Incidence of prostate cancer in Medicaid beneficiaries with and without HIV in 2001-2015 in 14 states.

Background: Prostate cancer is projected to be the most common cancer among people living with HIV; however, incidence of prostate cancer has been reported to be lower in men with HIV compared to men without HIV with little evidence to explain this difference. We describe prostate cancer incidence by HIV status in Medicaid beneficiaries, allowing for comparison of men with and without HIV who are similar with respect to socioeconomic characteristics and access to healthcare. Methods: Medicaid beneficiaries (N=15,167,636) aged 18-64 with ≥7 months of continuous enrollment during 2001-2015 in 14 US states were retained for analysis. Diagnoses of HIV and prostate cancer were identified using inpatient and other non-drug claims. We estimated cause-specific (csHR) and sub-distribution hazard ratios comparing incidence of prostate cancer by HIV status, adjusted for age, race-ethnicity, state of residence, year of enrollment, and comorbid conditions. Models were additionally stratified by age and race-ethnicity. Results: There were 366 cases of prostate cancer observed over 299,976 person-years among beneficiaries with HIV and 17,224 cases over 22,298,914 person-years in beneficiaries without HIV. The hazard of prostate cancer was lower in men with HIV than men without HIV (csHR=0.89; 95% CI: 0.80, 0.99), but varied by race-ethnicity, with similar observations among non-Hispanic Black (csHR=0.79; 95% CI: 0.69, 0.91) and Hispanic (csHR=0.85; 95% CI: 0.67, 1.09), but not non-Hispanic white men (csHR=1.17; 95% CI: 0.91, 1.50). Results were similar in models restricted to ages 50-64 and 40-49, except for a higher hazard of prostate cancer in Hispanic men with HIV in their 40s, while the hazard of prostate cancer was higher in men with HIV across all models for men aged 18-39. Conclusion: Reported deficits in prostate cancer incidence by HIV status may be restricted to specific groups defined by age and race-ethnicity.

Receipt of Prostate-Specific Antigen Test in Medicaid Beneficiaries With and Without HIV in 2001-2015 in 14 States.

Studies have reported lower incidence of prostate cancer in men living with HIV compared with men without HIV for reasons that remain unclear. Lower prostate cancer screening in men living with HIV could explain these findings. We describe receipt of prostate-specific antigen (PSA) test each calendar year by HIV status in Medicaid beneficiaries enrolled in 14 U.S. states, 2001-2015. A total of 15,299,991 Medicaid beneficiaries aged 18-64 with ≥7 months of continuous enrollment were included in analyses. HIV diagnosis and PSA tests were identified using non-drug claims. Incidence rate ratios comparing receipt of PSA test by HIV status adjusted for age, race/ethnicity, state of residence, calendar year, comorbid conditions, benign prostatic conditions, and receipt of testosterone-replacement therapy were estimated using Poisson regression. Models were also stratified by state, and estimates were pooled using random-effects meta-analysis to account for heterogeneity by state. Models were additionally stratified by age and race/ethnicity. There were 42,503 PSA tests over 314,273 person-years and 1,669,835 PSA tests over 22,023,530 person-years observed in beneficiaries with and without HIV, respectively. The incidence of PSA test was slightly lower in men living with HIV than men without HIV (incidence rate ratio [IRR] = 0.98; 95% confidence interval [CI]: 0.97, 0.99) when adjusting for state. In the pooled estimate, the rate was higher among men living with HIV (IRR = 1.11; 95% CI: 0.97, 1.27). Pooled estimates indicated approximately equal or higher rates of PSA test in men living with HIV compared with men without HIV across models stratified by age and race/ethnicity groups. Findings do not support the hypothesis that differences in prostate cancer screening explain differences in incidence by HIV status.

Incidence of Colon Cancer Among Medicaid Beneficiaries With or Without Human Immunodeficiency Virus Under Comparable Colorectal Cancer Screening Patterns.

