Association between Opioid-Benzodiazepine Trajectories and Injurious Fall Risk among US Medicare Beneficiaries.

Background/Objectives: Concurrent opioid (OPI) and benzodiazepine (BZD) use may exacerbate injurious fall risk (e.g., falls and fractures) compared to no use or use alone. Yet, patients may need concurrent OPI-BZD use for co-occurring conditions (e.g., pain and anxiety). Therefore, we examined the association between longitudinal OPI-BZD dosing patterns and subsequent injurious fall risk. Methods: We conducted a retrospective cohort study including non-cancer fee-for-service Medicare beneficiaries initiating OPI and/or BZD in 2016-2018. We identified OPI-BZD use patterns during the 3 months following OPI and/or BZD initiation (i.e., trajectory period) using group-based multi-trajectory models. We estimated the time to first injurious falls within the 3-month post-trajectory period using inverse-probability-of-treatment-weighted Cox proportional hazards models. Results: Among 622,588 beneficiaries (age ≥ 65 = 84.6%, female = 58.1%, White = 82.7%; having injurious falls = 0.45%), we identified 13 distinct OPI-BZD trajectories: Group (A): Very-low OPI-only (early discontinuation) (44.9% of the cohort); (B): Low OPI-only (rapid decline) (15.1%); (C): Very-low OPI-only (late discontinuation) (7.7%); (D): Low OPI-only (gradual decline) (4.0%); (E): Moderate OPI-only (rapid decline) (2.3%); (F): Very-low BZD-only (late discontinuation) (11.5%); (G): Low BZD-only (rapid decline) (4.5%); (H): Low BZD-only (stable) (3.1%); (I): Moderate BZD-only (gradual decline) (2.1%); (J): Very-low OPI (rapid decline)/Very-low BZD (late discontinuation) (2.9%); (K): Very-low OPI (rapid decline)/Very-low BZD (increasing) (0.9%); (L): Very-low OPI (stable)/Low BZD (stable) (0.6%); and (M): Low OPI (gradual decline)/Low BZD (gradual decline) (0.6%). Compared with Group (A), six trajectories had an increased 3-month injurious falls risk: (C): HR = 1.78, 95% CI = 1.58-2.01; (D): HR = 2.24, 95% CI = 1.93-2.59; (E): HR = 2.60, 95% CI = 2.18-3.09; (H): HR = 2.02, 95% CI = 1.70-2.40; (L): HR = 2.73, 95% CI = 1.98-3.76; and (M): HR = 1.96, 95% CI = 1.32-2.91. Conclusions: Our findings suggest that 3-month injurious fall risk varied across OPI-BZD trajectories, highlighting the importance of considering both dose and duration when assessing injurious fall risk of OPI-BZD use among older adults.

Machine Learning - Based Bleeding Risk Predictions in Atrial Fibrillation Patients on Direct Oral Anticoagulants.

Importance: Accurately predicting major bleeding events in non-valvular atrial fibrillation (AF) patients on direct oral anticoagulants (DOACs) is crucial for personalized treatment and improving patient outcomes, especially with emerging alternatives like left atrial appendage closure devices. The left atrial appendage closure devices reduce stroke risk comparably but with significantly fewer non-procedural bleeding events. Objective: To evaluate the performance of machine learning (ML) risk models in predicting clinically significant bleeding events requiring hospitalization and hemorrhagic stroke in non-valvular AF patients on DOACs compared to conventional bleeding risk scores (HAS-BLED, ORBIT, and ATRIA) at the index visit to a cardiologist for AF management. Design: Prognostic modeling with retrospective cohort study design using electronic health record (EHR) data, with clinical follow-up at one-, two-, and five-years. Setting: University of Pittsburgh Medical Center (UPMC) system. Participants: 24,468 non-valvular AF patients aged ≥18 years treated with DOACs, excluding those with prior history of significant bleeding, other indications for DOACs, on warfarin or contraindicated to DOACs. Exposures: DOAC therapy for non-valvular AF. Main Outcomes and Measures: The primary endpoint was clinically significant bleeding requiring hospitalization within one year of index visit. The models incorporated demographic, clinical, and laboratory variables available in the EHR at the index visit. Results: Among 24,468 patients, 553 (2.3%) had bleeding events within one year, 829 (3.5%) within two years, and 1,292 (5.8%) within five years of index visit. We evaluated multivariate logistic regression and ML models including random forest, classification trees, k-nearest neighbor, naive Bayes, and extreme gradient boosting (XGBoost) which modestly outperformed HAS-BLED, ATRIA, and ORBIT scores in predicting clinically significant bleeding at 1-year follow-up. The best performing model (random forest) showed area under the curve (AUC-ROC) 0.76 (0.70-0.81), G-Mean score of 0.67, net reclassification index 0.14 compared to 0.57 (0.50-0.63), G-Mean score of 0.57 for HASBLED score, p-value for difference <0.001. The ML models had improved performance compared to conventional risk across time-points of 2-year and 5-years and within the subgroup of hemorrhagic stroke. SHAP analysis identified novel risk factors including measures from body mass index, cholesterol profile, and insurance type beyond those used in conventional risk scores. Conclusions and Relevance: Our findings demonstrate the superior performance of ML models compared to conventional bleeding risk scores and identify novel risk factors highlighting the potential for personalized bleeding risk assessment in AF patients on DOACs.

