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BackgroundEstimating the medical complexity of people aging with HIV can inform clinical programs and policy to meet future healthcare needs. The objective of our study was to forecast the prevalence of comorbidities and multimorbidity among people with HIV (PWH) using antiretroviral therapy (ART) in the United States (US) through 2030.Methods and findingsUsing the PEARL model-an agent-based simulation of PWH who have initiated ART in the US-the prevalence of anxiety, depression, stage ≥3 chronic kidney disease (CKD), dyslipidemia, diabetes, hypertension, cancer, end-stage liver disease (ESLD), myocardial infarction (MI), and multimorbidity (≥2 mental or physical comorbidities, other than HIV) were forecasted through 2030. Simulations were informed by the US CDC HIV surveillance data of new HIV diagnosis and the longitudinal North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) data on risk of comorbidities from 2009 to 2017. The simulated population represented 15 subgroups of PWH including Hispanic, non-Hispanic White (White), and non-Hispanic Black/African American (Black/AA) men who have sex with men (MSM), men and women with history of injection drug use and heterosexual men and women. Simulations were replicated for 200 runs and forecasted outcomes are presented as median values (95% uncertainty ranges are presented in the Supporting information). In 2020, PEARL forecasted a median population of 670,000 individuals receiving ART in the US, of whom 9% men and 4% women with history of injection drug use, 60% MSM, 8% heterosexual men, and 19% heterosexual women. Additionally, 44% were Black/AA, 32% White, and 23% Hispanic. Along with a gradual rise in population size of PWH receiving ART-reaching 908,000 individuals by 2030-PEARL forecasted a surge in prevalence of most comorbidities to 2030. Depression and/or anxiety was high and increased from 60% in 2020 to 64% in 2030. Hypertension decreased while dyslipidemia, diabetes, CKD, and MI increased. There was little change in prevalence of cancer and ESLD. The forecasted multimorbidity among PWH receiving ART increased from 63% in 2020 to 70% in 2030. There was heterogeneity in trends across subgroups. Among Black women with history of injection drug use in 2030 (oldest demographic subgroup with median age of 66 year), dyslipidemia, CKD, hypertension, diabetes, anxiety, and depression were most prevalent, with 92% experiencing multimorbidity. Among Black MSM in 2030 (youngest demographic subgroup with median age of 42 year), depression and CKD were highly prevalent, with 57% experiencing multimorbidity. These results are limited by the assumption that trends in new HIV diagnoses, mortality, and comorbidity risk observed in 2009 to 2017 will persist through 2030; influences occurring outside this period are not accounted for in the forecasts.ConclusionsThe PEARL forecasts suggest a continued rise in comorbidity and multimorbidity prevalence to 2030, marked by heterogeneities across race/ethnicity, gender, and HIV acquisition risk subgroups. HIV clinicians must stay current on the ever-changing comorbidities-specific guidelines to provide guideline-recommended care. HIV clinical directors should ensure linkages to subspecialty care within the clinic or by referral. HIV policy decision-makers must allocate resources and support extended clinical capacity to meet the healthcare needs of people aging with HIV.

BackgroundThe impact of adopting a race-free estimated glomerular filtration rate (eGFR) creatinine (eGFRcr) equation on racial differences in chronic kidney disease (CKD) progression among people with human immunodeficiency virus (PWH) is unknown.MethodsWe defined eGFR stages using the original race-adjusted Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) eGFRcr equation and the new race-free CKD-EPI eGFRcr equation. We then estimated 5-year probabilities of transitioning from baseline kidney function to more advanced eGFR stages and examined the association of race (black vs white) with rates of CKD progression using Markov models.ResultsWith the race-adjusted eGFRcr equation, black participants (n = 31 298) had a lower risk of progressing from eGFR stage 1 to 2 (hazard ratio [HR], 0.77; 95% confidence interval [CI], .73-.82), an equal risk of progressing from stage 2 to 3 (1.00; .92-.07) and a 3-fold risk of progressing from stage 3 to 4 or 5 (3.06; 2.60-3.62), compared with white participants (n = 27 542). When we used the race-free eGFRcr equation, 16% of black participants were reclassified into a more severe eGFR stage at baseline. The reclassified black individuals had a higher prevalence of CKD risk factors than black PWH who were not reclassified. With the race-free eGFRcr equation, black participants had a higher risk of disease progression across all eGFR stages than white participants.ConclusionsThe original eGFRcr equation systematically masked a subgroup of black PWH who are at high-risk of CKD progression. The new race-free eGFRcr equation unmasks these individuals and may allow for earlier detection and management of CKD.

A care cascade is a critical tool for evaluating delivery of care for chronic infections across sequential stages, starting with diagnosis and ending with viral suppression. However, there have been few data describing the hepatitis B virus (HBV) care cascade among people living with HIV infection who have HBV coinfection. We conducted a cross-sectional study among people living with HIV and HBV coinfection receiving care between January 1, 2012 and December 31, 2016 within 13 United States and Canadian clinical cohorts contributing data to the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD). We evaluated each of the steps in this cascade, including: 1) laboratory-confirmed HBV infection, 2) tenofovir-based or entecavir-based HBV therapy prescribed, 3) HBV DNA measured during treatment, and 4) viral suppression achieved via undetectable HBV DNA. Among 3,953 persons with laboratory-confirmed HBV (median age, 50 years; 6.5% female; 43.8% were Black; 7.1% were Hispanic), 3,592 (90.9%; 95% confidence interval, 90.0-91.8%) were prescribed tenofovir-based antiretroviral therapy or entecavir along with their antiretroviral therapy regimen, 2,281 (57.7%; 95% confidence interval, 56.2-59.2%) had HBV DNA measured while on therapy, and 1,624 (41.1%; 95% confidence interval, 39.5-42.6) achieved an undetectable HBV DNA during HBV treatment. Our study identified significant gaps in measurement of HBV DNA and suppression of HBV viremia among people living with HIV and HBV coinfection in the United States and Canada. Periodic evaluation of the HBV care cascade among persons with HIV/HBV will be critical to monitoring success in completion of each step.

