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BackgroundAlcohol use disorders (AUD) can lead to poor health outcomes. Little is known about AUD treatment among persons with HIV (PWH). In an integrated health system in Northern California, 2014-2017, we compared AUD treatment rates between PWH with AUD and persons without HIV (PWoH) with AUD.MethodsUsing Poisson regression with GEE, we estimated prevalence ratios (PRs) comparing the annual probability of receiving AUD treatment (behavioral intervention or dispensed medication), adjusted for sociodemographics, psychiatric comorbidities, insurance type, and calendar year. Among PWH, we examined independent AUD treatment predictors using PRs adjusted for calendar year only.ResultsPWH with AUD (N = 633; 93% men, median age 49) were likelier than PWoH with AUD (N = 7006; 95% men, median age 52) to have depression (38% vs. 21%) and a non-alcohol substance use disorder (SUD, 48% vs. 25%) (both P

Objective: Despite recognition that people with HIV (PWH) are more vulnerable to sleep issues, there is limited understanding of clinically recognized sleep disorders in this population. Our objective was to evaluate the full spectrum of sleep disorder types diagnosed among PWH in care. Methods: We conducted a retrospective cohort study of PWH, and a comparator group of people without HIV (PWoH), in a large healthcare system. The incidence of clinically diagnosed sleep disorders was calculated using Poisson regression for three outcomes: any type of sleep disorder, insomnia, and sleep apnea. Incidence was compared between PWH and PWoH by computing the adjusted incidence rate ratio (aIRR), accounting for sleep disorder risk factors. Comparisons to PWoH were made for all PWH combined, then with PWH stratified by HIV management status (well‐managed HIV defined as being on antiretroviral therapy, HIV RNA <200 copies/mL, and CD4 count ≥500 cells/μL). Results: The study included 9076 PWH and 205 178 PWoH (mean age 46 years, 90% men). Compared with PWoH, sleep disorder incidence was greater among PWH overall [aIRR = 1.19, 95% confidence interval (CI): 1.12–1.26], particularly for insomnia (aIRR = 1.56, 95% CI: 1.45–1.67). Sleep apnea incidence was lower among PWH (aIRR = 0.90, 95% CI: 0.84–0.97). In HIV management subgroups, PWH without well‐managed HIV had lower sleep apnea incidence (vs. PWoH: aIRR = 0.79, 95% CI: 0.70–0.89) but PWH with well‐managed HIV did not (vs. PWoH: aIRR = 0.97, 95% CI: 0.89–1.06). Conclusions: PWH have high sleep disorder incidence, and insomnia is the most common clinical diagnosis. Lower sleep apnea incidence among PWH may reflect underdiagnosis in those with sub‐optimally treated HIV and will be important to investigate further. [ABSTRACT FROM AUTHOR]

Background: With extended lifespans for people with human immunodeficiency virus (PWH), there is a corresponding increased burden of chronic illnesses, including cancer. Our objective was to estimate the excess mortality among PWH with cancer compared with people without HIV (PWoH), accounting for the higher background mortality in the general PWH population., Methods: We identified 39,000 PWH and 387,767 demographically matched PWoH in three integrated healthcare systems from 2000 to 2016. We estimated excess mortality among PWH with cancer, computed as the cancer mortality rate difference-in-difference comparing PWH and PWoH. We evaluated five cancer groups: any cancer; virus-, human papillomavirus-, and Epstein-Barr virus -related cancers; virus-unrelated cancers, and common individual cancers. We fitted a multivariable additive Poisson model to estimate excess mortality among PWH with cancer., Results: PWH with any cancer had excess mortality compared with PWoH [41.3/1,000 person-years (py), 95% confidence interval (CI), 34.0-48.7]. The highest excess mortality was observed for Epstein-Barr virus-related cancers (63.2/1,000 py, 95% CI, 47.8-78.7), lung cancer (147.7/1,000 py, 95% CI, 41.1-254.3), and non-Hodgkin lymphoma (70.5/1,000 py, 95% CI, 51.4-89.6). Excess mortality among PWH was attenuated from 2009 to 2016, and PWH with cancer had no excess mortality 5 years after diagnosis., Conclusion: PWH in care may have excess mortality from certain cancer types, although disparities may have attenuated over time and do not persist beyond 5 years after diagnosis., Impact: Findings may guide improved clinical practice and suggest further research is needed to investigate whether cancer treatment or other factors contribute to mortality disparities for PWH with cancer., (©2024 American Association for Cancer Research.)

Background: Preexposure prophylaxis (PrEP) use remains limited and inequitable, and strategies are needed to improve PrEP provision in primary care., Methods: We conducted a cluster randomized trial at Kaiser Permanente, San Francisco, to evaluate the effectiveness of a clinical decision support intervention guided by an electronic health record (EHR)-based HIV risk prediction model to improve PrEP provision. Primary care providers (PCPs) were randomized to usual care or intervention, with PCPs who provide care to people with HIV balanced between arms. PCPs in the intervention arm received an EHR-based staff message with prompts to discuss HIV prevention and PrEP before upcoming in-person or video visits with patients whose predicted 3-year HIV risk was above a prespecified threshold. The main study outcome was initiation of PrEP care within 90 days, defined as PrEP discussions, referrals, or prescription fills., Results: One hundred twenty-one PCPs had 5051 appointments with eligible patients (2580 usual care; 2471 intervention). There was a nonsignificant increase in initiation of PrEP care in the intervention arm (6.0% vs 4.5%, HR 1.32, 95% CI: 0.84 to 2.1). There was a significant interaction by HIV provider status, with an intervention HR of 2.59 (95% CI: 1.30 to 5.16) for HIV providers and 0.89 (95% CI: 0.59 to 1.35) for non-HIV providers (P-interaction <0.001)., Conclusion: An EHR-based intervention guided by an HIV risk prediction model substantially increased initiation of PrEP care among patients of PCPs who also care for people with HIV. Higher-intensity interventions may be needed to improve PrEP provision among PCPs less familiar with PrEP and HIV care., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)