of extended treatment with DOAC and the risks of recurrent VTE and major bleeding among patients with VTE. METHODS: We conducted a retrospective cohort study of patients with incident VTE who completed 6 months of initial anticoagulant treatment and received either DOAC extended therapy or no extended therapy using MarketScan Commercial and Medicare Supplemental databases (2013-2019). We used group-based trajectory models to identify distinct adherence patterns during extended treatment. Using inverse probability treatment weighted Cox proportional hazards models, we examined the association between the adherence trajectories and the risks of recurrent VTE and major bleeding. RESULTS: Among 10,960 patients with extended treatment with DOACs (rivaroxaban, apixaban, dabigatran, edoxaban) and 5,133 patients with no extended treatment, we identified 4 distinct trajectories (consistently high, gradually declining, rapidly declining, and no extended treatment). Compared with the no extended treatment group, the groups with consistently high adherence (hazard ratio = 0.09, 95% CI = 0.05-0.17) and with gradually declining adherence (0.13, 0.03-0.53) showed decreased recurrent VTE risk without increased major bleeding risk (consistently high adherence 1.19, 0.71-1.99; gradually declining adherence 1.96, 0.81-4.70). There was no difference in the risk of recurrent VTE (0.34, 0.10-1.16) for the group with rapidly declining adherence, but this group was associated with increased major bleeding risk (2.65, 1.01-6.92). CONCLUSIONS: Our findings underscore the clinical importance of continuing and remaining adherent to extended DOAC treatment without increased major bleeding risk for patients with VTE. DISCLOSURES: This research was supported by the BMS/Pfizer Alliance American Thrombosis Investigator Initiated Research Program. The funding source had no role in the design, collection, analysis, or interpretation of the data or the decision to submit the article for publication. Dr Lo-Ciganic reported receiving research funding from Merck Sharp & Dohme Corp. Dr Dietrich reported receiving honorarium for training and education from BMS/Pfizer. Dr DeRemer is a stockholder of Portola Pharmaceuticals and reported receiving personal fees for advisory board meeting from BMS. No other disclosures were reported.

Nationwide trends in hospitalization, medical costs, and mortality for asthma after introduction of biologics: A cross-sectional study in the United States.

BACKGROUND: Asthma is the most common inflammatory lung disease in the United States. Since 2015, biologic therapies have provided targeted treatment for patients with severe asthma. OBJECTIVE: To evaluate the trends for in-hospital outcomes of asthma before (2012-2014) and after (2016-2018) the introduction of biologic therapies for asthma. METHODS: We conducted a nationwide cross-sectional analysis of patients aged 2 years or older who were hospitalized for asthma between 2012 and 2018 using data from the Nationwide Readmissions Database. Outcomes included rates of asthma hospital admission and asthma-related 30-day readmission, hospital length of stay, hospital costs, and inpatient mortality. Generalized linear models assessed trends in rates of asthma admission and readmission, length of stay, costs, and mortality quarterly during 2012-2014 and 2016-2018. RESULTS: Among 691,537 asthma-related admissions, quarterly asthma admission rates significantly decreased (-0.90%, 95% CI = -1.46% to - 0.34%; P = 0.002) during 2016-2018, mainly among adults, but not during 2012-2014. Quarterly assessed readmission rates decreased by 2.40% (-2.85% to -1.96%; P < 0.0001) during 2012-2014 and by 2.12% (-2.74% to - 1.50%; P < 0.0001) during 2016-2018. Mean length of stay for asthma admissions decreased quarterly by 0.44% (-0.49% to - 0.38%; P < 0.0001) during 2012-2014 and by 0.27% (-0.34% to - 0.20%; P < 0.0001) during 2016-2018. Quarterly hospital costs for admissions were unchanged during 2012-2014 but increased by 0.28% (0.21% to 0.35%; P < 0.0001) during 2016-2018. There were no significant trends in inpatient mortality during 2012-2014 and 2016-2018. CONCLUSIONS: After the introduction of new biologics for severe asthma in 2015, asthma-related hospital admissions decreased significantly, whereas hospital costs increased. Asthma-related 30-day readmission rates and length of stay for asthma admissions continuously decreased, whereas inpatient mortality rates remained stable. DISCLOSURES: This work was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award Number R01HL136945. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The data that support the findings of this study are available from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project.