BackgroundThe updated Veterans Aging Cohort Study (VACS) Index 2.0 combines general and human immunodeficiency virus (HIV)-specific biomarkers to generate a continuous score that accurately discriminates risk of mortality in diverse cohorts of persons with HIV (PWH), but a score alone is difficult to interpret. Using data from the North American AIDS Cohort Collaboration (NA-ACCORD), we translate VACS Index 2.0 scores into validated probability estimates of mortality.MethodsBecause complete mortality ascertainment is essential for accurate calibration, we restricted analyses to cohorts with mortality from the National Death Index or equivalent sources. VACS Index 2.0 components were ascertained from October 1999 to April 2018. Mortality was observed up to March 2019. Calibration curves compared predicted (estimated by fitting a gamma model to the score) to observed mortality overall and within subgroups: cohort (VACS/NA-ACCORD subset), sex, age 500 copies/mL, CD4 count

BackgroundIndependent of CD4 cell count, a low CD4/CD8 ratio in people with HIV (PWH) is associated with deleterious immune senescence, activation, and inflammation, which may contribute to carcinogenesis and excess cancer risk. We examined whether low CD4/CD8 ratios predicted cancer among PWH in the United States and Canada.MethodsWe examined all cancer-free PWH with 1 or more CD4/CD8 values from North American AIDS Cohort Collaboration on Research and Design observational cohorts with validated cancer diagnoses between 1998 and 2016. We evaluated the association between time-lagged CD4/CD8 ratio and risk of specific cancers in multivariable, time-updated Cox proportional hazard models using restricted cubic spines. Models were adjusted for age, sex, race and ethnicity, hepatitis C virus, and time-updated CD4 cell count, HIV RNA, and history of AIDS-defining illness.ResultsAmong 83 893 PWH, there were 5628 incident cancers, including lung cancer (n = 755), Kaposi sarcoma (n = 501), non-Hodgkin lymphoma (n = 497), and anal cancer (n = 439). The median age at cohort entry was 43 years. The overall median 6-month lagged CD4/CD8 ratio was 0.52 (interquartile range = 0.30-0.82). Compared with a 6-month lagged CD4/CD8 of 0.80, a CD4/CD8 of 0.30 was associated with increased risk of any incident cancer (adjusted hazard ratio = 1.24 [95% confidence interval = 1.14 to 1.35]). The CD4/CD8 ratio was also inversely associated with non-Hodgkin lymphoma, Kaposi sarcoma, lung cancer, anal cancer, and colorectal cancer in adjusted analyses (all 2-sided P

There are no studies comparing the prognosis for mature T-cell lymphoma (TCL) in people with HIV (PWH) to people without HIV (PWoH) and to AIDS-defining B-cell lymphomas (A-BCLs) in the modern antiretroviral therapy era. North American AIDS Cohort Collaboration on Research and Design and Comprehensive Oncology Measures for Peripheral T-cell Lymphoma Treatment are cohorts that enroll patients diagnosed with HIV and TCL, respectively. In our study, 52, 64, 101, 500, and 246 PWH with histologic confirmation of TCL, primary central nervous system lymphoma, Burkitt's lymphoma, diffuse large B-cell lymphoma (DLBCL), and Hodgkin's lymphoma (HL), respectively, and 450 TCLs without HIV were eligible for analysis. At the time of TCL diagnosis, anaplastic large-cell lymphoma (ALCL) was the most common TCL subtype within PWH. Although PWH with TCL diagnosed between 1996 and 2009 experienced a low 5-year survival probability at 0.23 (95% confidence interval [CI]: 0.13, 0.41), we observed a marked improvement in their survival when diagnosed between 2010 and 2016 (0.69; 95% CI: 0.48, 1; P = .04) in contrast to TCLs among PWoH (0.45; 95% CI: 0.41, 0.51; P = .53). Similarly, PWH with ALCLs diagnosed between 1996 and 2009 were associated with a conspicuously inferior 5-year survival probability (0.17; 95% CI: 0.07, 0.42) and consistently lagged behind A-BCL subtypes such as Burkitt's (0.43; 95% CI:0.33, 0.57; P = .09) and DLBCL (0.17; 95% CI: 0.06, 0.46; P = .11) and behind HL (0.57; 95% CI: 0.50, 0.65; P < .0001). Despite a small number, those diagnosed between 2010 and 2016 experienced a remarkable improvement in survival (0.67; 95% CI: 0.3, 1) in comparison with PWoH (0.76; 95% CI: 0.66, 0.87; P = .58). Thus, our analysis confirms improved overall survival for aggressive B- and T-cell malignancies among PWH in the last decade.

OBJECTIVE: To compare dementia incidence and prevalence after age 50 years by HIV status. DESIGN: Observational cohort, 2000-2016. METHODS: People with HIV (PWH) on antiretroviral therapy (ART) and demographically similar people without HIV (PWoH), all aged 50 years and older, were identified from Kaiser Permanente healthcare systems in Northern California, Southern California, and Mid-Atlantic States (Maryland, Virginia, Washington DC). Dementia diagnoses were obtained from electronic health records. Incidence and prevalence of dementia, overall and by time period (i.e. 2000-2002, 2003-2004, …, 2015-2016), were calculated using Poisson regression. Trends were examined using Joinpoint regression. Rate ratios were used to compare dementia by HIV status with adjustment for sociodemographics, substance use, and clinical factors. RESULTS: The study included 13 296 PWH and 155 354 PWoH (at baseline: for both, mean age = 54 years, 89% men; for PWH, 80% with HIV RNA