An explainable machine learning framework for predicting the risk of buprenorphine treatment discontinuation for opioid use disorder among commercially insured individuals.

OBJECTIVES: Buprenorphine is an effective evidence-based medication for opioid use disorder (OUD). Yet premature discontinuation undermines treatment effectiveness, increasing the risk of mortality and overdose. We developed and evaluated a machine learning (ML) framework for predicting buprenorphine care discontinuity within 12 months following treatment initiation. METHODS: This retrospective study used United States (US) 2018-2021 MarketScan commercial claims data of insured individuals aged 18-64 who initiated buprenorphine between July 2018 and December 2020 with no buprenorphine prescriptions in the previous six months. We measured buprenorphine prescription discontinuation gaps of ≥30 days within 12 months of initiating treatment. We developed predictive models employing logistic regression, decision tree classifier, random forest, extreme gradient boosting, Adaboost, and random forest-extreme gradient boosting ensemble. We applied recursive feature elimination with cross-validation to reduce dimensionality and identify the most predictive features while maintaining model robustness. For model validation, we used several statistics to evaluate performance, such as C-statistics and precision-recall curves. We focused on two distinct treatment stages: at the time of treatment initiation and one and three months after treatment initiation. We employed SHapley Additive exPlanations (SHAP) analysis that helped us explain the contributions of different features in predicting buprenorphine discontinuation. We stratified patients into risk subgroups based on their predicted likelihood of treatment discontinuation, dividing them into decile subgroups. Additionally, we used a calibration plot to analyze the reliability of the models. RESULTS: A total of 30,373 patients initiated buprenorphine and 14.98% (4551) discontinued treatment. C-statistic varied between 0.56 and 0.76 for the first-stage models including patient-level demographic and clinical variables. Inclusion of proportion of days covered (PDC) measured after one month and three months following treatment initiation significantly increased the models' discriminative power (C-statistics: 0.60 to 0.82). Random forest (C-statistics: 0.76, 0.79 and 0.82 with baseline predictors, one-month PDC and three-months PDC, respectively) outperformed other ML models in discriminative performance in all stages (C-statistics: 0.56 to 0.77). Most influential risk factors of discontinuation included early stage medication adherence, age, and initial days of supply. CONCLUSION: ML algorithms demonstrated a good discriminative power in identifying patients at higher risk of buprenorphine care discontinuity. The proposed framework may help healthcare providers optimize treatment strategies and deliver targeted interventions to improve buprenorphine care continuity.

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.

Diabetes-related complications, glycemic levels, and healthcare utilization outcomes after therapeutic inertia in type 2 diabetes mellitus.

AIMS: To assess diabetes-related complications, glycemic levels, and healthcare utilization 12 months after exposure to therapeutic inertia among patients with type 2 diabetes mellitus (T2D). METHODS: This retrospective cohort study analyzed data from the OneFlorida Clinical Research Consortium (electronic health records from Florida practices/clinics). The cohort included adult patients (≥18 years old) with T2D who had an HbA1c≥7.0% (53 mmol/mol) recorded from January 1, 2014-September 30, 2019. Therapeutic inertia (exposed vs. not exposed) was evaluated during the six months following HbA1c≥7.0% (53 mmol/mol). The outcomes assessed during the 12-month follow-up period included diabetes-related complications (continuous Diabetes Complications and Severity Index (DCSI)), glycemic levels (continuous follow-up HbA1c lab), and healthcare utilization counts. We analyzed data using multivariable regression models, adjusting for covariates. RESULTS: The cohort included 26,881 patients with T2D (58.94% White race, 49.72% female, and mean age of 58.82 (SD=13.09)). After adjusting for covariates, therapeutic inertia exposure was associated with lower DCSI (estimate=-0.14 (SE=0.03), p < 0.001), higher follow-up HbA1c (estimate=0.14 (SE=0.04), p < 0.001), and lower rates of ambulatory visits (rate ratio=0.79, 95% CI=0.75-0.82). CONCLUSIONS: Findings communicate the clinical practice implications and public health implications for combating therapeutic inertia in diabetes care.