Background: People with human immunodeficiency virus (HIV; PWH) in the United States have a lower incidence of colon cancer than the general population. The lower incidence may be explained by differences in receipt of screening. Thus, we sought to estimate colon cancer incidence under scenarios in which Medicaid beneficiaries, with or without HIV, followed the same screening protocols. Methods: We used data from 1.5 million Medicaid beneficiaries who were enrolled in 14 US states in 2001-2015 and aged 50-64 years; 72 747 beneficiaries had HIV. We estimated risks of colon cancer and death by age, censoring beneficiaries when they deviated from 3 screening protocols, which were based on Medicaid's coverage policy for endoscopies during the time period, with endoscopy once every 2, 4, or 10 years. We used inverse probability weights to control for baseline and time-varying confounding and informative loss to follow-up. Analyses were performed overall, by sex, and by race/ethnicity. Results: PWH had a lower incidence of colon cancer than beneficiaries without HIV. Compared with beneficiaries without HIV, the risk difference at age 65 years was -1.6% lower (95% confidence interval, -2.3% to -.7%) among PWH with the 2-year protocol and -0.8% lower (-1.3% to -.3%) with the 10-year protocol. Results were consistent across subgroup and sensitivity analyses. Conclusions: Our findings suggest that the lower risk of colon cancer that has been observed among PWH aged 50-64 years compared with those without HIV is not due to differences in receipt of lower endoscopy. Keywords: colon cancer, colorectal cancer screening, endoscopy, Medicaid, human immunodeficiency virus.

Retention in care and antiretroviral therapy adherence among Medicaid beneficiaries with HIV, 2001-2015.

Disparities in HIV care by socioeconomic status, place of residence, and race/ethnicity prevent progress toward epidemic control. No study has comprehensively characterized the HIV care cascade among people with HIV enrolled in Medicaid - an insurance source for low-income individuals in the US. We analyzed data from 246,127 people with HIV enrolled in Medicaid 2001-2015, aged 18-64, living in 14 US states. We estimated monthly prevalence of four steps of the care cascade: retained in care/adherent to ART; retained/not adherent; not retained/adherent; not retained/not adherent. Beneficiaries were retained in care if they had an outpatient care encounter every six months. Adherence was based on medication possession ratio. We estimated prevalence using a non-parametric multi-state approach, accounting for death as a competing event and for Medicaid disenrollment using inverse probability of censoring weights. Across 2001-2015, the proportion of beneficiaries with HIV who were retained/ART adherent increased, overall and in all subgroups. By 2015, approximately half of beneficiaries were retained in care, and 42% of beneficiaries were ART adherent. We saw meaningful differences by race/ethnicity and region. Our work highlights an important disparity in the HIV care cascade by insurance status during this time period.

Characterizing multimorbidity in ALIVE: Comparing single and ensemble clustering methods.

Multimorbidity, defined as having 2 or more chronic conditions, is a growing public health concern, but research in this area is complicated by the fact that multimorbidity is a highly heterogenous outcome. Individuals in a sample may have a differing number and varied combinations of conditions. Clustering methods, such as unsupervised machine learning algorithms, may allow us to tease out the unique multimorbidity phenotypes. However, many clustering methods exist and choosing which to use is challenging because we do not know the true underlying clusters. Here, we demonstrate the use of 3 individual algorithms (partition around medoids, hierarchical clustering, and probabilistic clustering) and a clustering ensemble approach (which pools different clustering approaches) to identify multimorbidity clusters in the AIDS Linked to the Intravenous Experience cohort study. We show how the clusters can be compared based on cluster quality, interpretability, and predictive ability. In practice, it is critical to compare the clustering results from multiple algorithms and to choose the approach that performs best in the domain(s) that aligns with plans to use the clusters in future analyses.

Longitudinal patterns of use of stimulants and opioids in the AIDS linked to the IntraVenous experience cohort, 2005-2019.