The randomized controlled trial (RCT) is the gold standard for evaluating the causal effects of medications. Limitations of RCTs have led to increasing interest in using real-world evidence (RWE) to augment RCT evidence and inform decision making on medications. Although RWE can be either randomized or nonrandomized, nonrandomized RWE can capitalize on the recent proliferation of large healthcare databases and can often answer questions that cannot be answered in randomized studies due to resource constraints. However, the results of nonrandomized studies are much more likely to be impacted by confounding bias, and the existence of unmeasured confounders can never be completely ruled out. Furthermore, nonrandomized studies require more complex design considerations which can sometimes result in design-related biases. We discuss questions that can help investigators or evidence consumers evaluate the potential impact of confounding or other biases on their findings: Does the design emulate a hypothetical randomized trial design? Is the comparator or control condition appropriate? Does the primary analysis adjust for measured confounders? Do sensitivity analyses quantify the potential impact of residual confounding? Are methods open to inspection and (if possible) replication? Designing a high-quality nonrandomized study of medications remains challenging and requires broad expertise across a range of disciplines, including relevant clinical areas, epidemiology, and biostatistics. The questions posed in this paper provide a guiding framework for assessing the credibility of nonrandomized RWE and could be applied across many clinical questions.

Concerns regarding both the limited generalizability and the slow pace of traditional randomized trials have led to calls for greater use of real-world evidence (RWE) in the evaluation of new treatments or products. RWE studies often rely on real-world data (RWD), including data extracted from healthcare records or data captured by mobile phones or other consumer devices. Global assessments of RWD sources are not helpful in assessing whether any specific RWD element is fit for any specific purpose. Instead, evidence generators and evidence consumers should clearly identify the specific health state or clinical phenomenon of interest and then consider each step between that clinical phenomenon and its representation in a research database. We propose specific questions regarding potential error or bias affecting each of those steps: Would a person experiencing this clinical phenomenon present for care in this setting or interact with this recording device? Would this clinical phenomenon be accurately recognized or assessed? How might the recording environment or tools affect accurate and consistent recording of this clinical phenomenon? Can data elements from different sources be harmonized, both technically (same format) and semantically (same meaning)? Can the original data elements be consistently reduced to a useful clinical phenotype? Addressing these questions requires a range of clinical, organizational, and technical expertise. Transparency regarding each step in the creation of RWD is essential if evidence consumers are to rely on RWE studies.

Concerns regarding both the limited generalizability and the slow pace of traditional randomized trials have led to calls for greater use of real-world evidence in the evaluation of new treatments or products. Real-world clinical trials or pragmatic trials often differ from traditional clinical trials in the use of open-label or nonblinded treatments delivered by real-world clinicians in community practice settings. Blinding and standardization of treatment may sometimes be necessary for internal validity, but they may also obscure or distort meaningful differences between treatments. When investigators consider whether blinding of clinicians, patients, or assessors is necessary, we suggest they consider several specific questions: Will clinicians, patients, and assessors have expectations or preferences regarding benefits or adverse effects? How might those expectations affect treatment uptake, treatment adherence, or assessment of outcomes? Will expectations differ in the settings where trial results will be applied? How would blinding of treatment reduce biases? How would blinding obscure true differences between treatments? How would procedures necessary for blinding reduce acceptability or increase risk of trial participation? When investigators consider how strictly treatments should be standardized, we suggest they consider several specific questions: How would treatment effectiveness or safety vary according to clinician experience or expertise? What level of experience or expertise is available in potential trial settings and settings where trial results would be applied? Is some level of standardization necessary for valid inference? Considering any special vulnerabilities of the study population, is some level of standardization necessary to assure participant safety?

Concerns regarding both the limited generalizability and the slow pace of traditional randomized trials have led to calls for greater use of real-world evidence (RWE) in the evaluation of new treatments or products. The RWE label has been used to refer to a variety of departures from the methods of traditional randomized controlled trials. Recognizing this complexity and potential confusion, the National Academies of Science, Engineering, and Medicine convened a series of workshops to clarify and address questions regarding the use of RWE to evaluate new medical treatments. Those workshops identified three specific dimensions in which RWE studies might differ from traditional clinical trials: use of real-world data (data extracted from health system records or data captured by mobile devices), delivery of real-world treatment (open-label treatments delivered in community settings by community practitioners), and real-world treatment assignment (including nonrandomized comparisons and variations on random assignment such as before-after or stepped-wedge designs). For any RWE study, decisions regarding each of these dimensions depends on the specific research question, characteristics of the potential study settings, and characteristics of the settings where study results would be applied.

From 2005 to 2018, among 32013 adults with human immunodeficiency virus entering care, median time to antiretroviral therapy (ART) prescription declined from 69 to 6 days, CD4 count at entry into care increased from 300 to 362 cells/μL, and CD4 count at ART prescription increased from 160 to 364 cells/μL.

BackgroundUnderstanding advances in the care and treatment of adults with HIV as well as remaining gaps requires comparing differences in mortality between persons entering care for HIV and the general population.ObjectiveTo assess the extent to which mortality among persons entering HIV care in the United States is elevated over mortality among matched persons in the general U.S. population and trends in this difference over time.DesignObservational cohort study.SettingThirteen sites from the U.S. North American AIDS Cohort Collaboration on Research and Design.Participants82 766 adults entering HIV clinical care between 1999 and 2017 and a subset of the U.S. population matched on calendar time, age, sex, race/ethnicity, and county using U.S. mortality and population data compiled by the National Center for Health Statistics.MeasurementsFive-year all-cause mortality, estimated using the Kaplan-Meier estimator of the survival function.ResultsOverall 5-year mortality among persons entering HIV care was 10.6%, and mortality among the matched U.S. population was 2.9%, for a difference of 7.7 (95% CI, 7.4 to 7.9) percentage points. This difference decreased over time, from 11.1 percentage points among those entering care between 1999 and 2004 to 2.7 percentage points among those entering care between 2011 and 2017.LimitationMatching on available covariates may have failed to account for differences in mortality that were due to sociodemographic factors rather than consequences of HIV infection and other modifiable factors.ConclusionMortality among persons entering HIV care decreased dramatically between 1999 and 2017, although those entering care remained at modestly higher risk for death in the years after starting care than comparable persons in the general U.S. population.Primary funding sourceNational Institutes of Health.

Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3-12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5-12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2-19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.

BackgroundPersons with HIV (PWH) with persistently low CD4 counts despite efficacious antiretroviral therapy could have higher hospitalization risk.MethodsIn six US and Canadian clinical cohorts, PWH with virologic suppression for ≥1 year in 2005-2015 were followed until virologic failure, loss to follow-up, death, or study end. Stratified by early (Years 2-5) and long-term (Years 6-11) suppression and lowest pre-suppression CD4 count 500 cells/μL had an aIRR of 1.44 during early suppression (95% CI 1.01-2.06), and 1.67 (1.03-2.72) during long-term suppression. Among patients with lowest pre-suppression CD4 ≥200 (56%), patients with current CD4 351-500 versus >500 cells/μL had an aIRR of 1.22 (0.93-1.60) during early suppression and 2.09 (1.18-3.70) during long-term suppression.ConclusionsVirologically suppressed patients with lower CD4 counts experienced higher hospitalization rates, and could potentially benefit from targeted clinical management strategies.

BackgroundTo assess the possible impact of antiretroviral therapy improvements, aging, and comorbidities, we examined trends in all-cause and cause-specific hospitalization rates among persons with HIV (PWH) from 2005 to 2015.MethodsIn 6 clinical cohorts, we followed PWH in care (≥1 outpatient CD4 count or HIV load [VL] every 12 months) and categorized ICD codes of primary discharge diagnoses using modified Clinical Classifications Software. Poisson regression estimated hospitalization rate ratios for calendar time trends, adjusted for demographics, HIV risk factor, and annually updated age, CD4, and VL.ResultsAmong 28 057 patients (125 724 person-years), from 2005 to 2015, the median CD4 increased from 389 to 580 cells/µL and virologic suppression from 55% to 85% of patients. Unadjusted all-cause hospitalization rates decreased from 22.3 per 100 person-years in 2005 (95% confidence interval [CI], 20.6-24.1) to 13.0 in 2015 (95% CI, 12.2-14.0). Unadjusted rates decreased for almost all diagnostic categories. Adjusted rates decreased for all-cause, cardiovascular, and AIDS-defining conditions, increased for non-AIDS-defining infection, and were stable for most other categories.ConclusionsAmong PWH with increasing CD4 counts and viral suppression, unadjusted hospitalization rates decreased for all-cause and most cause-specific hospitalizations, despite the potential effects of aging, comorbidities, and cumulative exposure to HIV and antiretrovirals.

BackgroundPersons living with human immunodeficiency virus (HIV; PLWH) experience a high burden of cancer. It remains unknown which cancer types are reduced in PLWH with earlier initiation of antiretroviral therapy (ART).MethodsWe evaluated AIDS-free, ART-naive PLWH during 1996-2014 from 22 cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. PLWH were followed from first observed CD4 of 350-500 cells/µL (baseline) until incident cancer, death, lost-to-follow-up, or December 2014. Outcomes included 6 cancer groups and 5 individual cancers that were confirmed by chart review or cancer registry linkage. We evaluated the effect of earlier (in the first 6 months after baseline) versus deferred ART initiation on cancer risk. Marginal structural models were used with inverse probability weighting to account for time-dependent confounding and informative right-censoring, with weights informed by subject's age, sex, cohort, baseline year, race/ethnicity, HIV transmission risk, smoking, viral hepatitis, CD4, and AIDS diagnoses.ResultsProtective results for earlier ART were found for any cancer (adjusted hazard ratio [HR] 0.57; 95% confidence interval [CI], .37-.86), AIDS-defining cancers (HR 0.23; 95% CI, .11-.49), any virus-related cancer (HR 0.30; 95% CI, .16-.54), Kaposi sarcoma (HR 0.25; 95% CI, .10-.61), and non-Hodgkin lymphoma (HR 0.22; 95% CI, .06-.73). By 15 years, there was also an observed reduced risk with earlier ART for virus-related NADCs (0.6% vs 2.3%; adjusted risk difference -1.6; 95% CI, -2.8, -.5).ConclusionsEarlier ART initiation has potential to reduce the burden of virus-related cancers in PLWH but not non-AIDS-defining cancers (NADCs) without known or suspected viral etiology.

BackgroundStudies suggest lower risk of breast cancer in women with HIV versus without HIV. These estimates may be biased by lower life expectancy and younger age distribution of women with HIV. Our analysis evaluated this bias and characterized secular trends in breast cancer among women with HIV initiating antiretroviral therapy. We hypothesized breast cancer risk would increase over time as mortality decreased.SettingWomen with HIV prescribed antiretroviral therapy in the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) from 1997 through 2016.MethodsWe estimated breast cancer hazard (cause-specific hazard ratios) and cumulative incidence accounting for competing risks (subdistribution hazard ratios) to assess changes in breast cancer risk over time. This was assessed overall (1997-2016) and within/across calendar periods. Analyses were adjusted for race/ethnicity and inverse probability weighted for cohort. Cumulative incidence was graphically assessed by calendar period and race/ethnicity.ResultsWe observed 11,587 women during 1997-2016, contributing 63 incident breast cancer diagnoses and 1,353 deaths [73,445 person-years (median follow-up = 4.5 years)]. Breast cancer cumulative incidence was 3.2% for 1997-2016. We observed no secular trends in breast cancer hazard or cumulative incidence. There were annual declines in the hazard and cumulative incidence of death (cause-specific hazard ratios and subdistribution hazard ratios: 0.89, 95% confidence interval: 0.87 to 0.91) which remained within and across calendar periods.ConclusionsThese findings contradict the hypothesis of increasing breast cancer risk with declining mortality over time among women with HIV, suggesting limited impact of changing mortality on breast cancer risk. Additional inquiry is merited as survival improves among women with HIV.

