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OBJECTIVE: To describe retention in HIV care based on various definitions of retention in the modern treatment era. DESIGN: A cohort study of people enrolled in care at 7 mostly urban HIV clinics across the United States, 2010-2018. METHODS: We estimated retention based on missed visits, kept visits, kept encounters (clinical visits, CD4 counts, and viral loads), and HIV labs. We contrasted risk factors for retention by different definitions and estimated odds ratios for of viral suppression and hazard ratios for mortality in 2 years immediately following the year in which retention was defined (the study year). RESULTS: Across 108,171 person-years (N=21,481 people), in 71% of years people kept ≥75% of scheduled visits; in 78%, people kept ≥2 visits >90 days apart; in 74%, people had ≥2 HIV labs >90 days apart; and in 47%, people had no gaps >6 months in clinic visits. Missing >25% of scheduled visits despite attending ≥2 visits >90 days apart was associated with non-white non-Hispanic race/ethnicity, history of injection drug use, and prior AIDS diagnosis. In contrast, attending ≥75% of scheduled visits while not attending ≥2 visits >90 days apart was associated with male sex, white race, no injection drug use history, and no prior AIDS diagnosis. Subsequent viral non-suppression was more strongly associated with missed- than kept-visit measures of retention; 2-year mortality was only associated with failure to be retained by missed-visit measures. DISCUSSION: Missed and kept-visit definitions of retention capture different constructs. Missed-visit measures are more strongly associated with poor HIV outcomes.

BackgroundDuring the COVID-19 pandemic, patients experienced significant care disruptions, including lab monitoring. We investigated changes in the time between viral load (VL) checks for people with HIV associated with the pandemic.MethodsThis was an observational analysis of VLs of people with HIV in routine care at a large subspecialty clinic. At pandemic onset, the clinic temporarily closed its onsite laboratory. The exposure was time period (time-varying): pre-pandemic (January 1st 2019-March 15th, 2020); pandemic lab-closed (March 16th-July 12th, 2020); and pandemic lab-open (July 13th-December 31st, 2020). We estimated time from an index VL to a subsequent VL, stratified by whether the index VL was suppressed (≤200 copies/mL). We also calculated cumulative incidence of a non-suppressed VL following a suppressed index VL, and of re-suppression following a loss of viral suppression.ResultsCompared to pre-pandemic, hazard ratios for next VL check were: 0.34 (95% CI: 0.30, 0.37, lab-closed) and 0.73 (CI: 0.68, 0.78, lab-open) for suppressed patients; 0.56 (CI: 0.42, 0.79, lab-closed) and 0.92 (95% CI: 0.76, 1.10, lab-open) for non-suppressed patients. The 12-month cumulative incidence of loss of suppression was the same in the pandemic lab-open (4%) and pre-pandemic period (4%). The hazard of re-suppression following loss of suppression was lower during the pandemic lab-open versus the pre-pandemic period (hazard ratio: 0.68, 95% CI: 0.50, 0.92).ConclusionsEarly pandemic restrictions and lab closure significantly delayed VL monitoring. Once the lab re-opened, non-suppressed patients resumed normal monitoring. Suppressed patients still had a delay, but no significant loss of suppression.SummaryDuring the early COVID-19 pandemic, people with HIV experienced disruptions in viral load monitoring due to lab closure and pandemic restrictions. Loosening restrictions resolved delays for non-suppressed, but not suppressed patients. Delays did not significantly increase proportion of non-suppressed patients.

Describe engagement in HIV care over time after initial engagement in HIV care, by gender identity.Observational, clinical cohort study of people with HIV engaged in routine HIV care across the United States.We followed people with HIV who linked to and engaged in clinical care (attending ≥2 visits in 12 months) in cohorts in the North American Transgender Cohort Collaboration, 2000-2018. Within strata of gender identity, we estimated the 7-year (84-month) restricted mean time spent: lost-to-clinic (stratified by pre/postantiretroviral therapy (ART) initiation); in care prior to ART initiation; on ART but not virally suppressed; virally suppressed (≤200 copies/ml); or dead (pre/post-ART initiation).Transgender women ( N = 482/101 841) spent an average of 35.5 out of 84 months virally suppressed (this was 30.5 months for cisgender women and 34.4 months for cisgender men). After adjustment for age, race, ethnicity, history of injection drug use, cohort, and calendar year, transgender women were significantly less likely to die than cisgender people. Cisgender women spent more time in care not yet on ART, and less time on ART and virally suppressed, but were less likely to die compared with cisgender men. Other differences were not clinically meaningful.In this sample, transgender women and cisgender people spent similar amounts of time in care and virally suppressed. Additional efforts to improve retention in care and viral suppression are needed for all people with HIV, regardless of gender identity.

OBJECTIVES: Telemedicine became the primary mode of delivering care during the COVID-19 pandemic. We describe the impact of telemedicine on access to care for people with HIV (PWH) by comparing the proportion of PWH engaged in care prior to and during the COVID-19 pandemic. DESIGN AND METHODS: We conducted an observational analysis of patients enrolled in the Johns Hopkins HIV Clinical Cohort, a single-center cohort of patients at an urban HIV subspecialty clinic affiliated with an academic center. Due to the COVID-19 pandemic, the clinic transitioned from in-person to mostly telemedicine visits. We compared patients receiving care in two time periods. The pre-pandemic period included 2,010 people with ≥1 visit scheduled between September 1(st) 2019 and March 15(th) 2020. The pandemic period included 1,929 people with ≥1 visit scheduled between March 16(th) 2020 and September 30(th) 2020. We determined the proportion of patients completing ≥1 of their scheduled visits during each period. RESULTS: Visit completion increased significantly from 88% pre-pandemic to 91% during the pandemic (p=0.008). Visit completion improved significantly for patients age 20–39 (82% to 92%, p

