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Medication adherence plays an important role in optimizing the outcomes of many treatment and preventive regimens in chronic illness. Self-report is the most common method for assessing adherence behavior in research and clinical care, but there are questions about its validity and precision. The NIH Adherence Network assembled a panel of adherence research experts working across various chronic illnesses to review self-report medication adherence measures and research on their validity. Self-report medication adherence measures vary substantially in their question phrasing, recall periods, and response items. Self-reports tend to overestimate adherence behavior compared with other assessment methods and generally have high specificity but low sensitivity. Most evidence indicates that self-report adherence measures show moderate correspondence to other adherence measures and can significantly predict clinical outcomes. The quality of self-report adherence measures may be enhanced through efforts to use validated scales, assess the proper construct, improve estimation, facilitate recall, reduce social desirability bias, and employ technologic delivery. Self-report medication adherence measures can provide actionable information despite their limitations. They are preferred when speed, efficiency, and low-cost measures are required, as is often the case in clinical care.

Background. Some human immunodeficiency virus (HIV)–infected individuals initiating combination antiretroviral therapy (cART) with low CD4 counts achieve viral suppression but not CD4 cell recovery. We aimed to identify (1) risk factors for failure to achieve CD4 count >200 cells/μL after 3 years of sustained viral suppression and (2) the association of the achieved CD4 count with subsequent mortality. Methods. We included treated HIV-infected adults from 2 large international HIV cohorts, who had viral suppression (≤500 HIV type 1 RNA copies/mL) for >3 years with CD4 count ≤200 cells/μL at start of the suppressed period. Logistic regression was used to identify risk factors for incomplete CD4 recovery (≤200 cells/μL) and Cox regression to identify associations with mortality. Results. Of 5550 eligible individuals, 835 (15%) did not reach a CD4 count >200 cells/μL after 3 years of suppression. Increasing age, lower initial CD4 count, male heterosexual and injection drug use transmission, cART initiation after 1998, and longer time from initiation of cART to start of the virally suppressed period were risk factors for not achieving a CD4 count >200 cells/μL. Individuals with CD4 ≤200 cells/μL after 3 years of viral suppression had substantially increased mortality (adjusted hazard ratio, 2.60; 95% confidence interval, 1.86–3.61) compared with those who achieved CD4 count >200 cells/μL. The increased mortality was seen across different patient groups and for all causes of death. Conclusions. Virally suppressed HIV-positive individuals on cART who do not achieve a CD4 count >200 cells/μL have substantially increased long-term mortality.

High early mortality in patients with HIV-1 starting antiretroviral therapy (ART) in sub-Saharan Africa, compared to Europe and North America, is well documented. Longer-term comparisons between settings have been limited by poor ascertainment of mortality in high burden African settings. This study aimed to compare mortality up to four years on ART between South Africa, Europe, and North America. Data from four South African cohorts in which patients lost to follow-up (LTF) could be linked to the national population register to determine vital status were combined with data from Europe and North America. Cumulative mortality, crude and adjusted (for characteristics at ART initiation) mortality rate ratios (relative to South Africa), and predicted mortality rates were described by region at 0-3, 3-6, 6-12, 12-24, and 24-48 months on ART for the period 2001-2010. Of the adults included (30,467 [South Africa], 29,727 [Europe], and 7,160 [North America]), 20,306 (67%), 9,961 (34%), and 824 (12%) were women. Patients began treatment with markedly more advanced disease in South Africa (median CD4 count 102, 213, and 172 cells/µl in South Africa, Europe, and North America, respectively). High early mortality after starting ART in South Africa occurred mainly in patients starting ART with CD4 count <50 cells/µl. Cumulative mortality at 4 years was 16.6%, 4.7%, and 15.3% in South Africa, Europe, and North America, respectively. Mortality was initially much lower in Europe and North America than South Africa, but the differences were reduced or reversed (North America) at longer durations on ART (adjusted rate ratios 0.46, 95% CI 0.37-0.58, and 1.62, 95% CI 1.27-2.05 between 24 and 48 months on ART comparing Europe and North America to South Africa). While bias due to under-ascertainment of mortality was minimised through death registry linkage, residual bias could still be present due to differing approaches to and frequency of linkage. After accounting for under-ascertainment of mortality, with increasing duration on ART, the mortality rate on HIV treatment in South Africa declines to levels comparable to or below those described in participating North American cohorts, while substantially narrowing the differential with the European cohorts. Please see later in the article for the Editors' Summary.