Concerns regarding both the limited generalizability and the slow pace of traditional randomized trials have led to calls for greater use of real-world evidence (RWE) in the evaluation of new treatments or products. The RWE label has been used to refer to a variety of departures from the methods of traditional randomized controlled trials. Recognizing this complexity and potential confusion, the National Academies of Science, Engineering, and Medicine convened a series of workshops to clarify and address questions regarding the use of RWE to evaluate new medical treatments. Those workshops identified three specific dimensions in which RWE studies might differ from traditional clinical trials: use of real-world data (data extracted from health system records or data captured by mobile devices), delivery of real-world treatment (open-label treatments delivered in community settings by community practitioners), and real-world treatment assignment (including nonrandomized comparisons and variations on random assignment such as before-after or stepped-wedge designs). For any RWE study, decisions regarding each of these dimensions depends on the specific research question, characteristics of the potential study settings, and characteristics of the settings where study results would be applied.

Concerns regarding both the limited generalizability and the slow pace of traditional randomized trials have led to calls for greater use of real-world evidence in the evaluation of new treatments or products. Real-world clinical trials or pragmatic trials often differ from traditional clinical trials in the use of open-label or nonblinded treatments delivered by real-world clinicians in community practice settings. Blinding and standardization of treatment may sometimes be necessary for internal validity, but they may also obscure or distort meaningful differences between treatments. When investigators consider whether blinding of clinicians, patients, or assessors is necessary, we suggest they consider several specific questions: Will clinicians, patients, and assessors have expectations or preferences regarding benefits or adverse effects? How might those expectations affect treatment uptake, treatment adherence, or assessment of outcomes? Will expectations differ in the settings where trial results will be applied? How would blinding of treatment reduce biases? How would blinding obscure true differences between treatments? How would procedures necessary for blinding reduce acceptability or increase risk of trial participation? When investigators consider how strictly treatments should be standardized, we suggest they consider several specific questions: How would treatment effectiveness or safety vary according to clinician experience or expertise? What level of experience or expertise is available in potential trial settings and settings where trial results would be applied? Is some level of standardization necessary for valid inference? Considering any special vulnerabilities of the study population, is some level of standardization necessary to assure participant safety?

IntroductionSmoking tobacco and unhealthy alcohol use may negatively influence HIV care continuum outcomes but have not been examined in combination.MethodsParticipants were people with HIV (PWH) in Kaiser Permanente Northern California. Predictors included smoking status and unhealthy alcohol use (exceeding daily and/or weekly limits) reported by patients during primary care screening (index date). Outcomes were based on not achieving the following steps in the care continuum: linkage to HIV care (≥1 visit within 90 days of newly identified HIV diagnosis), retention (2+ in-person visits, 60+ days apart) and HIV RNA control (

BACKGROUND: Unhealthy alcohol use among persons living with HIV (PLWH) is linked to significant morbidity, and use of alcohol services may differ by HIV status. Our objective was to compare unhealthy alcohol use screening and treatment by HIV status in primary care. METHODS: Cohort study of adult (≥18 years) PLWH and HIV-uninfected participants frequency matched 20:1 to PLWH by age, sex, and race/ethnicity who were enrolled in a large integrated healthcare system in the United States, with information ascertained from an electronic health record. Outcomes included unhealthy alcohol screening, prevalence, provider-delivered brief interventions, and addiction specialty care visits. Other predictors included age, sex, race/ethnicity, neighborhood deprivation index, depression, smoking, substance use disorders, Charlson comorbidity index, prior outpatient visits, insurance type, and medical facility. Cox proportional hazards models were used to compute hazard ratios (HR) for the outcomes of time to unhealthy alcohol use screening and time to first addiction specialty visit. Poisson regression with robust standard errors was used to compute prevalence ratios (PR) for other outcomes. RESULTS: 11,235 PLWH and 227,320 HIV-uninfected participants were included. By 4.5 years after baseline, most participants were screened for unhealthy alcohol use (85% of PLWH and 93% of HIV-uninfected), but with a lower rate among PLWH (adjusted HR 0.84, 95% CI 0.82 to 0.85). PLWH were less likely, compared with HIV-uninfected participants, to report unhealthy drinking among those screened (adjusted PR 0.74, 95% CI 0.69 to 0.79), and among those who screened positive, less likely to receive brief interventions (adjusted PR 0.82, 95% CI 0.75 to 0.90), but more likely (adjusted HR 1.7, 95% CI 1.2 to 2.4) to have an addiction specialty visit within 1 year. CONCLUSIONS: Unhealthy alcohol use was lower in PLWH, but the treatment approach by HIV status differed. PLWH reporting unhealthy alcohol use received less brief interventions and more addiction specialty care than HIV-uninfected participants.

BackgroundThe Affordable Care Act (ACA) has increased insurance coverage for people with HIV (PWH) in the United States. To inform health policy, it is useful to investigate how enrollment through ACA Exchanges, deductible levels, and demographic factors are associated with health care utilization and HIV clinical outcomes among individuals newly enrolled in insurance coverage following implementation of the ACA.MethodsAmong PWH newly enrolled in an integrated health care system (Kaiser Permanente Northern California) in 2014 (N = 880), we examined use of health care and modeled associations between enrollment mechanisms (enrolled in a Qualified Health Plan through the California Exchange vs. other sources), deductibles (none, $1-$999 and > = $1000), receipt of benefits from the California AIDS Drug Assistance Program (ADAP), demographic factors, and three-year patterns of health service utilization (primary care, psychiatry, substance treatment, emergency, inpatient) and HIV outcomes (CD4 counts; viral suppression at HIV RNA