BackgroundPeople undergoing revascularization for symptomatic peripheral artery disease (PAD) have a high incidence of major limb amputation in the year following their surgical procedure. The incidence of limb amputation is particularly high in patients from racial and ethnic minority groups. The purpose of our study was to investigate the role of sub-optimal prescription of preoperative antiplatelets and statins in producing disparities in risk of major amputation following revascularization for symptomatic PAD.MethodsWe used data from adult (≥18 years old) patients in the Vascular Quality Initiative (VQI) registry who underwent a revascularization procedure from 2011-2018. Patients were categorized as non-Hispanic Black, non-Hispanic White, and Hispanic. We estimated the crude probability of a patient being prescribed a preoperative antiplatelet and preoperative statin. We calculated one year risk incidence of amputation by prescription groups and by race/ethnicity. We estimated the amputation risk difference between race/ethnicity groups (the proportion of disparity) that could be eliminated under a hypothetical intervention where a pre-operative antiplatelet and statin was provided to all patients.ResultsAcross 100,579 revascularizations recorded in the Vascular Quality Initiative, a vascular procedure-based registry in the United States and Canada, 1-year risk of amputation was 2.5% (95% CI: 2.4%,2.6%) in White patients, 5.3% (4.9%,5.6%) in Black patients and 5.3% (4.7%,5.9%) in Hispanic patients. Black (57.5%) and Hispanic patients (58.7%) were only slightly less likely than White patients (60.9%) to receive recommended antiplatelet and statin therapy prior to their procedures. However, the effect of antiplatelets and statins was greater in Black and Hispanic patients such that, had all patients received the appropriate guideline recommended medications, the estimated risk difference comparing Black to White patients would have reduced by 8.9% (−2.9%,21.9%) and the risk difference comparing Hispanic to White patients would have been reduced by 17.6% (−0.7%,38.6%).ConclusionsEven though guideline-based care appeared evenly distributed by race/ethnicity, increasing access to such care may still decrease health care disparities in major limb amputation.

Direct-acting antivirals (DAA) are highly effective against hepatitis C virus (HCV) infection among persons with human immunodeficiency virus (PWH). However, alcohol use post-DAA treatment poses a continued threat to the liver. Whether the focus on liver health alone during HCV treatment can impact alcohol consumption is unclear. Therefore, we examined the change in alcohol use among HCV-coinfected PWH who received DAA therapy by non-addiction medical providers.In our longitudinal clinical cohort study, we identified HCV-coinfected PWH who received interferon-free DAA therapy between January 2014 and June 2019 in the Centers for AIDS Research Network of Integrated Clinical Systems. The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) was the alcohol screening instrument. We used mixed-effects logistic regression models to estimate the longitudinal change in alcohol use upon DAA therapy.Among 738 HCV-coinfected PWH, 339 (46 %) reported any alcohol use at the end of HCV treatment, including 113 (15 %) with high-risk use (i.e., AUDIT-C ≥3 for women, ≥4 for men). Concurrently, 280 (38 %) PWH noted active drug use, and 357 (48 %) were currently smoking. We observed no changes in the odds of any alcohol or high-risk alcohol use over time with DAA therapy. Findings were similar in the PWH subgroup with a history of alcohol use before DAA treatment.For PWH with HCV, alcohol use did not change following interferon-free DAA treatment by non-addiction medical providers. Thus, clinicians should consider integrating targeted alcohol use interventions into HCV care to motivate reduced alcohol consumption and safeguard future liver health.

In this paper, we propose a framework for thinking through the design and conduct of descriptive epidemiologic studies. A well-defined descriptive question aims to quantify and characterize some feature of the health of a population and must clearly state: 1) the target population, characterized by person and place, and anchored in time; 2) the outcome, event, or health state or characteristic; and 3) the measure of occurrence that will be used to summarize the outcome (e.g., incidence, prevalence, average time to event, etc.). Additionally, 4) any auxiliary variables will be prespecified and their roles as stratification factors (to characterize the outcome distribution) or nuisance variables (to be standardized over) will be stated. We illustrate application of this framework to describe the prevalence of viral suppression on December 31, 2019, among people living with human immunodeficiency virus (HIV) who had been linked to HIV care in the United States. Application of this framework highlights biases that may arise from missing data, especially 1) differences between the target population and the analytical sample; 2) measurement error; 3) competing events, late entries, loss to follow-up, and inappropriate interpretation of the chosen measure of outcome occurrence; and 4) inappropriate adjustment.

Background Opioid use is prevalent among people living with human immunodeficiency virus (HIV; PLWH) and adversely affects HIV outcomes. We assessed the effect of buprenorphine (BUP) initiation on subsequent HIV viral loads. Methods We identified PLWH from the Johns Hopkins HIV Clinical Cohort who initiated BUP between 2002 and 2017. Poisson regression with robust variance was used to estimate the prevalence of viral suppression ( Results We identified 279 PLWH who initiated BUP. After BUP initiation, PLWH were more likely to be virally suppressed (prevalence ratio [PR], 1.19; 95% confidence interval [CI], 1.03–1.37). After matching PLWH who initiated BUP to controls and accounting for measured and unmeasured confounders, BUP initiation increased viral suppression for both those on antiretroviral therapy (ART) at baseline (PERR PR, 1.08; 95% CI, 1.00–1.18) and those not on ART at baseline (PR, 1.31; 95% CI, 1.10–1.61). Conclusions Our results indicate that the initiation of BUP results in an increase in the probability of being virally suppressed after accounting for both measured and unmeasured confounders. Persons with opioid use disorder should initiate BUP to not only treat substance use but also to increase viral suppression allowing for treatment as prevention.

This prospective, nonrandomized implementation study evaluated a computerized brief intervention (CBI) for persons with HIV (PWH) and heavy/hazardous alcohol use. CBI was integrated into two HIV primary care clinics. Eligible patients were engaged in care, ≥18 years old, English speaking, endorsed heavy/hazardous alcohol use on the Alcohol Use Disorders Identification Test - C (AUDIT-C). Two 20-minute computerized sessions using cognitive behavioral techniques were delivered by a 3-D avatar on touch screen tablets. Of 816 eligible AUDIT-C scores, 537 (66%) resulted in CBI invitation, 226 (42%) of invited patients enrolled, and 176 (78%) of enrolled patients watched at least one session. CBI enrollment was associated with a significant average reduction of 9.1 drinks/week (95% CI: −14.5, −3.6) 4–12 months post-enrollment. Among those who participated in one or both sessions, average reduction in drinks/week was 11.7 drinks/week (95% CI: −18.8, −4.6). There was corresponding improvement in AUDIT-C scores. Overall patients reported high levels of intervention satisfaction, particularly among older and Black patients. These promising results point to a practical intervention for alcohol reduction in this vulnerable patient population with elevated rates of heavy/hazardous drinking. Future research should examine strategies to increase initial engagement, strengthen intervention effects to increase the number of patients who achieve non-hazardous drinking, and examine the duration of therapeutic effects.