Objective To characterize and address the opioid crisis disproportionately impacting rural U.S. regions. Methods The Rural Opioid Initiative (ROI) is a two-phase project to collect and harmonize quantitative and qualitative data and develop tailored interventions to address rural opioid use. The baseline quantitative survey data from people who use drugs (PWUD) characterizes the current opioid epidemic (2018–2020) in eight geographically diverse regions. Results Among 3,084 PWUD, 92% reported ever injecting drugs, 86% reported using opioids (most often heroin) and 74% reported using methamphetamine to get high in the past 30 days; 53% experienced homelessness in the prior 6 months; and 49% had ever overdosed. Syringe service program use varied by region and 53% had ever received an overdose kit or naloxone prescription. Less than half (48%) ever received medication for opioid use disorder (MOUD). Conclusions The ROI combines data across eight rural regions to better understand drug use including drivers and potential interventions in rural areas with limited resources. Baseline ROI data demonstrate extensive overlap between opioid and methamphetamine use, high homelessness rates, inadequate access to MOUD, and other unmet needs among PWUD in the rural U.S. By combining data across studies, the ROI provides much greater statistical power to address research questions and better understand the syndemic of infectious diseases and drug use in rural settings including unmet treatment needs.

Type 2 diabetes (T2D) risk prediction remains a challenge, particularly in underrepresented populations, including people living with HIV (PWH) and those of non-European ancestry. We evaluated the performance of two metaPRS (polygenic risk score) models, integrating genetic markers related to inflammation and lipid metabolism, in predicting T2D risk across ancestry groups (African and European), with and without HIV. The metaPRS were generated in a subset from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study (6,034 Black; 11,972 White) and validated in 7,580 (4,120 Black; 3,460 White) PWH from the Centers for AIDS Research of Integrated Clinical Systems (CNICS), as well as an additional 4,152 (2,586 Black; 1,566 White) seronegative participants from REGARDS. Incorporating the metaPRS into models provided non-significant improvements in T2D risk prediction compared to single-trait T2D PRS and clinical risk factors. Performance was similar in PWH and in people without HIV, suggesting that these general population-derived genetic scores are transferable to PWH. Future studies should focus on refining PRS models in diverse populations and exploring genetic factors specific to PWH regarding T2D risk.

Research on patient engagement in health care shows that better health outcomes and lower healthcare costs are observed among highly engaged patients. Similar to other illnesses, high levels of patient engagement in HIV care are considered essential to maintaining optimal health, and patients who are on treatment and retained in HIV care are known to have better health outcomes. In this article, we draw on focus group discussion data with patients living with HIV in order to explain tacit expectations associated with engagement in care. The main objective of our research was to elicit an explanatory model of engagement in HIV care from the patients' perspective. We conducted focus group discussions with a sample of two distinct types of patients: those who regularly attended medical appointments and those who did not. In total, we conducted six focus group discussions (n = 43) across in three cities in the US; these included two focus group discussions with a well-engaged and less-well-engaged group in each location. Both types of patients assigned a moral dimension to engagement in care, in that well-engaged patients were considered to be 'good' patients. Aspiring to become a 'good' patient provided a meaningful goal for some and deepened vulnerabilities among patients that struggled to achieve this status. More vulnerable patients may feel less secure in health care interactions and these feelings may be amplified if patients have an unreasonable impression of what constitutes a 'good' patient; thereby leading to disengagement in care. Our findings can inform the development of patient-centered, tailored messages to better serve patients struggling to stay engaged in HIV care.

Transgender women (TW) are disproportionately affected by both HIV and cardiovascular disease (CVD). We aim to quantify prevalence of elevated predicted CVD risk for TW compared to cisgender women (CW) and cisgender men (CM) in HIV care and describe the impact of multiple operationalizations of CVD risk score calculations for TW. We conducted a cross-sectional analysis of patients engaged in HIV care between October 2014 and February 2018. The Centers for AIDS Research Network of Integrated Clinical Systems, a collaboration of 8 HIV clinical sites in the United States contributed data for this analysis. 221 TW, 2983 CW, and 13467 CM. The measure of interest is prevalence of elevated 10-year cardiovascular disease risk based on ACC/AHA Pooled Cohort Risk Assessment equations (PCE) and the Framingham Risk Score (FRS), calculated for TW by: birth-assigned sex (male); history of exogenous sex hormone use (female/male); and current gender (female). Using birth-assigned sex, the adjusted prevalence ratio (aPR) was 2.52 (95% CI: 1.08,5.86) and 2.58 (95% CI: 1.71,3.89) comparing TW to CW, by PCE and FRS, respectively. It was 1.25 (95% CI: 0.54,2.87) and 1.25 (95% CI: 0.84,1.86) comparing TW to CM, by PCE and FRS, respectively. If TW were classified according to current gender versus birth-assigned sex, their predicted CVD risk scores were lower. PCE and FRS have not been validated in TW with HIV. Few adjudicated CVD events in the data set precluded analyses based on clinical outcomes. After adjustment for demographics and history of HIV care, prevalence of elevated CVD risk in TW was similar to CM and equal to or higher than in CW, depending operationalization of the sex variable. Future studies with CVD outcomes are needed to help clinicians accurately estimate CVD risk among TW with HIV.