Assessing quality care for people with HIV (PWH) should not be limited to reporting on HIV Care Continuum benchmarks, particularly viral suppression rates. At Kaiser Permanente Mid-Atlantic States (KPMAS), an integrated health system providing HIV care in the District of Columbia, Maryland, and Virginia, we created a comprehensive measure of HIV quality care, including both preventative measures and clinical outcomes. We included PWH ≥18 years old with ≥6 months KPMAS membership between 2015 and 2018. Process quality metrics (QMs) include: pneumococcal vaccination and influenza vaccination; primary care physician (PCP) and/or HIV/infectious disease (HIV/ID) visits with additional HIV/ID visit; antiretroviral treatment medication fills; and syphilis and gonorrhea/chlamydia screenings. Outcome QMs include HIV RNA

BACKGROUND: Persons with HIV (PWH) are more likely to smoke and are more susceptible to the harmful effects of smoking than persons without HIV. We examined smoking patterns and use of cessation treatment among PWH and persons without HIV in a U.S. integrated health system. METHODS: We identified adults (≥18 years) with HIV and demographically-matched persons without HIV between July 2013 and December 2017. Smoking status and cessation treatment were ascertained from health records. We calculated age-standardized annual prevalence of smoking and evaluated trends using Cochran-Armitage tests and Poisson regression. Factors associated with cessation treatment during the study period, and smoking in the last year of the study, were evaluated by HIV status using multivariable Poisson models. RESULTS: The study included 11,235 PWH and 227,320 persons without HIV. Smoking prevalence was higher among PWH across all years but declined for both groups (from 16.6% to 14.6% in PWH and 11.6% to 10.5% in persons without HIV). Among smokers, PWH were more likely to initiate cessation treatment compared to persons without HIV (17.9% vs. 13.3%, covariate-adjusted prevalence ratio of 1.31, 95% CI = 1.15-1.50), with few differences in cessation treatment across subgroups of PWH. In 2017, smoking prevalence remained higher in PWH, especially among those who were younger or who had diagnoses of depression or substance use disorder. CONCLUSION: In a setting with access to cessation resources, smoking prevalence decreased both in PWH and persons without HIV. PWH had greater uptake of cessation treatment, which is encouraging for smoking reduction and improved health.

ObjectiveThe purpose of this study was to model weight trajectories over a 5-year time period (2012-2016) and their association with behavioural and psychosocial characteristics and health care-related experiences using data from the Patient Outcomes Research to Advance Learning (PORTAL) overweight/obesity cohort.MethodsWeight trajectories for each eligible patient in the PORTAL overweight/obesity cohort (n = 2864) were identified first using growth modelling; trajectories were then grouped using a hierarchical cluster analysis. Weight trajectory clusters that emerged were compared on demographics, and predictors of cluster membership were examined. Clusters were also compared on responses to a survey assessing health behaviours, quality of life, and health care experience completed in 2015 by 49% of the total sample (n = 1391).ResultsSeven distinct weight trajectory clusters were identified: (a) significant weight loss then maintenance; (b) higher stable weight; (c) moderate stable weight; (d) steady weight loss then relapse; (e) weight gain then weight loss; (f) steady weight gain then maintenance; and (g) lower stable weight. Age, sex, race/ethnicity, and body mass index at baseline predicted patient's weight trajectory (P < .001). Over two thirds of patients maintained their weight over the 5-year period. Significant weight loss then maintenance, weight gain then weight loss, and higher stable weight patients were more likely to report receiving weight counselling from their provider. Patients in the significant weight loss then maintenance and lower stable weight clusters were more likely to be physically active than the other clusters.ConclusionFindings suggest variability in patterns of weight change among adults with overweight or obesity who have access to health care and that these patterns differ on demographic, behavioural and psychosocial factors, and health care experience.

In a sample of people with HIV (PWH) enrolled in an alcohol intervention trial and followed for 12 months, we examined the association of changes in days (i.e., decrease, increase, no change [reference]) of unhealthy drinking (consuming ≥ 4/≥ 5 drinks for women/men) with antiretroviral therapy adherence (≥ 95% adherent), viral suppression (HIV RNA

IntroductionWeight gain following antiretroviral therapy (ART) initiation is common, potentially predisposing some persons with HIV (PWH) to cardio-metabolic disease. We assessed relationships between ART drug class and weight change among treatment-naïve PWH initiating ART in the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD).MethodsAdult, treatment-naïve PWH in NA-ACCORD initiating integrase strand transfer inhibitor (INSTI), protease inhibitor (PI) or non-nucleoside reverse-transcriptase inhibitor (NNRTI)-based ART on/after 1 January 2007 were followed through 31 December 2016. Multivariate linear mixed effects models estimated weight up to five years after ART initiation, adjusting for age, sex, race, cohort site, HIV acquisition mode, treatment year, and baseline weight, plasma HIV-1 RNA level and CD4+ cell count. Due to shorter follow-up for PWH receiving newer INSTI drugs, weights for specific INSTIs were estimated at two years. Secondary analyses using logistic regression and all covariates from primary analyses assessed factors associated with >10% weight gain at two and five years.ResultsAmong 22,972 participants, 87% were male, and 41% were white. 49% started NNRTI-, 31% started PI- and 20% started INSTI-based regimens (1624 raltegravir (RAL), 2085 elvitegravir (EVG) and 929 dolutegravir (DTG)). PWH starting INSTI-based regimens had mean estimated five-year weight change of +5.9kg, compared to +3.7kg for NNRTI and +5.5kg for PI. Among PWH starting INSTI drugs, mean estimated two-year weight change was +7.2kg for DTG, +5.8kg for RAL and +4.1kg for EVG. Women, persons with lower baseline CD4+ cell counts, and those initiating INSTI-based regimens had higher odds of >10% body weight increase at two years (adjusted odds ratio = 1.37, 95% confidence interval: 1.20 to 1.56 vs. NNRTI).ConclusionsPWH initiating INSTI-based regimens gained, on average, more weight compared to NNRTI-based regimens. This phenomenon may reflect heterogeneous effects of ART agents on body weight regulation that require further exploration.

