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AimsTo use electronic health record data from real-world clinical practice to assess demographics, clinical characteristics and disease burden of adults with type 1 diabetes (T1D) in the United States.Materials and methodsRetrospective observational study of adults with T1D for ≥24 months at their first visit with a T1D diagnosis code ("index date") between July 2014 and June 2016 in the Optum Humedica database. Demographic characteristics, acute complications (severe hypoglycaemia [SH], diabetic ketoacidosis [DKA]), microvascular complications, cardiovascular (CV) events and health care resource utilization during the 12 months before the index date ("baseline period") were compared between patients with optimal versus suboptimal glycaemic control (glycated haemoglobin [HbA1c] 30 000 adults with T1D showed that individuals with suboptimal versus optimal glycaemic control differed significantly in terms of health care coverage, comorbidities, diabetes-related complications, health care utilization and CV risk factors. However, suboptimal control was not associated with increased risk of CV outcomes.

Introduction: HIV-1 infection leads to chronic inflammation and to an increased risk of non-AIDS mortality. Our objective was to determine whether AIDS-defining events (ADEs) were associated with increased overall and cause-specific non-AIDS related mortality after antiretroviral therapy (ART) initiation. Methods: We included HIV treatment-naive adults from the Antiretroviral Therapy Cohort Collaboration (ART-CC) who initiated ART from 1996 to 2014. Causes of death were assigned using the Coding Causes of Death in HIV (CoDe) protocol. The adjusted hazard ratio (aHR) for overall and cause-specific non-AIDS mortality among those with an ADE (all ADEs, tuberculosis (TB), Pneumocystis jiroveci pneumonia (PJP), and non-Hodgkin's lymphoma (NHL)) compared to those without an ADE was estimated using a marginal structural model. Results: The adjusted hazard of overall non-AIDS mortality was higher among those with any ADE compared to those without any ADE (aHR 2.21, 95% confidence interval (CI) 2.00 to 2.43). The adjusted hazard of each of the cause-specific non-AIDS related deaths were higher among those with any ADE compared to those without, except metabolic deaths (malignancy aHR 2.59 (95% CI 2.13 to 3.14), accident/suicide/overdose aHR 1.37 (95% CI 1.05 to 1.79), cardiovascular aHR 1.95 (95% CI 1.54 to 2.48), infection aHR (95% CI 1.68 to 2.81), hepatic aHR 2.09 (95% CI 1.61 to 2.72), respiratory aHR 4.28 (95% CI 2.67 to 6.88), renal aHR 5.81 (95% CI 2.69 to 12.56) and central nervous aHR 1.53 (95% CI 1.18 to 5.44)). The risk of overall and cause-specific non-AIDS mortality differed depending on the specific ADE of interest (TB, PJP, NHL). Conclusions: In this large multi-centre cohort collaboration with standardized assignment of causes of death, non-AIDS mortality was twice as high among patients with an ADE compared to without an ADE. However, non-AIDS related mortality after an ADE depended on the ADE of interest. Although there may be unmeasured confounders, these findings suggest that a common pathway may be independently driving both ADEs and NADE mortality. While prevention of ADEs may reduce subsequent death due to NADEs following ART initiation, modification of risk factors for NADE mortality remains important after ADE survival. Keywords: AIDS-defining events; non-AIDS mortality; tuberculosis; Pneumocystis jiroveci pneumonia; non-Hodgkin's lymphoma; marginal structural model, 1 | INTRODUCTION In the era of antiretroviral therapy (ART), there have been striking decreases in acquired immune deficiency syndrome (AIDS)-related mortality [1-3] and prolongation of life expectancy [4-7] for [...]

Background: Hypersensitivity reaction (HSR) and hepatotoxicity are rare, but potentially serious side-effects of antiretroviral use. Objective: To investigate discontinuations due to HSR, hepatotoxicity or other reasons among users of dolutegravir (DTG) vs. raltegravir (RAL) or elvitegravir (EVG) in the EuroSIDA cohort. Methods: We compared individuals ≥18 years and starting combination antiretroviral therapy (ART, ≥3 drugs) with DTG vs. RAL or EVG, with or without abacavir (ABC), between January 16, 2014 and January 23, 2019. Discontinuations due to serious adverse events (SAEs) were independently reviewed. Results: Altogether 4366 individuals started 5116 ART regimens including DTG, RAL, or EVG, contributing 9180 person-years of follow-up (PYFU), with median follow-up 1.6 (interquartile range 0.7–2.8) years per treatment episode. Of these, 3074 (60.1%) used DTG (1738 with ABC, 1336 without) and 2042 (39.9%) RAL or EVG (286 with ABC, 1756 without). 1261 (24.6%) INSTI episodes were discontinued, 649 of the DTG-containing regimens (discontinuation rate 115, 95% CI 106–124/1000 PYFU) and 612 RAL or EVG-containing regimens (173, CI 160–188/1000 PYFU). After independent review, there were five HSR discontinuations, two for DTG (one with and one without ABC, discontinuation rate 0.35, CI 0.04–1.28/1000 PYFU), and three for RAL or EVG without ABC (0.85, CI 0.18–2.48/1000 PYFU). There was one hepatotoxicity discontinuation on DTG with ABC (discontinuation rate 0.18, CI 0.00–0.99/1000 PYFU). Conclusion: During 5 years of observations in the EuroSIDA cohort independently reviewed discontinuations due to HSR or hepatotoxicity were very rare, indicating a low rate of SAEs. [ABSTRACT FROM AUTHOR]