BACKGROUND: Overdoses involving opioids and stimulants are on the rise, yet few studies have examined longitudinal trends in use of both substances. We sought to describe use and co-use of opioids and stimulants, 2005-2019, in the AIDS Linked to the Intravenous Experience (ALIVE) cohort - a community-based cohort of people with a history of injection drug use living in or near Baltimore, MD. METHODS: We included 2083 ALIVE participants, who had at least two visits during the study period. Our outcome was based on self-reported use of opioids and stimulants in the prior 6 months. We estimated prevalence of 4 categories of use (neither stimulants nor opioids, only stimulants, only opioids, stimulants and opioids), using a non-parametric multi-state model, accounting for the competing event of death and weighting for informative loss to follow-up. All analyses were stratified by enrollment cohort, with the main analysis including participants who enrolled prior to 2015 and a sub-analysis including participants who enrolled 2015-2018. RESULTS: In the main analysis, prevalence of using stimulants and opioids decreased from 38 % in 2005 to 12 % 2013 but stabilized from 2014 onwards (13-19 %). The prevalence of using only stimulants (7-11 %) and only opioids (5-10 %) was stable across time. Participants who reported using both were more likely to report homelessness, depression, and other substance use (e.g., marijuana and heavy alcohol use) than participants in the other use categories. On average, 65 % of visits with use of both were followed by a subsequent visit with use of both; of participants transitioning out of using both, 13% transitioned to using neither. CONCLUSIONS: While use of stimulants and opioids declined in the cohort through 2013, a meaningful proportion of participants persistently used both. More research is needed to understand and develop strategies to mitigate harms associated with persistent use of both stimulants and opioids.

Lower endoscopy, early-onset, and average-onset colon cancer among Medicaid beneficiaries with and without HIV.

BACKGROUND: Studies suggest a lower colorectal cancer (CRC) risk and lower or similar CRC screening among people with HIV (PWH) compared with the general population. We evaluated the incidence of lower endoscopy and average-onset (diagnosed at ≥50) and early-onset (diagnosed at <50) colon cancer by HIV status among Medicaid beneficiares with comparable sociodemographic factors and access to care. METHODS: We obtained Medicaid Analytic eXtract (MAX) data from 2001 to 2015 for 14 states. We included 41 727 243 and 42 062 552 unique individuals with at least 7 months of continuous eligibility for the endoscopy and colon cancer analysis, respectively. HIV and colon cancer diagnoses and endoscopy procedures were identified from inpatient and other nondrug claims. We used Cox proportional hazards regression models to assess endoscopy and colon cancer incidence, controlling for age, sex, race/ethnicity, calendar year and state of enrollment, and comorbidities conditions. RESULTS: Endoscopy and colon cancer incidence increased with age in both groups. Compared with beneficiaries without HIV, PWH had an increased hazard of endoscopy; this association was strongest among those 18-39 years [hazard ratio: 1.85, 95% confidence interval (95% CI) 1.77-1.92] and attenuated with age. PWH 18-39 years also had increased hazard of early-onset colon cancer (hazard ratio: 1.66, 95% CI:1.05-2.62); this association was attenuated after comorbidity adjustment. Hazard ratios were null among all beneficiaries less than 50 years of age. PWH had a lower hazard of average-onset colon cancer compared with those without HIV (hazard ratio: 0.79, 95% CI: 0.66-0.94). CONCLUSION: PWH had a higher hazard of endoscopy, particularly at younger ages. PWH had a lower hazard of average-onset colon cancer. Early-onset colon cancer was higher among the youngest PWH but not associated with HIV overall.

Comparing Cancer Incidence in an Observational Cohort of Medicaid Beneficiaries With and Without HIV, 2001-2015.

BACKGROUND: Life expectancy among people with HIV (PWH) is increasing, making chronic conditions-including cancer-increasingly relevant. Among PWH, cancer burden has shifted from AIDS-defining cancers (ADCs) toward non-AIDS-defining cancers (NADCs). SETTING: We described incidence of cancer in a claims-based cohort of Medicaid beneficiaries. We included 43,426,043 Medicaid beneficiaries (180,058 with HIV) from 14 US states, aged 18-64, with >6 months of enrollment (with no dual enrollment in another insurance) and no evidence of a prveious cancer. METHODS: We estimated cumulative incidence of site-specific cancers, NADCs, and ADCs, by baseline HIV status, using age as the time scale and accounting for death as a competing risk. We compared cumulative incidence across HIV status to estimate risk differences. We examined cancer incidence overall and by sex, race/ethnicity, and calendar period. RESULTS: PWH had a higher incidence of ADCs, infection-related NADCs, and death. For NADCs such as breast, prostate, and colon cancer, incidence was similar or higher among PWH below age 50, but higher among those without HIV by age 65. Incidence of lung and head and neck cancer was always higher for female beneficiaries with HIV, whereas the curves crossed for male beneficiaries. We saw only small differences in incidence trends by race/ethnicity. CONCLUSION: Our findings suggest an increased risk of certain NADCs at younger ages among PWH, even when compared against other Medicaid beneficiaries, and highlight the importance of monitoring PWH for ADCs and NADCs. Future work should explore possible mechanisms explaining the differences in incidence for specific cancer types.