BackgroundPrior studies suggest that transgender women (TW) with human immunodeficiency virus (HIV) are less likely to be virally suppressed than cisgender women (CW) and cisgender men (CM). However, prior data are limited by small sample sizes and cross-sectional designs. We sought to characterize the HIV care continuum comparing TW to CW and CM in the United States and Canada.MethodsWe analyzed annual HIV care continuum outcomes by gender status from January 2001 through December 2015 among adults (aged ≥18 years) in 15 clinical cohorts. Outcomes were retention in care and viral suppression.ResultsThe study population included TW (n = 396), CW (n = 14 094), and CM (n = 101 667). TW had lower proportions retained in care than CW and CM (P < .01). Estimates of retention in care were consistently lower in TW, with little change over time within each group. TW and CW had similar proportions virally suppressed over time (TW, 36% in 2001 and 80% in 2015; CW, 35% in 2001 and 83% in 2015) and were lower than CM (41% in 2001 and 87% in 2015). These differences did not reach statistical significance after adjusting for age, race, HIV risk group, and cohort.ConclusionsTW experience challenges with retention in HIV care. However, TW who are engaged in care achieve viral suppression that is comparable to that of CW and CM of similar age, race, and HIV risk group. Further research is needed to understand care engagement disparities.

BackgroundPeople living with human immunodeficiency virus (HIV; PLWH) have a markedly elevated anal cancer risk, largely due to loss of immunoregulatory control of oncogenic human papillomavirus infection. To better understand anal cancer development and prevention, we determined whether recent, past, cumulative, or nadir/peak CD4+ T-cell count (CD4) and/or HIV-1 RNA level (HIV RNA) best predict anal cancer risk.MethodsWe studied 102 777 PLWH during 1996-2014 from 21 cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. Using demographics-adjusted, cohort-stratified Cox models, we assessed associations between anal cancer risk and various time-updated CD4 and HIV RNA measures, including cumulative and nadir/peak measures during prespecified moving time windows. We compared models using the Akaike information criterion.ResultsCumulative and nadir/peak CD4 or HIV RNA measures from approximately 8.5 to 4.5 years in the past were generally better predictors for anal cancer risk than their corresponding more recent measures. However, the best model included CD4 nadir (ie, the lowest CD4) from approximately 8.5 years to 6 months in the past (hazard ratio [HR] for

Improvements in life expectancy among people living with human immunodeficiency virus (PLWH) receiving antiretroviral treatment in the United States and Canada might differ among key populations. Given the difference in substance use among key populations and the current opioid epidemic, drug- and alcohol-related deaths might be contributing to the disparities in life expectancy. We sought to estimate life expectancy at age 20 years in key populations (and their comparison groups) in 3 time periods (2004-2007, 2008-2011, and 2012-2015) and the potential increase in expected life expectancy with a simulated 20% reduction in drug- and alcohol-related deaths using the novel Lives Saved Simulation model. Among 92,289 PLWH, life expectancy increased in all key populations and comparison groups from 2004-2007 to 2012-2015. Disparities in survival of approximately a decade persisted among black versus white men who have sex with men and people with (vs. without) a history of injection drug use. A 20% reduction in drug- and alcohol-related mortality would have the greatest life-expectancy benefit for black men who have sex with men, white women, and people with a history of injection drug use. Our findings suggest that preventing drug- and alcohol-related deaths among PLWH could narrow disparities in life expectancy among some key populations, but other causes of death must be addressed to further narrow the disparities.

BackgroundUnhealthy alcohol use has adverse effects on HIV treatment. Screening, brief intervention, and referral to treatment (SBIRT) has some evidence of efficacy but may not be sufficient for those with low motivation or comorbid substance use.ObjectiveTo examine the effectiveness of motivational interviewing (MI) and emailed feedback (EF) among primary care HIV-positive patients, compared with treatment as usual care (UC) only, which included SBIRT.DesignRandomized clinical trial.ParticipantsSix hundred fourteen adult HIV-positive patients in Kaiser Permanente Northern California who reported prior-year unhealthy alcohol use.InterventionParticipants were randomized to either three sessions of MI (one in person and two by phone), information regarding alcohol risks via EF through a patient portal, or UC alone. MI and EF participants who reported unhealthy alcohol use at 6 months were offered additional MI and EF treatment, respectively.Main measuresParticipant-reported unhealthy alcohol use (defined as ≥ 4/≥ 5 drinks per day for women/men), alcohol problems at 12 months, based on blinded telephone interviews. Secondary outcomes included drug use and antiretroviral (ART) adherence.Key resultsAt 12 months, there were no overall group differences, but in all three arms, there were declines in unhealthy alcohol use and alcohol-related problems (p

BackgroundSubstance use disorders (SUDs) and psychiatric disorders are common among people with HIV (PWH) and lead to poor outcomes. Yet these conditions often go unrecognized and untreated in primary care.MethodsThe Promoting Access to Care Engagement (PACE) trial currently in process examines the impact of self-administered electronic screening for SUD risk, depression and anxiety in three large Kaiser Permanente Northern California primary care clinics serving over 5000 PWH. Screening uses validated measures (Tobacco, Alcohol, Prescription medication, and other Substance use [TAPS]; and the Adult Outcomes Questionnaire [AOQ], which includes the Patient Health Questionnaire [PHQ-9] and Generalized Anxiety Disorder [GAD-2]) delivered via three modalities (secure messaging, tablets in waiting rooms, and desktop computers in exam rooms). Results are integrated automatically into the electronic health record. Based on screening results and physician referrals, behavioral health specialists embedded in primary care initiate motivational interviewing- and cognitive behavioral therapy-based brief treatment and link patients to addiction and psychiatry clinics as needed. Analyses examine implementation (screening and treatment rates) and effectiveness (SUD, depression and anxiety symptoms; HIV viral control) outcomes using a stepped-wedge design, with a 12-month intervention phase implemented sequentially in the clinics, and a 24-month usual care period prior to implementation in each clinic functioning as sequential observational phases for comparison. We also evaluate screening and treatment costs and implementation barriers and facilitators.DiscussionThe study examines innovative, technology-facilitated strategies for improving assessment and treatment in primary care. Results may help to inform substance use, mental health, and HIV services.Trial registrationNCT03217058.