BackgroundTelemedicine use for the care of people with HIV (PWH) was widely expanded during the COVID-19 pandemic. During 2021, as on-site care was re-introduced, care was delivered through a mixture of in-person and telemedicine. We studied how different patient populations used telemedicine in this hybrid-care environment.MethodsUsing observational data from patients enrolled in the Johns Hopkins HIV Clinical Cohort, we analyzed all in-person and telemedicine HIV primary care visits completed in an HIV clinic from January 1st, 2021 to December 30th, 2021. We used log-binomial regression models to investigate the association between patient characteristics and the probability of completing a telemedicine versus in-person visit. A secondary analysis of telemedicine visits investigated the probably of completing a video versus telephone visit.ResultsA total of 5,518 visits were completed by 1,884 patients; 4,282 (77.6%) visits were in-person, 800 (14.5%) by phone, and 436 (7.9%) by video. The relative risk (RR) of completing telemedicine vs. in-person visits was 0.65 (95% Confidence Interval (CI): 0.47, 0.91) for patients age 65+ vs. age 20-39; 0.84 (95% CI: 0.72, 0.98) for males vs. females; 0.81 (95% CI: 0.66, 0.99) for Black vs. white patients; 0.62 (95% CI: 0.49, 0.79) for patients in the highest vs. lowest quartile of Area Deprivation Index; and 1.52 (95% CI: 1.26, 1.84) for patients >15 miles vs. ConclusionsIn the second year of the pandemic, overall in-person care was utilized more than telemedicine, and significant differences persist across subgroups in telemedicine uptake.

Author(s): Haber, Noah A; Lesko, Catherine R; Fox, Matthew P; Powers, Kimberly A; Harling, Guy; Edwards, Jessie K; Salomon, Joshua A; Lippman, Sheri A; Bor, Jacob; Chang, Angela Y; Anglemyer, Andrew; Pettifor, Audrey | Abstract: ObjectivesThe Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 and other cross-sectional metrics can lead to potentially counterintuitive conclusions when used to evaluate health systems' performance. This study demonstrates how time and population dynamics impact UNAIDS 90-90-90 metrics in comparison with a longitudinal analogue.DesignA simplified simulation representing a hypothetical population was used to estimate and compare inference from UNAIDS 90-90-90 metrics and longitudinal metrics based on Kaplan-Meier-estimated 2-year probability of transition between stages.MethodsWe simulated a large cohort over 15 years. Everyone started out at risk for HIV, and then transitioned through the HIV care continuum based on fixed daily probabilities of acquiring HIV, learning status, entering care, initiating antiretroviral therapy (ART), and becoming virally suppressed, or dying. We varied the probability of ART initiation over three five-year periods (low, high, and low). We repeated the simulation with an increased probability of death.ResultsThe cross-sectional probability of being on ART among persons who were diagnosed responded relatively slowly to changes in the rate of ART initiation. Increases in ART initiation rates caused apparent declines in the cross-sectional probability of being virally suppressed among persons who had initiated ART, despite no changes in the rate of viral suppression. In some cases, higher mortality resulted in the cross-sectional metrics implying improved healthcare system performance. The longitudinal continuum was robust to these issues.ConclusionThe UNAIDS 90-90-90 care continuum may lead to incorrect inference when used to evaluate health systems performance. We recommend that evaluation of HIV care delivery include longitudinal care continuum metrics wherever possible.

Objective: Claudication is an early-stage subtype of peripheral artery disease that may result in surgical intervention. The purpose of this study was to compare the types of elective bypass in a population of Black and White patients with claudication and to identify actionable areas that may explain the higher limb amputation rates observed in Black patients. Methods: We identified Black and White patients undergoing elective infrainguinal bypass for claudication using data from the Vascular Quality Initiative registry (2011-2018). Distal bypass target was classified as 1) at or above the popliteal artery (above-knee) or 2) below the popliteal, including all tibial, peroneal, dorsalis pedis and tarsal/plantar arteries (below-knee). Graft conduit was categorized as vein or prosthetic. We calculated one-year risk of major lower limb amputation with 95% confidence intervals (CI) for all combinations of target and conduit, stratified by race. We then forced an intervention on the data to estimate the post-intervention incidence of amputation and the proportion of racial disparity eliminated and 95% CI if everyone received the gold standard treatment (above-knee, vein). Results: We identified 8,401 infrainguinal bypass revascularizations for claudication (12% Black/88% White); 82% were performed above-knee and 44% of those used a vein conduit. The remaining 18% of bypasses were to below-knee arteries, of which 78% used a vein conduit. The remaining 1,534 (18.3%) bypasses were to below-knee arteries, including 1,197 (78.4%) using vein and 330 (21.6%) using prosthetic material. One-year incidence of major limb amputation was 1.6% (1.3%,1.9%) among all grafts, 1.2% (1.0%,1.5%) in above-knee grafts, and 3.3% (2.4%,4.2%) in below-knee grafts. Black patients had higher incidence of amputation across bypass target/conduit groups compared to White patients; the difference was greatest for below-knee revascularizations (8.9%, 95% CI: 4.8%,12.3% v 2.1%, 95% CI: 0.9%,2.9%). Pre-intervention amputation incidence was 1.3% (1.0%,1.5%) in White patients and 3.6% (1.9%,5.2%) in Black patients. Overall amputation incidence decreased significantly after our gold standard intervention was applied for both White (1.0%; 0.7%,1.2%) and Black (2.0%; 0.7%,3.2%) patients. The risk difference (i.e. the disparity gap) between Black and White patients was lessened post-intervention by 56.8% (31.9%,116.3%). Conclusions: We observed risk of amputation higher than would be expected based on other studies of the natural history of claudication without bypass surgery; future work should identify the mechanisms that alter the natural history of claudication via open bypass surgery. Interventions below-knee or using a prosthetic graft were particularly harmful and their harm was concentrated in Black patients.