Abstract Background Available evidence suggests that smokers have a lower propensity than others to use primary care services. But previous studies have incorporated only limited adjustment for confounding and mediating factors such as income, access to services and health status. We used data from a large prospective cohort study (the 45 and Up Study), linked to administrative claims data, to quantify the relationship between smoking status and use of primary care services, including specific preventive services, in a contemporary Australian population. Methods Baseline questionnaire data from the 45 and Up Study were linked to administrative claims (Medicare) data for the 12-month period following study entry. The main outcome measures were Medicare benefit claimed for unreferred services, out-of-pocket costs (OOPC) paid, and claims for specific preventive services (immunisations, health assessments, chronic disease management services, PSA tests and Pap smears). Rate ratios with 95% confidence intervals were estimated using a hierarchical series of models, adjusted for predisposing, access- and health-related factors. Separate hurdle (two part) regression models were constructed for Medicare benefit and OOPC. Poisson models with robust error variance were used to model use of each specific preventive service. Results Participants included 254,382 people aged 45 years and over of whom 7.3% were current smokers. After adjustment for predisposing, access- and health-related factors, current smokers were very slightly less likely to have claimed Medicare benefit than never smokers. Among those who claimed benefit, current smokers claimed similar total benefit, but recent quitters claimed significantly greater benefit, compared to never-smokers. Current smokers were around 10% less likely than never smokers to have paid any OOPC. Current smokers were 15-20% less likely than never smokers to use immunisations, Pap smears and prostate specific antigen tests. Conclusions Current smokers were less likely than others to use primary care services that incurred out of pocket costs, and specific preventive services. This was independent of a wide range of predisposing, access- and health-related factors, suggesting that smokers have a lower propensity to seek health care. Smokers may be missing out on preventive services from which they would differentially benefit.

Introduction: Although prostate cancer (PCa) incidence is lower in HIV+ men than in HIV− men, the usefulness of prostate‐specific antigen (PSA) screening in this population is not well defined and may have higher false negative rates than in HIV− men. We aimed to describe the kinetics and predictive value of PSA in HIV+ men. Methods: Men with PCa (n=21) and up to two matched controls (n=40) with prospectively stored plasma samples before PCa (or matched date in controls) were selected. Cases and controls were matched on date of first and last sample, age, region of residence and CD4 count at first sample date. Total PSA (tPSA), free PSA (fPSA), testosterone and sex hormone binding globulin (SHBG) were measured. Conditional logistic regression models investigated associations between markers and PCa. Sensitivity and specificity of using tPSA >4 µg/L to predict PCa was calculated. Mixed models were used to describe kinetics. Results: Sixty‐one men were included with a median six (IQR 2–9) years follow‐up. Time between last sample and PCa was seven (4–11) months. Cases and controls were well matched at first sample, with a median age of 51 (IQR 48–57) and CD4 of 437 (243–610) cells/mm[sup.3]. Median tPSA [2.8 (IQR: 1.6–4.6) and 0.8 (0.5–1.2) µg/L] and fPSA [0.4 (0.2–0.8) and 0.3 (0.2–0.4) µg/L] levels were higher in cases than controls at first sample. Both tPSA and fPSA increased significantly over time in cases (Figure 1), to a median at last sample of 6.1 (4.7–9.5) and 0.9 (0.6–1.3) µg/L, respectively, but were stable in controls, with a median at last sample of 0.8 (0.5–1.4) and 0.2 (0.2–0.4) µg/L (Figure). Higher levels of tPSA and fPSA were associated with higher odds of PCa at first sample [OR for 2‐fold higher 4.7 (CI: 1.7–12.9) and 5.4 (1.7–17.4)]. Elevated tPSA values in cases were detectable ≥5 years before PCa (p0.7). The most informative predictor of PCa was tPSA (AUC=0.9), followed by fPSA (0.8). Testosterone (AUC = 0.5) and SHBG (0.5) were poor predictors of PCa. Overall, tPSA level >4 µg/L had 99% specificity and 37% sensitivity. Performance was best in the year prior to PCa (specificity: 99%, sensitivity: 88%). Conclusions: PSA was highly predictive of PCa in HIV+ men. Our results indicate that PSA screening in HIV+ men may be useful, and further work is needed to identify potentially age‐related cut‐offs to maximize sensitivity and specificity to identify those for further evaluation at early stages of PCa., Figure 1: Total PSA (tPSA) and free PSA (fPSA) levels by time before diagnosis (or last sample date in controls) with superimposed loess curves. tPSA and fPSA levels were increasing [...]