BackgroundHepatitis B virus (HBV) infection is a leading cause of end-stage liver disease (ESLD) and hepatocellular carcinoma (HCC) in HIV. Factors contributing to the high rates of liver complications among HIV/HBV-coinfected individuals remain unknown.SettingNorth American AIDS Cohort Collaboration on Research and Design.MethodsWe performed a retrospective cohort study among HIV/HBV-coinfected patients in 10 US and Canadian cohorts of the North American AIDS Cohort Collaboration on Research and Design that validated ESLD (ascites, spontaneous bacterial peritonitis, variceal hemorrhage, and/or hepatic encephalopathy) and HCC diagnoses from 1996 to 2010. Multivariable Cox regression was used to examine adjusted hazard ratios [aHRs with 95% confidence interval (CIs)] of liver complications (first occurrence of ESLD or HCC) associated with hypothesized determinants and with increasing durations of HIV suppression (≤500 copies/mL).ResultsAmong 3573 HIV/HBV patients with 13,790 person-years of follow-up, 111 liver complications occurred (incidence rate = 8.0 [95% CI: 6.6 to 9.7] events/1000 person-years). Rates of liver complication were increased with non-black/non-Hispanic race [aHR = 1.76 (1.13-2.74)], diabetes mellitus [aHR = 2.07 (1.20-3.57)], lower time-updated CD4 cell count [3.25: aHR = 9.79 (5.73-16.74); 1.45-3.25: aHR = 3.20 (1.87-5.47) versus FIB-4

PurposeUse of electronic health records (EHRs) in health research may lead to the false assumption of complete event ascertainment. We estimated "observation windows" (OWs), defined as periods within which the assumption of complete ascertainment of events is more likely to hold, as a quality control approach to reducing the likelihood of this false assumption. We demonstrated the impact of OWs on estimating the rates of type II diabetes mellitus (diabetes) from HIV clinical cohorts.MethodsData contributed by 16 HIV clinical cohorts to the NA-ACCORD were used to identify and evaluate OWs for an operationalized definition of diabetes occurrence as a case study. Procedures included (1) gathering cohort-level data; (2) visualizing and summarizing gaps in observations; (3) systematically establishing start and stop dates during which the assumption of complete ascertainment of diabetes events was reasonable; and (4) visualizing the diabetes OWs relative to the cohort open and close dates to identify immortal person-time. We estimated diabetes occurrence event rates and 95% confidence intervals in the most recent decade that data were available (January 1, 2007, to December 31, 2016).ResultsThe number of diabetes events decreased by 17% with the use of the diabetes OWs; immortal person-time was removed decreasing total person-years by 23%. Consequently, the diabetes rate increased from 1.23 (95% confidence interval [1.20, 1.25]) per 100 person-years to 1.32 [1.29, 1.35] per 100 person-years with the use of diabetes OWs.ConclusionsAs the use of EHR-curated data for event-driven health research continues to expand, OWs have utility as a quality control approach to complete event ascertainment, helping to improve accuracy of estimates by removing immortal person-time when ascertainment is incomplete.

BackgroundResearch is needed to better understand relations between immunosuppression and HIV viraemia and risk for non-Hodgkin lymphoma, a common cancer in people living with HIV. We aimed to identify key CD4 count and HIV RNA (viral load) predictors of risk for non-Hodgkin lymphoma, overall and by subtype.MethodsWe studied people living with HIV during 1996-2014 from 21 Canadian and US cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. To determine key independent predictors of risk for non-Hodgkin lymphoma, we assessed associations with time-updated recent, past, cumulative, and nadir or peak measures of CD4 count and viral load, using demographics-adjusted, cohort-stratified Cox models, and we compared models using Akaike's information criterion.FindingsOf 102 131 people living with HIV during the study period, 712 people developed non-Hodgkin lymphoma. The key independent predictors of risk for overall non-Hodgkin lymphoma were recent CD4 count (ie, lagged by 6 months;

BackgroundThe United States National HIV/AIDS Strategy established goals to reduce disparities in retention in human immunodeficiency virus (HIV) care, antiretroviral therapy (ART) use, and viral suppression. The impact of sex, age, and sexual HIV acquisition risk (ie, heterosexual vs same-sex contact) on the magnitude of HIV-related racial/ethnic disparities is not well understood.MethodsWe estimated age-stratified racial/ethnic differences in the 5-year restricted mean percentage of person-time spent in care, on ART, and virally suppressed among 19 521 women (21.4%), men who have sex with men (MSM; 59.0%), and men who have sex with women (MSW; 19.6%) entering HIV care in the North American AIDS Cohort Collaboration on Research and Design between 2004 and 2014.ResultsAmong women aged 18-29 years, whites spent 12.0% (95% confidence interval [CI], 1.1%-20.2%), 9.2% (95% CI, .4%-20.4%), and 13.5% (95% CI, 2.7%-22.5%) less person-time in care, on ART, and virally suppressed, respectively, than Hispanics. Black MSM aged ≥50 years spent 6.3% (95% CI, 1.3%-11.7%), 11.0% (95% CI, 4.6%-18.1%), and 9.7% (95% CI, 3.6%-16.8%) less person-time in these stages, respectively, than white MSM ≥50 years of age. Among MSM aged 40-49 years, blacks spent 9.8% (95% CI, 2.4%-16.5%) and 11.9% (95% CI, 3.8%-19.3%) less person-time on ART and virally suppressed, respectively, than whites.ConclusionsRacial/ethnic differences in HIV care persist in specific populations defined by sex, age, and sexual HIV acquisition risk. Clinical and public health interventions that jointly target these demographic factors are needed.