Association between treatment of hepatitis C virus and risk of cardiovascular disease among insured patients with the virus in the United States.

PURPOSE: Hepatitis C virus (HCV) infection has been associated with increased risk of cardiovascular disease (CVD). It is unclear whether HCV treatment affects risk of CVD among patients infected with HCV. We assessed the incidence and risk of CVD among insured patients with HCV infection and evaluated if HCV treatment was associated with reduced CVD risk. METHODS: This retrospective cohort study used MarketScan Commercial and Medicare Supplement databases. Patients newly diagnosed with HCV (vs. patients without HCV) between January 2008 and August 2015 were categorized by treatment (none, insufficient, or minimum effective) based on receipt and duration of anti-HCV treatments. After propensity score matching, time-dependent Cox proportional hazards models were used to compare CVD risk between patients with HCV versus without and between patients with HCV by treatment type and duration. RESULTS: HCV was associated with 13% increased risk of developing CVD overall (adjusted hazard ratio [aHR] 95% CI 1.26-1.35) and with 13% (aHR 1.07-1,18), 9% (aHR 1.03-1.15), and 32% (aHR 1.24-1.40) significantly increased risks of developing coronary artery disease, cerebrovascular disease, and peripheral vascular disease, respectively. Among patients with HCV, compared with no treatment, receipt of minimum effective treatment was associated with 24% decreased risk of CVD, and receipt of insufficient treatment was associated with 14% decreased risk of CVD. CONCLUSIONS: Individuals chronically infected with HCV had a higher incidence of CVD. Among patients with HCV, receipt of antiviral treatment for HCV was associated with decreased risk of CVD.

Hepatitis C Cascade of Care in the Direct-Acting Antivirals Era: A Meta-Analysis.

INTRODUCTION: The hepatitis C virus (HCV) epidemic remains a public health problem worldwide. A systematic review and meta-analysis were conducted to provide evidence of outcomes attained across the HCV care cascade in the era of direct-acting antivirals. METHODS: Studies from North America, Europe, and Australia (January 2014 through March 2021) reporting on HCV care cascade outcomes (screening to cure) were included. When calculating the proportions of individuals completing each step, the numerator for Steps 1-8 was the number of individuals completing each step; the denominator was the number of individuals completing the previous step for Steps 1-3 and Step 3 for Steps 4-8. In 2022, random effects meta-analyses were conducted to estimate pooled proportions with 95% CIs. RESULTS: Sixty-five studies comprising 7,402,185 individuals were identified. Among individuals with positive HCV ribonucleic acid test results, 62% (95% CI=55%, 70%) attended their first care appointment, 41% (95% CI=37%, 45%) initiated treatment, 38% (95% CI=29%, 48%) completed treatment, and 29% (95% CI=25%, 33%) achieved cure. HCV screening rates were 43% (95% CI=22%, 66%) in prisons or jails and 20% (95% CI=11%, 31%) in emergency departments. Linkage to care rates were 62% (95% CI=46%, 75%) for homeless individuals and 26% (95% CI=22%, 31%) for individuals diagnosed in emergency departments. Cure rates were 51% (95% CI=30%, 73%) in individuals with substance use disorder and 17% (95% CI=17%, 17%) in homeless individuals. Cure rates were lowest in the U.S. DISCUSSION: Despite the availability of effective all-oral direct-acting antiviral therapies, persistent gaps remain across the HCV care cascade, especially among traditionally marginalized populations. Public health interventions targeting identified priority areas (e.g., emergency departments) may improve screening and healthcare retention of vulnerable populations with HCV infection (e.g., substance use disorder populations).