To describe disparities along the depression treatment cascade, from indication for antidepressant treatment to effective treatment, in HIV-infected individuals by gender and race/ethnicity. The Center for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS) cohort includes 31,000 HIV-infected adults in routine clinical care at 8 sites. Individuals were included in the analysis if they had a depressive symptoms measure within one month of establishing HIV care at a CNICS site. Depressive symptoms were measured using the validated Patient Health Questionnaire-9 (PHQ-9). Indication for antidepressant treatment was defined as PHQ-9 ≥ 10 or a current antidepressant prescription. Antidepressant treatment was defined as a current antidepressant prescription. Evidence-based antidepressant treatment was considered treatment changes based on a person's most recent PHQ-9, in accordance with clinical guidelines. We calculated the cumulative probability of moving through the depression treatment cascade within 24 months of entering CNICS HIV care. We used multivariable Cox proportional hazards models to estimate associations between gender, race/ethnicity, and a range of depression outcomes. In our cohort of HIV-infected adults in routine care, 47% had an indication for antidepressant treatment. Significant drop-offs along the depression treatment cascade were seen for the entire study sample. However, important disparities existed. Women were more likely to have an indication for antidepressant treatment (HR 1.54; 95% CI 1.34, 1.78), receive antidepressant treatment (HR 2.03; 95% CI 1.53, 2.69) and receive evidence-based antidepressant treatment (HR 1.67; 95% CI 1.03, 2.74), even after accounting for race/ethnicity. Black non-Hispanics (HR 0.47, 95% CI 0.35, 0.65), Hispanics (HR 0.63, 95% CI 0.44, 0.89) and other race/ethnicities (HR 0.35, 95% CI 0.17, 0.73) were less likely to initiate antidepressant treatment, compared to white non-Hispanics. In our cohort of HIV-infected adults depressive symptoms were common. Important disparities in the prevalence of depressive symptoms and receipt of antidepressant treatment existed by gender and race/ethnicity.

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

Background Advances in antiretroviral therapies have greatly improved the survival of people living with human immunodeficiency virus (HIV) infection (PLWH); yet, PLWH have a higher risk of cardiovascular disease than those without HIV. While numerous genetic loci have been linked to cardiometabolic risk in the general population, genetic predictors of the excessive risk in PLWH are largely unknown. Methods We screened for common and HIV-specific genetic variants associated with variation in lipid levels in 6284 PLWH (3095 European Americans [EA] and 3189 African Americans [AA]), from the Centers for AIDS Research Network of Integrated Clinical Systems cohort. Genetic hits found exclusively in the PLWH cohort were tested for association with other traits. We then assessed the predictive value of a series of polygenic risk scores (PRS) recapitulating the genetic burden for lipid levels, type 2 diabetes (T2D), and myocardial infarction (MI) in EA and AA PLWH. Results We confirmed the impact of previously reported lipid-related susceptibility loci in PLWH. Furthermore, we identified PLWH-specific variants in genes involved in immune cell regulation and previously linked to HIV control, body composition, smoking, and alcohol consumption. Moreover, PLWH at the top of European-based PRS for T2D distribution demonstrated a > 2-fold increased risk of T2D compared to the remaining 95% in EA PLWH but to a much lesser degree in AA. Importantly, while PRS for MI was not predictive of MI risk in AA PLWH, multiethnic PRS significantly improved risk stratification for T2D and MI. Conclusions Our findings suggest that genetic loci involved in the regulation of the immune system and predisposition to risky behaviors contribute to dyslipidemia in the presence of HIV infection. Moreover, we demonstrate the utility of the European-based and multiethnic PRS for stratification of PLWH at a high risk of cardiometabolic diseases who may benefit from preventive therapies.