Objective: Peripheral artery disease (PAD) is a common atherosclerotic disorder that reduces blood flow to the lower extremities. There are significant racial disparities in the outcomes of patients with PAD. Ideally, understanding the result of inadequate implementation of proven interventions on health disparities might provoke a policy and culture shift in the provision of care for minoritized persons. We demonstrate a method that leverages knowledge of interventions that we know should be implemented to optimize care for people with PAD, to identify the extent to which disparities might be mitigated by more universal uptake of those interventions. Methods: We compare racial disparities as they exist currently with disparities that would exist under complete uptake of interventions to improve PAD and vascular care. This counterfactual world is modeled by upweighting people who received the proposed interventions to represent the study population at the start of follow-up. It relies on the assumption that we have measured (and adjusted for) all confounders of the intervention (a hypothesized mediator of the observed health disparities) and the outcome. A unique feature of the application of this method to this problem is our ability to demonstrate how, even when guideline-based care appears evenly distributed by race/ethnicity, increasing access to such care may still decrease health disparities. This method was previously proposed for estimating potential reductions in racial disparities for people with HIV. Results: Across 100,579 infrainguinal revascularizations among Black (n=15,442), Hispanic (n=5,506) and White (n=67,651) patients treated for symptomatic PAD, Black (56.5%) and Hispanic patients (57.6%) were slightly less likely than White patients (59.8%) to receive Class I recommended aspirin and statin therapy prior to their procedures. One-year risk of amputation was 2.7% (95% CI: 2.6%,2.8%) in White patients, 5.8% (5.4%,6.2%) in Black patients and 5.6% (5.0%,6.2%) in Hispanic patients. Had all patients received the appropriate anti-ischemic medications, amputation risk would have been lower across all three race-ethnicity groups. However, specifically, the risk difference (RD) for Black vs White patients would have reduced by 8% (-3%,20%) and the RD for Hispanic vs White patients would have reduced by 18% (-1%,36%). Conclusions: Not only is provision of aspirin and statin for infrainguinal revascularization good for all PAD patients, it is also a social justice imperative.

Background Racial and ethnic disparities in outcomes following lower limb revascularization for peripheral artery disease have been ascribed to disease severity at presentation for surgery. Methods and Results We calculated 1‐year risk of major adverse limb events (MALEs), major amputation, and death for patients undergoing elective revascularization for claudication or chronic limb‐threatening ischemia in the Vascular Quality Initiative data (2011–2018). We report hazard ratios according to race and ethnicity using Cox (death) or Fine and Gray subdistribution hazards models (MALE and major amputation, treating death as a competing event), adjusted for patient, treatment, and anatomic factors associated with disease severity. Among 88 599 patients (age, 69 years; 37% women), 1‐year risk of MALE (major amputation and death) was 12.8% (95% CI, 12.5–13.0) in 67 651 White patients, 16.5% (95% CI, 5.8–7.8) in 15 442 Black patients, and 17.2% (95% CI, 5.6–6.9) in 5506 Hispanic patients. Compared with White patients, we observed an increased hazard of poor limb outcomes among Black (MALE: 1.17; 95% CI, 1.12–1.22; amputation: 1.52; 95% CI, 1.39–1.65) and Hispanic (MALE: 1.22; 95% CI, 1.14–1.31; amputation: 1.45; 95% CI, 1.28–1.64) patients. However, Black and Hispanic patients had a hazard of death of 0.85 (95% CI, 0.79–0.91) and 0.71 (95% CI, 0.63–0.79) times the hazard among White patients, respectively. Worse limb outcomes were observed among Black and Hispanic patients across subcohorts of claudication and chronic limb‐threatening ischemia. Conclusions Black and Hispanic patients undergoing infrainguinal revascularization for chronic limb‐threatening ischemia and claudication had worse limb outcomes compared with White patients, even with similar disease severity at presentation. Additional investigation aimed at eliminating disparate limb outcomes is needed.

We estimated joint associations between having history of alcohol use disorder (AUD) (based on prior ICD-9/ICD-10 codes) and recent self-reported alcohol use and viral non-suppression (≥ 1 viral load measurement > 20 copies/mL in the same calendar year as alcohol consumption was reported) among patients on ART enrolled in routine care, 2014–2018, in an urban specialty clinic. Among 1690 patients, 26% had an AUD, 21% reported high-risk alcohol use, and 39% had viral non-suppression. Relative to person-years in which people without AUD reported not drinking, prevalence of viral non-suppression was higher in person-years when people with AUD reported drinking at any level; prevalence of viral non-suppression was not significantly higher in person-years when people with AUD reported not drinking or person-years when people without AUD reported drinking at any level. No level of alcohol use may be “safe” for people with a prior AUD with regard to maintaining viral suppression.

BackgroundThe COVID-19 pandemic disrupted the normal delivery of HIV care, altered social support networks, and caused economic insecurity. People with HIV (PWH) are vulnerable to such disruptions, particularly if they have a history of substance use. We describe engagement in care and adherence to antiretroviral therapy (ART) for PWH during the pandemic.MethodsFrom May 2020 to February 2021, 773 PWH enrolled in 6 existing cohorts completed 1495 surveys about substance use and engagement in HIV care during the COVID-19 pandemic. We described the prevalence and correlates of having missed a visit with an HIV provider in the past month and having missed a dose of ART in the past week.ResultsThirteen percent of people missed an HIV visit in the past month. Missing a visit was associated with unstable housing, food insecurity, anxiety, low resiliency, disruptions to mental health care, and substance use including cigarette smoking, hazardous alcohol use, cocaine, and cannabis use. Nineteen percent of people reported missing at least one dose of ART in the week prior to their survey. Missing a dose of ART was associated with being a man, low resiliency, disruptions to mental health care, cigarette smoking, hazardous alcohol use, cocaine, and cannabis use, and experiencing disruptions to substance use treatment.ConclusionsSocial determinants of health, substance use, and disruptions to mental health and substance use treatment were associated with poorer engagement in HIV care. Close attention to continuity of care during times of social disruption is especially critical for PWH.