Impact of Direct-acting Antivirals on Hepatocellular Carcinoma and Mortality Among Medicaid Beneficiaries With Hepatitis C.

OBJECTIVE: The effects of all-oral direct-acting antivirals (DAAs) on hepatocellular carcinoma (HCC) and liver-related and all-cause mortality were assessed among Medicaid beneficiaries with hepatitis C virus (HCV). SUBJECTS: This cohort study used 2013-2019 Arizona Medicaid data from beneficiaries with HCV aged 18-64 years. METHODS: Risks of HCC and liver-related and all-cause mortality were compared between patients with or without DAA treatment, stratified by liver disease severity, using inverse probability of treatment weighted multivariable Cox proportional hazards regression models. RESULTS: Of 29,289 patients, 13.3% received DAAs. Among patients with compensated cirrhosis (CC), DAA treatment was associated with a lower risk of HCC [adjusted hazard ratio (aHR), 0.57; 95% CI, 0.37-0.88] compared with untreated patients although this association was not statistically significant for patients without cirrhosis or with decompensated cirrhosis (DCC). Compared with untreated patients, DAA treatment was associated with decreased risk of liver-related mortality for patients without cirrhosis (aHR: 0.02; 95% CI: 0.004-0.11), with CC (aHR: 0.09; 95% CI: 0.06-0.13), or with DCC (aHR: 0.20; 95% CI: 0.14-0.27). Similarly, compared with untreated patients, DAA treatment was associated with lower all-cause mortality for patients without cirrhosis (aHR: 0.10; 95% CI: 0.08-0.14), with CC (aHR: 0.07; 95% CI: 0.05-0.10), or with DCC (aHR: 0.15; 95% CI: 0.11-0.20). CONCLUSIONS: Among Arizona Medicaid beneficiaries with HCV, DAA treatment was associated with decreased risk of HCC for patients with CC but not for patients without cirrhosis or with DCC. However, DAA treatment was associated with decreased risk of liver-related and all-cause mortality.

Clinician barriers, perceptions, and practices in treating patients with hepatitis C virus and substance use disorder in the United States.

The likelihood of clinicians prescribing direct-acting antiviral (DAA) therapy for patients with chronic hepatitis C virus (HCV) and substance use disorder (SUD) was assessed via a survey emailed throughout the United States to clinicians (physicians and advanced practice providers) in gastroenterology, hepatology, and infectious disease specialties. Clinicians' perceived barriers and preparedness and actions associated with current and future DAA prescribing practices of HCV-infected patients with SUD were assessed. Of 846 clinicians presumably receiving the survey, 96 completed and returned it. Exploratory factor analyses of perceived barriers indicated a highly reliable (Cronbach alpha = 0.89) model with five factors: HCV stigma and knowledge, prior authorization requirements, and patient- clinician-, and system-related barriers. In multivariable analyses, after controlling for covariates, patient-related barriers (P < 0.01) and prior authorization requirements (P < 0.01) were negatively associated with the likelihood of prescribing DAAs. Exploratory factor analyses of clinician preparedness and actions indicated a highly reliable (Cronbach alpha = 0.75) model with three factors: beliefs and comfort level; action; and perceived limitations. Clinician beliefs and comfort levels were negatively associated with the likelihood of prescribing DAAs (P = 0.01). Composite scores of barriers (P < 0.01) and clinician preparedness and actions (P < 0.05) were also negatively associated with the intent to prescribe DAAs. Conclusion: These findings underscore the importance of addressing patient-related barriers and prior authorization requirements-significant problematic barriers-and improving clinicians' beliefs (e.g., medication-assisted therapy should be prescribed before DAAs) and comfort levels for treating patients with HCV and SUD to enhance treatment access for patients with both HCV and SUD.

Deprescribing Strategies for Opioids and Benzodiazepines with Emphasis on Concurrent Use: A Scoping Review.