Time-to-completion of COVID-19 vaccination primary series varies by HIV viral load status among people who inject drugs in Baltimore, Maryland.

People who inject drugs (PWID) may have diminished access to essential preventive services like COVID-19 vaccination given structural and substance use barriers. We aimed to assess the role of HIV on COVID-19 vaccination uptake among adult PWID participating in the ALIVE cohort study in Baltimore, Maryland who were alive as of April 2021. We abstracted COVID-19 vaccination data from electronic medical records via the regional health information exchange. We used Kaplan-Meier method to estimate time from universal vaccine eligibility (April 6, 2021) to completion of the COVID-19 vaccination primary series (1 dose J&J or 2 doses mRNA) by HIV viral load status (uninfected, PWH [HIV-RNA < 400 copies/mL], PWH [HIV-RNA ≥ 400 copies/mL]) and Cox Proportional Hazards regression to adjust for potential confounders. Our sample (N = 960) was primarily black (77%) and male (65%) with 31% reporting recent injection drug use. Among 265 (27%) people living with HIV (PWH) in our sample, 84% were virally suppressed. As of February 22, 2022, 539 (56%) completed the primary series, 131 (14%) received a single dose of mRNA vaccine and 290 (30%) remained unvaccinated. Compared to PWID without HIV, virally suppressed PWH were more likely to complete the primary series (Adjusted Hazard Ratio [aHR]:1.23,95% Confidence Interval [95 %CI]:1.07,1.50), while PWH who were not virally suppressed were less likely (aHR:0.72,95 %CI:0.45,1.16), although this was not statistically significant. We conclude that among PWID, HIV infection and viral suppression is associated with quicker vaccination uptake, likely due to HIV care engagement. Targeted improvements along the HIV care continuum may bolster vaccine uptake.

Trajectories of drug treatment and illicit opioid use in the AIDS Linked to the IntraVenous Experience cohort, 2014-2019.

BACKGROUND: Medication for opioid use disorder (MOUD) is an effective intervention to combat opioid use disorder and overdose, yet there is limited understanding of engagement in treatment over time in the community, contextualized by ongoing substance use. We aimed to identify concurrent trajectories of methadone prescriptions, buprenorphine prescriptions, and illicit opioid use among older adults with a history of injection drug use. METHODS: We used data on 887 participants from the AIDS Linked to the IntraVenous Experience cohort, who were engaged in the study in 2013 and attended ≥1 visit during follow-up (2014-2019). Outcomes were self-reported MOUD prescription and illicit opioid use in the last 6 months. To identify concurrent trajectories in all 3 outcomes, we used group-based multi-trajectory modeling. We examined participant characteristics, including sociodemographics, HIV status, and other substance use, overall and by cluster. RESULTS: We identified 4 trajectory clusters: (1) no MOUD and no illicit opioid use (43%); (2) buprenorphine and some illicit opioid use (11%); (3) methadone and no illicit opioid use (28%); and (4) some methadone and illicit opioid use (18%). While prevalence of each outcome was stable across time, transitions on/off treatment or on/off illicit opioid use occurred, with the rate of transition varying by cluster. The rate of transition was highest in Cluster 3 (0.74/person-year) and lowest in Cluster 1 (0.18/person-year). We saw differences in participant characteristics by cluster, including that the buprenorphine cluster had the highest proportion of people with HIV and participants who identified as non-Hispanic Black. CONCLUSIONS: Most participants had discontinued illicit opioid use and were also not accessing MOUD. Trajectories defined by engagement with buprenorphine or methadone had distinct sociodemographic and behavioral characteristics, indicating that tailored interventions to expand access to both types of treatment are likely needed to reduce harms associated with untreated opioid use disorder.

Geographic variation in HCV treatment penetration among people who inject drugs in Baltimore, MD.