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).

Association between first-line antidepressant use and risk of dementia in older adults: a retrospective cohort study.

BACKGROUND: Prior studies suggested that antidepressant use is associated with an increased risk of dementia compared to no use, which is subject to confounding by indication. We aimed to compare the dementia risk among older adults with depression receiving first-line antidepressants (i.e., SSRI/SNRI) versus psychotherapy, which is also considered the first-line therapy for depression. METHODS: This retrospective cohort study was conducted using the US Medical Expenditure Panel Survey from 2010 to 2019. We included adults aged ≥ 50 years diagnosed with depression who initiated SSRI/SNRI or psychotherapy. We excluded patients with a dementia diagnosis before the first record of SSRI/SNRI use or psychotherapy. The exposure was the patient's receipt of SSRI/SNRI (identified from self-report questionnaires) or psychotherapy (identified from the Outpatient Visits or Office-Based Medical Provider Visits files). The outcome was a new diagnosis of dementia within 2 years (i.e., survey panel period) identified using ICD-9/ICD-10 codes from the Medical Conditions file. Using a multivariable logistic regression model, we reported adjusted odds ratios (aORs) with 95% confidence intervals (CIs). We also conducted subgroup analyses by patient sex, age group, race/ethnicity, severity of depression, combined use of other non-SSRI/SNRI antidepressants, and presence of underlying cognitive impairment. RESULTS: Among 2,710 eligible patients (mean age = 61 ± 8, female = 69%, White = 84%), 89% used SSRIs/SNRIs, and 11% received psychotherapy. The SSRI/SNRI users had a higher crude incidence of dementia than the psychotherapy group (16.4% vs. 11.8%), with an aOR of 1.36 (95% CI = 1.06-1.74). Subgroup analyses yielded similar findings as the main analyses, except no significant association for patients who were aged < 65 years (1.23, 95% CI = 0.93-1.62), male (1.34, 95% CI = 0.95-1.90), Black (0.76, 95% CI = 0.48-1.19), had a higher PHQ-2 (1.39, 95% CI = 0.90-2.15), and had underlying cognitive impairment (1.06, 95% CI = 0.80-1.42). CONCLUSIONS: Our findings suggested that older adults with depression receiving SSRIs/SNRIs were associated with an increased dementia risk compared to those receiving psychotherapy.

Trajectories of Pre-Exposure Prophylaxis (PrEP) Adherence Among Commercially Insured Individuals.

We used group-based trajectory models to identify four distinct trajectory patterns of adherence to pre-exposure prophylaxis (PrEP) among 20,696 users. Only 44.5% were consistently PrEP adherent, with younger age, being female, or having substance use disorder or depression associated with early discontinuation. Public health efforts are needed to improve PrEP adherence.

Association between first-line antidepressant use and risk of dementia in older adults: a retrospective cohort study.

Background: Prior studies suggested that antidepressant use is associated with an increased risk of dementia compared to no use, which is subject to confounding by indication. We aimed to compare the dementia risk among older adults with depression receiving first-line antidepressants (i.e., SSRI/SNRI) versus psychotherapy, which is also considered the first-line therapy for depression. Methods: This retrospective cohort study was conducted using the US Medical Expenditure Panel Survey from 2010 to 2019. We included adults aged ≥50 years diagnosed with depression who initiated SSRI/SNRI or psychotherapy. We excluded patients with a dementia diagnosis before the first record of SSRI/SNRI use or psychotherapy. The exposure was the patient's receipt of SSRI/SNRI (identified from self-report questionnaires) or psychotherapy (identified from the Outpatient Visits or Office-Based Medical Provider Visits files). The outcome was a new diagnosis of dementia within 2 years (i.e., survey panel period) identified using ICD-9/ICD-10 codes from the Medical Conditions file. Using a multivariable logistic regression model, we reported adjusted odds ratios (aORs) with 95% confidence intervals (CIs). We also conducted subgroup analyses by patient sex, age group, race, severity of depression, combined use of other non-SSRI/SNRI antidepressants, and presence of underlying cognitive impairment. Results: Among 2,710 eligible patients (mean age= 61±8, female=69%, white=84%), 89% used SSRIs/SNRIs, and 11% received psychotherapy. The SSRI/SNRI users had a higher crude incidence of dementia than the psychotherapy group (16.1% vs. 12.7%), with an aOR of 1.39 (95% CI=1.21-1.59). Subgroup analyses yielded similar findings as the main analyses, except no significant association for patients who were black (0.75, 95% CI=0.55-1.02), had a higher PHQ-2 (1.08, 95% CI=0.82-1.41), had concomitant non-SSRI/SNRI antidepressants (0.75, 95% CI=0.34-1.66), and had underlying cognitive impairment (0.84, 95% CI=0.66-1.05). Conclusions: Our findings suggested that older adults with depression receiving SSRIs/SNRIs were associated with an increased dementia risk compared to those receiving psychotherapy.