While the Food and Drug Administration's black-box warnings caution against concurrent opioid and benzodiazepine (OPI-BZD) use, there is little guidance on how to deprescribe these medications. This scoping review analyzes the available opioid and/or benzodiazepine deprescribing strategies from the PubMed, EMBASE, Web of Science, Scopus, and Cochrane Library databases (01/1995-08/2020) and the gray literature. We identified 39 original research studies (opioids: n = 5, benzodiazepines: n = 31, concurrent use: n = 3) and 26 guidelines (opioids: n = 16, benzodiazepines: n = 11, concurrent use: n = 0). Among the three studies deprescribing concurrent use (success rates of 21-100%), two evaluated a 3-week rehabilitation program, and one assessed a 24-week primary care intervention for veterans. Initial opioid dose deprescribing rates ranged from (1) 10-20%/weekday followed by 2.5-10%/weekday over three weeks to (2) 10-25%/1-4 weeks. Initial benzodiazepine dose deprescribing rates ranged from (1) patient-specific reductions over three weeks to (2) 50% dose reduction for 2-4 weeks, followed by 2-8 weeks of dose maintenance and then a 25% reduction biweekly. Among the 26 guidelines identified, 22 highlighted the risks of co-prescribing OPI-BZD, and 4 provided conflicting recommendations on the OPI-BZD deprescribing sequence. Thirty-five states' websites provided resources for opioid deprescription and three states' websites had benzodiazepine deprescribing recommendations. Further studies are needed to better guide OPI-BZD deprescription.

Trends, characteristics, race, and ethnicity associated with nonadherence to antidepressants among breast cancer survivors with depression.

BACKGROUND: Breast cancer is the most diagnosed cancer in the United States, and half of breast cancer survivors experience major depressive disorders (hereafter depression). Healthcare Effectiveness Data and Information Set (HEDIS) quality measures evaluating depression treatment practices recommend uninterrupted antidepressant treatment for 3 months in the acute phase and 3 months in the continuation phase for the general population. However, little is known about the extent of and trends in antidepressant nonadherence among breast cancer survivors with depression, which may impact adherence to breast cancer treatment, potentially leading to breast cancer recurrence and other adverse outcomes. OBJECTIVE: To examine the trends and characteristics associated with antidepressant nonadherence among breast cancer survivors with depression in the United States. METHODS: We conducted cross-sectional analyses of Surveillance, Epidemiology, and End Results linked with Medicare data (2010-2019) for women with breast cancer and depression who newly initiated antidepressant use. Using HEDIS measures of nonadherence (ie, antidepressant prescription coverage ≤84 days of the 114-day acute phase or ≤180 days of the 231-day continuation phase), we calculated the annual crude prevalence of antidepressant nonadherence and examined trends using unadjusted logistic regression. Multivariable logistic regression identified characteristics associated with antidepressant nonadherence. RESULTS: Among 9,452 eligible breast cancer survivors with depression (aged ≥65 years = 84% and White race = 82%), the crude prevalence of antidepressant nonadherence decreased from 2010 to 2019 for both the acute (49% to 40%; Ptrend<0.001) and continuation (67% to 57%; Ptrend<0.001) phases. Factors significantly associated with higher odds of antidepressant nonadherence in both the acute and continuation phases included Black race (odds ratios [ORs] [95% CI] for the acute/continuation phases: 2.0 [1.7-2.4]/2.0 [1.7-2.3]) and Hispanic ethnicity (1.5 [1.1-1.9]/2.2 [1.6-2.9]) compared with White race; receiving the first antidepressant from an oncologist vs a psychiatrist (1.4 [1.1-1.8]/1.6 [1.2-2.0]); and using antidepressants not recommended for older adults by the Beers criteria (2.2 [1.6-2.9]/2.0 [1.4-2.7]). Factors associated with lower odds of antidepressant nonadherence in both phases included receiving lymph node dissection (0.7 [0.5-0.9]/0.7 [0.5-0.9]), receiving endocrine therapy (0.9 [0.8-0.9]/0.8 [0.7-0.9]), having a higher National Cancer Institute comorbid index (0.8 [0.7-0.8]/0.9 [0.8-0.9]), having a follow-up visit with a psychiatrist (0.9 [0.8-0.9]/0.9 [0.8-0.9]), and switching to different antidepressants (0.7 [0.6-0.8]/0.7 [0.7-0.8]). CONCLUSIONS: Despite antidepressant nonadherence prevalence decreasing from 2010 to 2019, over half of breast cancer survivors with depression and Medicare were nonadherent in the continuation phase. Patients with identified nonadherence risk factors may benefit from close monitoring and targeted interventions. DISCLOSURES: Wei-Hsuan Lo-Ciganic reported grants from the National Institute on Drug Abuse (R01DA044985 and R01DA050676), the National Institute on Aging (R21AG060308), the National Institute of Mental Health (R01MH121907), Merck Sharp & Dohme, Bristol Myers Squibb, the Richard King Mellon Foundation at the University of Pittsburgh, the Clinical and Translational Science Institute of the University of Florida, the Pharmaceutical Research and Manufacturers of America (PhRMA) Foundation, and the US Department of Veterans Affairs outside the submitted work; in addition, Wei-Hsuan Lo-Ciganic has a patent pending for U1195.70174US00. Haesuk Park reported grants from Bristol Myers Squibb/Pfizer Alliance American Thrombosis Investigator Initiated Research Program (ARISTA-USA) outside the submitted work. Juan M. Hincapie-Castillo reported grants from Merck outside the submitted work. Debbie Wilson reported grants from the National Institute on Drug Abuse, the National Institute on Aging, Merck Sharp & Dohme, and Bristol Myers Squibb outside the submitted work; and serving as an editorial board member for the Journal of Pharmacy Technology. Ching-Yuan Chang's contributions to this manuscript were made while at the University of Florida College of Pharmacy. Ching-Yuan Chang is currently employed by Vertex Pharmaceuticals, Inc. Vertex did not fund or have any involvement in this study or publication. Vakaramoko Diaby is currently employed by Otsuka, Inc. Otsuka did not fund or have any involvement in this study or publication. No other disclosures were reported.