BackgroundAlcohol use during the COVID-19 pandemic increased. People living with HIV or at risk for HIV acquisition often have psycho-social and structural barriers or co-occurring substance use making them vulnerable to the adverse effects of alcohol. We describe factors associated with alcohol use during the COVID-19 pandemic in this group.MethodsFrom May 2020 to February 2021, 1984 people enrolled in 6 existing cohort studies completed surveys about alcohol and other drug use during the COVID-19 pandemic. We describe the past-month prevalence of no alcohol use, low-risk use, and hazardous use. We use multinomial regression to describe factors associated with low-risk or hazardous alcohol use relative to no alcohol use.ResultsForty-five percent of participants reported no alcohol use, 33% low-risk use, and 22% hazardous use in the past 30 days. Cannabis and stimulant use were associated with a higher prevalence of low-risk use relative to no use. Tobacco, stimulant, cannabis use and recent overdose were associated with a higher prevalence of hazardous use relative to no use. Substance use treatment and living with HIV were associated with a lower prevalence of low-risk or hazardous use relative to no use.ConclusionsStimulant use was strongly associated with a higher prevalence of hazardous alcohol use while engagement in substance use treatment or living with HIV was associated with a lower prevalence. Ascertaining hazardous alcohol and other drug use, particularly stimulants, in clinical care could identify people at higher risk for adverse outcome and harm reduction counseling.

Evidence from randomized controlled trials available for timely health technology assessments of new pharmacological treatments and regulatory decision making may not be generalizable to local patient populations, often resulting in decisions being made under uncertainty. In recent years, several reweighting approaches have been explored to address this important question of generalizability to a target population. We present a case study of the Innovative Medicines Initiative to illustrate the inverse propensity score reweighting methodology, which may allow us to estimate the expected treatment benefit if a clinical trial had been run in a broader real‐world target population. We learned that identifying treatment effect modifiers, understanding and managing differences between patient characteristic data sets, and balancing the closeness of trial and target patient populations with effective sample size are key to successfully using this methodology and potentially mitigating some of this uncertainty around local decision making.

BACKGROUND: In time-to-event analyses, there is limited guidance on when persons who are lost to follow-up (LTFU) should be censored. METHODS: We simulated bias in risk estimates for: (1) a composite event of measured (outcome only observable in a patient encounter) and captured events (outcome observable outside a patient encounter); and a (2) measured or (3) captured event in the presence of a competing event of the other type, under three censoring strategies: (i) censor at the last study encounter; (ii) censor when LTFU definition is met; and (iii) a new, hybrid censoring strategy. We demonstrate the real-world impact of this decision by estimating: (1) time to Acquired Immune Deficiency Syndrome diagnosis (AIDS) or death, (2) time to initiation of antiretroviral therapy (ART), and (3) time to death prior to ART initiation among adults engaged in HIV care. RESULTS: For (1) our hybrid censoring strategy was least biased. In our example, 5-year risk of AIDS or death was over-estimated using last-encounter censoring (25%) and under-estimated using LTFU-definition censoring (21%), compared to results from our hybrid approach (24%). Last-encounter censoring was least biased for (2). When estimating 5-year risk of ART initiation, LTFU-definition censoring underestimated risk (80% versus 85% using last-encounter censoring). LTFU-definition censoring was least biased for (3). When estimating 5-year risk of death before ART initiation, last-encounter censoring overestimated risk (5.2% versus 4.7% using LTFU-definition censoring). CONCLUSIONS: The least biased censoring strategy for time-to-event analyses in the presence of LTFU depends on the event and estimand of interest.

High mortality rates among persons with HIV with a history of injection drug use (PWID) are thought to be driven in part by higher rates of external cause-related mortality. We followed 4,796 persons aged 18–70 engaged in continuity HIV care from 2001–2015 until death or administrative censoring. We compared cause-specific (csHR) and subdistribution hazards (sdHR) of death due to external causes among PWID and persons who acquired their HIV infection through other routes (non-IDU). We standardized estimates on age, sex, race, and HIV-related health status. The standardized csHR for external cause-related death was 3.57 (95% CI: 2.39, 5.33), and the sdHR was 3.14 (95% CI: 2.16, 4.55). The majority of external cause-related deaths were overdose-related and standardized sdHR was 4.02 (95% CI: 2.40, 6.72). Absolute rate of suicide was low but the csHR for PWID compared to non-IDU was most elevated for suicide (6.50, 95% CI: 1.51, 28.03). HIV-infected PWID are at a disproportionately increased risk of death due to external causes, particularly overdose and suicide.

Epidemiology should aim to improve population health; however, no consensus exists regarding the activities and skills that should be prioritized to achieve this goal. We performed a scoping review of articles addressing the translation of epidemiologic knowledge into improved population health outcomes. We identified 5 themes in the translational epidemiology literature: foundations of epidemiologic thinking, evidence-based public health or medicine, epidemiologic education, implementation science, and community-engaged research (including literature on community-based participatory research). We then identified 5 priority areas for advancing translational epidemiology: 1) scientific engagement with public health; 2) public health communication; 3) epidemiologic education; 4) epidemiology and implementation; and 5) community involvement. Using these priority areas as a starting point, we developed a conceptual framework of translational epidemiology that emphasizes interconnectedness and feedback among epidemiology, foundational science, and public health stakeholders. We also identified 2–5 representative principles in each priority area that could serve as the basis for advancing a vision of translational epidemiology. We believe an emphasis on translational epidemiology can help the broader field to increase the efficiency of translating epidemiologic knowledge into improved health outcomes and to achieve its goal of improving population health.