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.

Medication use and contextual factors associated with meeting guideline-based glycemic levels in diabetes among a nationally representative sample.

Introduction: Based on the long-lasting diabetes management challenges in the United States, the objective was to examine glycemic levels among a nationally representative sample of people with diabetes stratified by prescribed antihyperglycemic treatment regimens and contextual factors. Methods: This serial cross-sectional study used United States population-based data from the 2015 to March 2020 National Health and Nutrition Examination Surveys (NHANES). The study included non-pregnant adults (≥20 years old) with non-missing A1C and self-reported diabetes diagnosis from NHANES. Using A1C lab values, we dichotomized the outcome of glycemic levels into <7% versus ≥7% (meeting vs. not meeting guideline-based glycemic levels, respectively). We stratified the outcome by antihyperglycemic medication use and contextual factors (e.g., race/ethnicity, gender, chronic conditions, diet, healthcare utilization, insurance, etc.) and performed multivariable logistic regression analyses. Results: The 2042 adults with diabetes had a mean age of 60.63 (SE = 0.50), 55.26% (95% CI = 51.39-59.09) were male, and 51.82% (95% CI = 47.11-56.51) met guideline-based glycemic levels. Contextual factors associated with meeting guideline-based glycemic levels included reporting an "excellent" versus "poor" diet (aOR = 4.21, 95% CI = 1.92-9.25) and having no family history of diabetes (aOR = 1.43, 95% CI = 1.03-1.98). Contextual factors associated with lower odds of meeting guideline-based glycemic levels included taking insulin (aOR = 0.16, 95% CI = 0.10-0.26), taking metformin (aOR = 0.66, 95% CI = 0.46-0.96), less frequent healthcare utilization [e.g., none vs. ≥4 times/year (aOR = 0.51, 95% CI = 0.27-0.96)], being uninsured (aOR = 0.51, 95% CI = 0.33-0.79), etc. Discussion: Meeting guideline-based glycemic levels was associated with medication use (taking vs. not taking respective antihyperglycemic medication classes) and contextual factors. The timely, population-based estimates can inform national efforts to optimize diabetes management.

Trends in Prescribing of Non-steroidal Anti-inflammatory Medications in the US Ambulatory Care Setting From 2006 to 2016.

While opioid prescribing has significantly decreased from a peak in 2012, less is known about the national utilization of non-opioid analgesics such as non-steroidal anti-inflammatory drugs (NSAIDs) and acetaminophen (APAP) in the context of the opioid crisis. The objective of this study is to characterize the prescribing trends of NSAIDs and APAP in the US ambulatory care setting. We conducted repeated cross-sectional analyses using the 2006-2016 National Ambulatory Medical Care Survey. NSAID-involved visits were defined as patient visits among adults in which NSAIDs were ordered, supplied, administered, or continued. We used similarly-defined APAP visits as a referent group for context. After excluding aspirin and other NSAID/APAP combination products containing opioids, we calculated the annual proportion of NSAID-involved visits among all ambulatory visits. We conducted trend analyses using multivariable logistic regression adjusted for years, patient, and prescriber characteristics. From 2006 to 2016, there were 775.7 million NSAID-involved visits and 204.3 million APAP-involved visits. Most NSAIDs-involved visits were from patients aged 46-64 years (39.6%), female (60.4%), White (83.2%), and having commercial insurance (49.0%). There were significant increasing trends for the proportion of NSAID-involved visits (8.1-9.6%) and APAP-involved visits (1.7-2.9%) (both P < .0001). We observed an overall increase in NSAID and APAP-involved visits in US ambulatory care settings from 2006 to 2016. This trend may be attributed to decreasing opioid prescribing and raises safety concerns related to acute or chronic NSAID and APAP use. PERSPECTIVE: This study shows an overall increasing trend in NSAID use reported in nationally representative ambulatory care visits in the United States. This increase coincides with previously reported significant decreases in opioid analgesic use, particularly after 2012. Given the safety concerns related to chronic or acute NSAID use, there is a need to continue monitoring the use trends of this class of medication.