Economic Impact of Universal Hepatitis C Virus Testing for Middle-Aged Adults Who Inject Drugs.

INTRODUCTION: The objective of this study was to estimate the economic impact of providing universal hepatitis C virus testing in commercially insured middle-aged persons who inject drugs in the U.S. METHODS: This study developed a dynamic 10-year economic model to project the clinical and economic outcomes associated with hepatitis C virus testing among middle-aged adult persons who inject drugs, from a payer's perspective. Costs related to hepatitis C virus testing, direct-acting antiviral, and liver-related outcomes between the (1) current hepatitis C virus testing rate (i.e., 8%) and (2) universal hepatitis C virus testing rate (i.e., 100%) were compared. Among patients testing positive, 21% of those without cirrhosis and 48% of those with cirrhosis were assumed to initiate direct-acting antivirals. Sensitivity analyses were performed to identify variables (e.g., direct-acting antiviral drug costs, hepatitis C virus testing costs, direct-acting antiviral treatment rate) influencing this study's conclusion. RESULTS: The model predicts that during the 10-year period, universal hepatitis C virus testing will cost an additional $242 per person who injects drugs to the payers' healthcare budgets compared with the current scenario. Sensitivity analyses showed values ranging from $1,656 additional costs to $1,085 cost savings across all varied parameters and scenarios. A total of 80% of the current direct-acting antiviral costs indicated that cost savings will be $383 per person who injects drugs. CONCLUSIONS: Universal hepatitis C virus testing among persons who inject drugs would not achieve cost savings within 10 years, with the cost of direct-acting antivirals contributing the most to the spending. To promote universal hepatitis C virus testing among persons who inject drugs, decreasing direct-acting antiviral costs and sustainable funding streams for hepatitis C virus testing should be considered.

Predictive Modeling for Suicide-Related Outcomes and Risk Factors among Patients with Pain Conditions: A Systematic Review.