Purpose Health plan disenrollment occurs frequently in commercial insurance claims databases. If individuals who disenroll are different from those who remain enrolled, informative censoring may bias descriptive statistics as well as estimates of causal effect. We explored whether patterns of disenrollment varied by patient or health plan characteristics. Methods In a large cohort of commercially insured adults (2007-2013), we examined two primary outcomes: (a) within-year disenrollment between January 1 and December 30, which was considered to occur due to patient disenrollment from the health plan, and (b) end-of-year disenrollment on December 31, which was considered to occur due to either patient disenrollment from the health plan or withdrawal of the entire health plan from the commercial insurance database. In yearly cohorts, we identified factors independently associated with disenrollment by using log-binomial regression models to estimate risk ratios (RR) and 95% confidence intervals (CI). Results Among 2 053 100 unique patient years, the annual proportion of within-year disenrollment remained steady across years (range, 13% to 14%) whereas the annual proportion of end-of-year disenrollment varied widely (range, 8% to 26%). Independent predictors of within-year disenrollment were related to health status, including age, comorbidities, frailty, hospitalization, emergency room visits, use of durable medical equipment, use of preventive care, and use of prescription medications. In contrast, independent predictors of end-of-year disenrollment were related to health plan characteristics including insurance plan type and geographic characteristics. Conclusions Differential risk of disenrollment suggests that analytic approaches to address selection bias should be considered in studies using commercial insurance databases.

OBJECTIVE The aim of this study was to describe the risk of viral nonsuppression across the depression care cascade. DESIGN A clinical cohort study. METHODS We used depressive symptoms (PHQ-8 ≥ 10) self-reported on computer-assisted surveys, clinical diagnoses of depression in the medical record in the prior year and pharmacologic (any prescription for an antidepressant) and psychologic treatments for depression (attendance at at least two mental health visits in the prior year) to classify patients into groups: no history of depression; prior depression diagnosis; current indication for depression treatment (symptoms or clinical diagnosis); and treated depression (stratified by presence of persistent symptoms). We associated position in the depression care cascade with viral nonsuppression (>200 copies/ml) 7 days before to 6 months after the index self-report of depressive symptoms. RESULTS History of depression [adjusted risk difference (aRD) relative to no history = 5.9%, 95% confidence interval (95% CI): 1.5-10.3] and current depression (symptoms or diagnosis) in the absence of treatment (aRD relative to no current depression or depression treatment = 4.8%, 95% CI: 1.8-7.8) were associated with a higher risk of viral nonsuppression than no history of depression. Depression treatment mitigated this association (aRD = -0.4%, 95% CI: -2.5 to 1.7). CONCLUSION The relationship between depression care cascade and viral suppression is complex. Untreated depression and clinically unrecognized depressive symptoms were both related to viral nonsuppression. Treated depression was not associated with viral nonsuppression; however, a high proportion of treated patients still had depressive symptoms. Depression treatment should be titrated if patients' symptoms are not responsive and patients with a history of depression should be monitored for ART adherence.

Background: Although antiretroviral therapy (ART) is known to be protective against HIV-related mortality, the expected magnitude of effect is unclear because existing estimates of the effect of ART may not directly generalize to recently HIV-diagnosed persons.

PURPOSE OF REVIEW: Epidemiologists frequently must handle competing events, which prevent the event of interest from occurring. We review considerations for handling competing events when interpreting results causally. RECENT FINDINGS: When interpreting statistical associations as causal effects, we recommend following a causal inference “roadmap” as one would in an analysis without competing events. There are, however, special considerations to be made for competing events when choosing the causal estimand that best answers the question of interest, selecting the statistical estimand (e.g. the cause-specific or subdistribution) that will target that causal estimand, and assessing whether causal identification conditions (e.g., conditional exchangeability, positivity, and consistency) have been sufficiently met. SUMMARY: When doing causal inference in the competing events setting, it is critical to first ascertain the relevant question and the causal estimand that best answers it, with the choice often being between estimands that do and do not eliminate competing events.

Nearly every introductory epidemiology course begins with a focus on person, place, and time, the key components of descriptive epidemiology. And yet in our experience, introductory epidemiology courses were the last time we spent any significant amount of training time focused on descriptive epidemiology. This gave us the impression that descriptive epidemiology does not suffer from bias and is less impactful than causal epidemiology. Descriptive epidemiology may also suffer from a lack of prestige in academia and may be more difficult to fund. We believe this does a disservice to the field and slows progress towards goals of improving population health and ensuring equity in health. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak and subsequent coronavirus disease 2019 pandemic have highlighted the importance of descriptive epidemiology in responding to serious public health crises. In this commentary, we make the case for renewed focus on the importance of descriptive epidemiology in the epidemiology curriculum using SARS-CoV-2 as a motivating example. The framework for error we use in etiological research can be applied in descriptive research to focus on both systematic and random error. We use the current pandemic to illustrate differences between causal and descriptive epidemiology and areas where descriptive epidemiology can have an important impact.

Background Collaborative research often combines findings across multiple, independent studies via meta-analysis. Ideally, all study estimates that contribute to the meta-analysis will be equally unbiased. Many meta-analyses require all studies to measure the same covariates. We explored whether differing minimally sufficient sets of confounders identified by a directed acyclic graph (DAG) ensures comparability of individual study estimates. Our analysis applied four statistical estimators to multiple minimally sufficient adjustment sets identified in a single DAG. Methods We compared estimates obtained via linear, log-binomial, and logistic regression and inverse probability weighting, and data were simulated based on a previously published DAG. Results Our results show that linear, log-binomial, and inverse probability weighting estimators generally provide the same estimate of effect for different estimands that are equally sufficient to adjust confounding bias, with modest differences in random error. In contrast, logistic regression often performed poorly, with notable differences in effect estimates obtained from unique minimally sufficient adjustment sets, and larger standard errors than other estimators. Conclusions Our findings do not support the reliance of collaborative research on logistic regression results for meta-analyses. Use of DAGs to identify potentially differing minimally sufficient adjustment sets can allow meta-analyses without requiring the exact same covariates.

PURPOSE OF REVIEW: “Target bias” is the difference between an estimate of association from a study sample and the causal effect in the target population of interest. It is the sum of internal and external bias. Given the extensive literature on internal validity, here, we review threats and methods to improve external validity. RECENT FINDINGS: External bias may arise when the distribution of modifiers of the effect of treatment differs between the study sample and the target population. Methods including those based on modeling the outcome, modeling sample membership, and doubly robust methods are available, assuming data on the target population is available. SUMMARY: The relevance of information for making policy decisions is dependent on both the actions that were studied and the sample in which they were evaluated. Combining methods for addressing internal and external validity can improve the policy relevance of study results.