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.

Trajectories of adherence to extended treatment with warfarin and risks of recurrent venous thromboembolism and major bleeding.

Background: Little is published about warfarin therapy adherence patterns beyond 6 months of initial anticoagulant treatment and their association with effectiveness and safety for patients with venous thromboembolism (VTE). Objectives: To compare the risks of recurrent VTE and major bleeding during extended treatment between adherence patterns using MarketScan Commercial and Medicare Supplemental databases (2013-2019). Methods: In a retrospective cohort study, we included patients with incident VTE who completed an initial 6-month anticoagulant treatment and received either warfarin or no extended therapy. Group-based trajectory models were used to identify distinct extended treatment trajectories. Associations between the trajectories and risk of hospitalization due to recurrent VTE and major bleeding were assessed using inverse probability treatment-weighted Cox proportional hazards models. Results: Compared with no extended treatment, consistently high warfarin adherence was associated with a significantly decreased risk of hospitalization due to recurrent VTE (hazard ratio [HR] = 0.23; 95% CI, 0.12-0.45), but gradually (HR = 0.29; 95CI, 0.08-1.06) or rapidly declining (HR = 0.14; 95% CI, 0.02-1.24) adherence showed no association with the risk of hospitalization due to recurrent VTE. Compared with no extended treatment, warfarin extended therapy was associated with an increased risk of hospitalization due to major bleeding regardless of adherence patterns (consistently high: HR = 2.08; 95% CI, 1.18-3.64, gradually declining: HR = 2.10; 95% CI, 0.74-5.95, and rapidly declining: HR = 9.19; 95% CI, 4.38-19.29). However, compared with rapidly declining adherence, consistently high (HR = 0.23; 95% CI, 0.11-0.47) and gradually declining (HR = 0.23; 95% CI, 0.08-0.64) adherence were associated with decreased risk of hospitalization due to major bleeding. Conclusion: The findings indicated that consistently high adherence to extended warfarin treatment was associated with a decreased risk of hospitalization due to recurrent VTE but an increased risk of hospitalization due to major bleeding compared with no extended treatment.

Trajectories of Oral Anticoagulation Adherence and Associated Clinical Outcomes During Long-Term Anticoagulation Among Medicare Beneficiaries With Venous Thromboembolism.

BACKGROUND: Little is known about anticoagulation medication nonadherence patterns impacting effectiveness and safety outcomes in clinical practice. OBJECTIVE: We identified adherence trajectories of extended therapy with direct-acting oral anticoagulants (DOACs) and warfarin after 6 months initial anticoagulant therapy among Medicare beneficiaries with venous thromboembolism (VTE). We further assessed the associated recurrent VTE and major bleeding risks. METHODS: Using group-based trajectory models, this retrospective cohort study identified distinct beneficiary subgroups with similar adherence patterns of extended-phase anticoagulant treatment (DOACs or warfarin) for patients with VTE who completed 6 months of initial anticoagulant treatment. We examined associations between adherence trajectories and risks of recurrent VTE and major bleeding using inverse probability treatment weighted Cox proportional hazards models. RESULTS: Compared with no extended treatment, consistently high DOAC adherence was associated with decreased recurrent VTE risk (hazard ratio [HR] = 0.33, 95% confidence interval [CI] = 0.21-0.51) without increased major bleeding risk, and consistently high warfarin adherence was associated with decreased recurrent VTE risk (HR = 0.62, 95% CI = 0.40-0.95) and increased major bleeding risk (HR = 1.64, 95% CI = 1.12-2.41). Gradually declining adherence to DOACs (HR = 1.80, 95% CI = 1.07-3.03) or warfarin (HR = 2.34, 95% CI = 1.57-3.47) was associated with increased bleeding risk with no change in recurrent VTE risk. CONCLUSION AND RELEVANCE: This real-world evidence suggests persistently adhering to extended DOAC therapy is associated with lower recurrent VTE risk without increasing major bleeding among Medicare beneficiaries with VTE. Persistently adhering to extended warfarin therapy was associated with lower recurrent VTE risk but higher major bleeding risk.