Suicide is a leading cause of death in the US. Patients with pain conditions have higher suicidal risks. In a systematic review searching observational studies from multiple sources (e.g., MEDLINE) from 1 January 2000-12 September 2020, we evaluated existing suicide prediction models' (SPMs) performance and identified risk factors and their derived data sources among patients with pain conditions. The suicide-related outcomes included suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors. Among the 87 studies included (with 8 SPM studies), 107 suicide risk factors (grouped into 27 categories) were identified. The most frequently occurring risk factor category was depression and their severity (33%). Approximately 20% of the risk factor categories would require identification from data sources beyond structured data (e.g., clinical notes). For 8 SPM studies (only 2 performing validation), the reported prediction metrics/performance varied: C-statistics (n = 3 studies) ranged 0.67-0.84, overall accuracy(n = 5): 0.78-0.96, sensitivity(n = 2): 0.65-0.91, and positive predictive values(n = 3): 0.01-0.43. Using the modified Quality in Prognosis Studies tool to assess the risk of biases, four SPM studies had moderate-to-high risk of biases. This systematic review identified a comprehensive list of risk factors that may improve predicting suicidal risks for patients with pain conditions. Future studies need to examine reasons for performance variations and SPM's clinical utility.

Buprenorphine Use Trends Following Removal of Prior Authorization Policies for the Treatment of Opioid Use Disorder in 2 State Medicaid Programs.

Importance: State Medicaid programs have implemented initiatives to expand treatment coverage for opioid use disorder (OUD); however, some Medicaid programs still require prior authorizations (PAs) for filling buprenorphine prescriptions. Objective: To evaluate the changes in buprenorphine use for OUD among Medicaid enrollees in states that completely removed buprenorphine PA requirements. Design Setting and Participants: This retrospective cross-sectional study analyzed the immediate and trend changes on buprenorphine use during 2013 to 2020 associated with removal of PA requirements using a controlled interrupted time series analysis to account for autocorrelation. Data were collected from Medicaid State Drug Utilization Data for 2 states (California and Illinois) that completely removed a buprenorphine PA during the study period, and buprenorphine prescriptions for OUD treatment were identified among Medicaid enrollees. Main Outcomes and Measures: Quarterly total number of buprenorphine prescriptions for each state was calculated, and stratification analyses were conducted by dosage form (films and tablets). Results: Among the 2 state Medicaid programs (California and Illinois) that removed buprenorphine PAs, there was a total of 702 643 and 415 115 eligible buprenorphine prescription claims, respectively. After removing PA requirements for buprenorphine, there was an immediate increase that was not statistically significant (rate ratio [RR], 1.11; 95% CI, 0.76-1.61) in the number of all buprenorphine prescriptions in California and a statistically significant increase (RR, 6.99; 95% CI, 4.67-10.47) in the number of all buprenorphine prescriptions in Illinois relative to the change in the control states (Alabama, Florida, Idaho, Kansas, Mississippi, Nevada, South Dakota, and Wyoming). Additionally, there was a statistically significant decreasing trend in the number of all buprenorphine prescriptions in California (RR, 0.88; 95% CI, 0.82-0.94) and a statistically significant increasing trend in Illinois (RR, 1.11; 95% CI, 1.05-1.19) relative to the trend in control states. Conclusions and Relevance: In this cross-sectional study, removal of buprenorphine PA requirements was associated with a statistically significant increase in the number of buprenorphine prescription fills among Medicaid populations in 1 of the 2 included states.

Evaluation of Cough Medication Use Patterns in Ambulatory Care Settings in the United States: 2003-2018.