In response to the threat posed by the coronavirus disease 2019 (COVID-19) pandemic, many universities are encouraging or requiring online instruction. Teaching an epidemiology course online is different in many respects from teaching in person. In this article, we review specific approaches and strategies related to teaching epidemiology online during the pandemic and beyond, including a discussion of options for course format, grading and assessment approaches, pandemic-related contingencies, and the use of technology. Throughout this article we present practical, epidemiology-specific teaching examples. Moreover, we also examine 1) how the lessons learned about the practice of epidemiology during the pandemic can be integrated into the didactic content of epidemiology training programs and 2) whether epidemiologic pedagogy and teaching strategies should change in the long term, beyond the COVID-19 pandemic. The pandemic has served to heighten our awareness of concerns related to student health and safety, as well as issues of accessibility, equity, and inclusion. Our goal is to present a practical overview connecting pandemic-era online teaching with thoughts about the future of epidemiologic instruction.

Learning health systems use data to generate knowledge that informs clinical care, but few studies have evaluated how to leverage patient-reported mental health symptoms and substance use data to make patient-specific predictions. We developed a general Bayesian prediction algorithm that uses self-reported psychiatric symptoms and substance use within a population to predict future symptoms and substance use for individuals in that population. We validated our approach in 2444 participants from two clinical cohorts - the National Network of Depression Centers and the Johns Hopkins HIV Clinical Cohort - by predicting symptoms of depression, anxiety, and mania as well as alcohol, heroin, and cocaine use and comparing our predictions to observed symptoms and substance use. When we dichotomized mental health symptoms as moderate-severe vs. none-mild, individual predictions yielded areas under the ROC curve (AUCs) of 0.84 [95% confidence interval 0.80-0.88] and 0.85 [0.82-0.88] for symptoms of depression in the two cohorts, AUCs of 0.84 [0.79-0.88] and 0.85 [0.82-0.88] for symptoms of anxiety, and an AUC of 0.77 [0.72-0.82] for manic symptoms. Predictions of substance use yielded an AUC of 0.92 [0.88-0.97] for heroin use, 0.90 [0.82-0.97] for cocaine use, and 0.90 [0.88-092] for alcohol misuse. This rigorous, mathematically grounded approach could provide patient-specific predictions at the point of care. It can be applied to other psychiatric symptoms and substance use indicators, and is customizable to specific health systems. Such approaches can realize the potential of a learning health system to transform ever-increasing quantities of data into tangible guidance for patient care.

Background In some time-to-event analyses, it is unclear whether loss to follow up should be treated as a censoring event or competing event. Such ambiguity is particularly common in HIV research that uses routinely collected clinical data to report the timing of key milestones along the HIV care continuum. In this setting, loss to follow up may be viewed as a censoring event, under the assumption that patients who are "lost" from a study clinic immediately enroll in care elsewhere, or a competing event, under the assumption that people "lost" are out of care all together. Methods We illustrate an approach to address this ambiguity when estimating the 2-year risk of antiretroviral treatment initiation among 19,506 people living with HIV who enrolled in the IeDEA Central Africa cohort between 2006 and 2017, along with published estimates from tracing studies in Africa. We also assessed the finite sample properties of the proposed approach using simulation experiments. Results The estimated 2-year risk of treatment initiation was 69% if patients were censored at loss to follow up or 59% if losses to follow up were treated as competing events. Using the proposed approach, we estimated that the 2-year risk of antiretroviral therapy initiation was 62% (95% confidence interval: 61, 62). The proposed approach had little bias and appropriate confidence interval coverage under scenarios examined in the simulation experiments. Conclusions The proposed approach relaxes the assumptions inherent in treating loss to follow up as a censoring or competing event in clinical HIV cohort studies.

PURPOSE: A comparison of stage at cancer diagnosis and cancer treatment rates between people with HIV (PWH) and the general US population is needed to identify any disparities by HIV status. METHODS: We compared 236 PWH in clinical care diagnosed with cancer from 1997 to 2014 to a sample from NCI’s Surveillance, Epidemiology and End Results (SEER) Program, presumed to be HIV negative. We performed G-computation using random forest methods to estimate stage and treatment percent differences (PD) by HIV. We conducted sensitivity analyses among non-AIDS-defining cancers (NADC), by sex and by CD4 ≤ 200 or > 200 cells/mm(3). RESULTS: PWH were less likely to be diagnosed at localized stage (PD = − 16%; 95% CI − 21, − 11) and more likely to be diagnosed at regional stage (PD = 14%; 95% CI 8, 19) than those in SEER. Cancer treatment rates were 13% lower among PWH as compared to SEER (95% CI − 18, − 8). The difference in percent receiving cancer treatment was more pronounced for those with lower CD4 at cancer diagnosis (PD −15%; 95% CI − 27, − 6). Lower treatment rates were observed among NADC, males, and women with CD4 ≤ 200. CONCLUSION: Cancer care for PWH could be improved by diagnosis at earlier stages and increasing rates of cancer treatment.

Background Excess adiposity, which affects 69% of US adults, increases coronary heart disease ( CHD ) risk in an association that manifests below conventional obesity cut points. The population‐level impact on CHD risk that is attainable through modest adiposity reductions in populations is not well characterized. We estimated the effect of hypothetical reductions in both body mass index ( BMI ) and waist circumference ( WC ) on CHD incidence. Methods and Results The study population included 13 610 ARIC (Atherosclerosis Risk in Communities) participants. Our hypothetical reduction in BMI or WC was applied relative to the temporal trend, with no hypothetical reduction among those with BMI >24 or WC >88 cm, respectively. This threshold for hypothetical reduction is near the clinical guidelines for excess adiposity. CHD risk differences compared the hypothetical reduction with no reduction. Sensitivity analysis was conducted to estimate the effect of applying the hypothetical BMI reduction at the established overweight cut point of 25. Cumulative 12‐year CHD incidence with no intervention was 6.3% (95% CI, 5.9–6.8%). Risk differences following the hypothetical BMI and WC reductions were −0.6% (95% CI, −1.0% to −0.1%) and −1.0% (95% CI, −1.4% to −0.5%), respectively. These results were robust for the sensitivity analyses. Consequently, we estimated that this hypothetical reduction of 5% in BMI and WC, respectively, could have prevented 9% and 16%, respectively, of the CHD events occurring in this study population over 12 years, after adjustment for established CHD risk factors. Conclusions Meaningful CHD risk reductions could derive from modest reductions in adiposity attainable through lifestyle modification.