Using 2003−2018 National Ambulatory Medical Care Survey data for office-based visits and 2003−2018 National Hospital Ambulatory Medical Care Survey data for emergency department (ED) visits, we conducted cross-sectional analyses to examine cough medication (CM) use trends in the United States (US) ambulatory care settings. We included adult (≥18 years) patient visits with respiratory-infection-related or non-infection-related cough as reason-for-visit or diagnosis without malignant cancer or benign respiratory tumor diagnoses. Using multivariable logistic regressions, we examined opioid antitussive, benzonatate, dextromethorphan-containing antitussive, and gabapentinoid use trends. From 2003−2005 to 2015−2018, opioid antitussive use decreased in office-based visits (8.8% to 6.4%, Ptrend = 0.03) but remained stable in ED visits (6.3% to 5.9%, Ptrend = 0.99). In both settings, hydrocodone-containing antitussive use declined over 50%. Benzonatate use more than tripled (office-based:1.6% to 4.8%; ED:1.5% to 8.0%; both Ptrend < 0.001). Dextromethorphan-containing antitussive use increased in ED visits (1.8% to 2.6%, Ptrend = 0.003) but stayed unchanged in office-based visits (3.8% to 2.7%; Ptrend = 0.60). Gabapentinoid use doubled in office-based visits (1.1% in 2006−2008 to 2.4% in 2015−2018, Ptrend < 0.001) but was negligible in ED visits. In US office-based and ED ambulatory care settings, hydrocodone-containing antitussive use substantially declined from 2003 to 2018, while benzonatate use more than tripled, and dextromethorphan-containing antitussive and gabapentinoid use remained low (<3%).

Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study.

BACKGROUND: Little is known about whether machine-learning algorithms developed to predict opioid overdose using earlier years and from a single state will perform as well when applied to other populations. We aimed to develop a machine-learning algorithm to predict 3-month risk of opioid overdose using Pennsylvania Medicaid data and externally validated it in two data sources (ie, later years of Pennsylvania Medicaid data and data from a different state). METHODS: This prognostic modelling study developed and validated a machine-learning algorithm to predict overdose in Medicaid beneficiaries with one or more opioid prescription in Pennsylvania and Arizona, USA. To predict risk of hospital or emergency department visits for overdose in the subsequent 3 months, we measured 284 potential predictors from pharmaceutical and health-care encounter claims data in 3-month periods, starting 3 months before the first opioid prescription and continuing until loss to follow-up or study end. We developed and internally validated a gradient-boosting machine algorithm to predict overdose using 2013-16 Pennsylvania Medicaid data (n=639 693). We externally validated the model using (1) 2017-18 Pennsylvania Medicaid data (n=318 585) and (2) 2015-17 Arizona Medicaid data (n=391 959). We reported several prediction performance metrics (eg, C-statistic, positive predictive value). Beneficiaries were stratified into risk-score subgroups to support clinical use. FINDINGS: A total of 8641 (1·35%) 2013-16 Pennsylvania Medicaid beneficiaries, 2705 (0·85%) 2017-18 Pennsylvania Medicaid beneficiaries, and 2410 (0·61%) 2015-17 Arizona beneficiaries had one or more overdose during the study period. C-statistics for the algorithm predicting 3-month overdoses developed from the 2013-16 Pennsylvania training dataset and validated on the 2013-16 Pennsylvania internal validation dataset, 2017-18 Pennsylvania external validation dataset, and 2015-17 Arizona external validation dataset were 0·841 (95% CI 0·835-0·847), 0·828 (0·822-0·834), and 0·817 (0·807-0·826), respectively. In external validation datasets, 71 361 (22·4%) of 318 585 2017-18 Pennsylvania beneficiaries were in high-risk subgroups (positive predictive value of 0·38-4·08%; capturing 73% of overdoses in the subsequent 3 months) and 40 041 (10%) of 391 959 2015-17 Arizona beneficiaries were in high-risk subgroups (positive predictive value of 0·19-1·97%; capturing 55% of overdoses). Lower risk subgroups in both validation datasets had few individuals (≤0·2%) with an overdose. INTERPRETATION: A machine-learning algorithm predicting opioid overdose derived from Pennsylvania Medicaid data performed well in external validation with more recent Pennsylvania data and with Arizona Medicaid data. The algorithm might be valuable for overdose risk prediction and stratification in Medicaid beneficiaries. FUNDING: National Institute of Health, National Institute on Drug Abuse, National Institute on Aging.