Randomized trials are considered the gold standard for estimating causal effects. Trial findings are often used to inform policy and programming efforts, yet their results may not generalize well to a relevant target population due to potential differences in effect moderators between the trial and population. Statistical methods have been developed to improve generalizability by combining trials and population data, and weighting the trial to resemble the population on baseline covariates. Large-scale surveys in fields such as health and education with complex survey designs are a logical source for population data; however, there is currently no best practice for incorporating survey weights when generalizing trial findings to a complex survey. We propose and investigate ways to incorporate survey weights in this context. We examine the performance of our proposed estimator in simulations by comparing its performance to estimators that ignore the complex survey design. We then apply the methods to generalize findings from two trials - a lifestyle intervention for blood pressure reduction and a web-based intervention to treat substance use disorders - to their respective target populations using population data from complex surveys. The work highlights the importance in properly accounting for the complex survey design when generalizing trial findings to a population represented by a complex survey sample.

In recent years, increasing attention has been paid to problems of external validity, specifically to methodological approaches for both quantitative generalizability and transportability of study results. However, most approaches to these issues have considered external validity separately from internal validity. Here we argue that considering either internal or external validity in isolation may be problematic. Further, we argue that a joint measure of the validity of an effect estimate with respect to a specific population of interest may be more useful: We call this proposed measure target validity. In this work, we introduce and formally define target bias as the total difference between the true causal effect in the target population and the estimated causal effect in the study sample, and target validity as target bias = 0. We illustrate this measure with a series of examples and show how this measure may help us to think more clearly about comparisons between experimental and nonexperimental research results. Specifically, we show that even perfect internal validity does not ensure that a causal effect will be unbiased in a specific target population.

INTRODUCTION: Few studies examine how depression and substance use interact to affect HIV control. METHODS: In 14,380 persons with HIV (PWH), we used logistic regression and generalized estimating equations to evaluate how symptoms of depression interact with alcohol, cocaine, opioid, and methamphetamine use to affect subsequent retention in care, maintaining an active prescription for ART, and consistent virologic suppression. RESULTS: Among PWH with no or mild depressive symptoms, heavy alcohol use had no association with virologic suppression (OR 1.00 [0.95–1.06]); among those with moderate or severe symptoms, it was associated with reduced viral suppression (OR 0.80 [0.74–0.87]). We found no interactions with heavy alcohol use on retention in care or maintaining ART prescription or with other substances for any outcome. DISCUSSION: These results highlight the importance of treating moderate or severe depression in PWH, especially with comorbid heavy alcohol use, and support multifaceted interventions targeting alcohol use and depression.

Background The 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. Methods We 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. Results Among 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. Conclusions Racial/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.

Background Alcohol misuse is associated with increased human immunodeficiency virus sexual risk behaviors by women. Drug use, intimate partner violence (IPV), and depressive symptoms frequently co-occur, are well-recognized alcohol misuse comorbidities, and may interact to increase risk behaviors. Using a syndemic framework we examined associations between drug use, IPV, and depressive symptoms and sexual risk behaviors by 400 women with alcohol misuse attending an urban sexually transmitted infections clinic. Methods Participants completed computer-assisted interviews querying drug use, IPV, and depressive symptoms and sexual risk behavior outcomes—unprotected sex under the influence of alcohol, sex for drugs/money, and number of lifetime sexual partners. We used multivariable analysis to estimate prevalence ratios (PR) for independent and joint associations between drug use, IPV, and depressive symptoms and our outcomes. To investigate synergy between risk factors we calculated the relative excess prevalence owing to interaction for all variable combinations. Results In multivariable analysis, drug use, IPV, and depressive symptoms alone and in combination were associated with higher prevalence/count of risk behaviors compared with women with alcohol misuse alone. The greatest prevalence/count occurred when all three were present (unprotected sex under the influence of alcohol [PR, 2.6; 95% confidence interval, 1.3–4.9]), sex for money or drugs [PR, 2.6; 95% confidence interval, 1.7–4.2], and number of lifetime partners [PR, 3.2; 95% confidence interval, 1.9–5.2]). Drug use, IPV, and depressive symptoms did not interact synergistically to increase sexual risk behavior prevalence. Conclusions A higher prevalence of sexual risk behaviors by women with alcohol misuse combined with drug use, IPV, and depressive symptoms supports the need for alcohol interventions addressing these additional comorbidities.

Accurate, routine measurement of recent illicit substance use is challenging. The Johns Hopkins Human Immunodeficiency Virus Clinical Cohort (Baltimore, Maryland) collects 2 imperfect but routine measurements of recent substance use: medical record review and self-interview. We used Bayesian latent class modeling to estimate sensitivity and specificity of each measurement as well as prevalence of substance use among 2,064 patients engaged in care during 2007-2015. Sensitivity of medical record review was higher than sensitivity of self-interview for cocaine and heroin use; posterior estimates ranged from 44% to 76% for cocaine use and from 39% to 67% for heroin use, depending on model assumptions and priors. In contrast, sensitivity of self-interview was higher than sensitivity of medical record review for any alcohol use, hazardous alcohol use, and cigarette smoking. Posterior estimates of sensitivity of self-interview were generally above 80%, 85%, and 87% for each substance, respectively. Specificity was high for all measurements. From one model, we estimated prevalence of substance use in the cohort to be 12.5% for cocaine, 9.3% for heroin, 48.5% for alcohol, 21.4% for hazardous alcohol, and 55.4% for cigarettes. Prevalence estimates from other models were generally comparable. Measurement error of substance use is nontrivial and should be accounted for in subsequent analyses.