We evaluated geographic heterogeneity in hepatitis C virus (HCV) treatment penetration among people who inject drug (PWID) across Baltimore, MD since the advent of direct-acting antivirals (DAAs) using space-time clusters of HCV viraemia. Using data from a community-based cohort of PWID, the AIDS Linked to the IntraVenous Experience (ALIVE) study, we identified space-time clusters with higher-than-expected rates of HCV viraemia between 2015 and 2019 using scan statistics. We used Poisson regression to identify covariates associated with HCV viraemia and used the regression-fitted values to detect adjusted space-time clusters of HCV viraemia in Baltimore city. Overall, in the cohort, HCV viraemia fell from 77% in 2015 to 64%, 49%, 39% and 36% from 2016 to 2019. In Baltimore city, the percentage of census tracts where prevalence of HCV viraemia was ≥85% dropped from 57% to 34%, 25%, 22% and 10% from 2015 to 2019. We identified two clusters of higher-than-expected HCV viraemia in the unadjusted analysis that lasted from 2015 to 2017 in East and West Baltimore and one adjusted cluster of HCV viraemia in West Baltimore from 2015 to 2016. Neither differences in age, sex, race, HIV status, nor neighbourhood deprivation were able to explain the significant space-time clusters. However, residing in a cluster with higher-than-expected viraemia was associated with age, sex, educational attainment and higher levels of neighbourhood deprivation. Nearly 4 years after DAAs became available, HCV treatment has penetrated all PWID communities across Baltimore city. While nearly all census tracts experienced improvements, change was more gradual in areas with higher levels of poverty.

Defining representativeness of study samples in medical and population health research.

Medical and population health science researchers frequently make ambiguous statements about whether they believe their study sample or results are representative of some (implicit or explicit) target population. This article provides a comprehensive definition of representativeness, with the goal of capturing the different ways in which a study can be representative of a target population. It is proposed that a study is representative if the estimate obtained in the study sample is generalisable to the target population (owing to representative sampling, estimation of stratum specific effects, or quantitative methods to generalise or transport estimates) or the interpretation of the results is generalisable to the target population (based on fundamental scientific premises and substantive background knowledge). This definition is explored in the context of four covid-19 studies, ranging from laboratory science to descriptive epidemiology. All statements regarding representativeness should make clear the way in which the study results generalise, the target population the results are being generalised to, and the assumptions that must hold for that generalisation to be scientifically or statistically justifiable.

Temporal association of pre-pandemic perceived social support with psychological resilience and mental well-being during the COVID-19 pandemic among people with a history of injection drug use.

BACKGROUND: There are limited data on whether modifiable social factors foster psychological resilience and mental well-being among people who use drugs following Big Events. We examined the temporal association of pre-pandemic perceived social support with psychological resilience and negative mental health symptoms during the COVID-19 pandemic among people with a history of injection drug use. METHODS: Between June and September 2020, we conducted a telephone survey among 545 participants in the AIDS Linked to the IntraVenous Experience (ALIVE) study: a community-based cohort of adults with a history of injection drug use. Leveraging data from study visits in 2018-early 2020, associations of pre-pandemic perceived social support with psychological resilience scores (range=1-5) and the probability of negative mental health symptoms during the pandemic were assessed using multivariable linear and modified Poisson regression models, respectively. RESULTS: Participants' median age was 58 years, 38.2% were female, 83.3% identified as Black, and 30.3% were living with HIV. During the pandemic, 14.5% had low (<3) resilience scores, 36.1% experienced anxiety, and 35.8% reported increased loneliness. Compared to participants in the lowest tertile of pre-pandemic social support, participants in the highest tertile had higher mean resilience scores (ß = 0.27 [95% CI = 0.12, 0.43]), a lower probability of anxiety (prevalence ratio [PR] = 0.71 [95% CI = 0.52, 0.96]), and a lower probability of increased loneliness (PR = 0.62 [95% CI = 0.45, 0.84]). CONCLUSIONS: Pre-pandemic perceived social support was associated with greater psychological resilience and generally better mental well-being during the pandemic. Interventions that improve social support may foster psychological resilience and protect the mental well-being of people who use drugs, especially during periods of social disruption.

Estimation of the Time-Varying Incremental Effect of Low-dose Aspirin on Incidence of Pregnancy.

BACKGROUND: In many research settings, the intervention implied by the average causal effect of a time-varying exposure is impractical or unrealistic, and we might instead prefer a more realistic target estimand. Instead of requiring all individuals to be always exposed versus unexposed, incremental effects quantify the impact of merely shifting each individual's probability of being exposed. METHODS: We demonstrate the estimation of incremental effects in the time-varying setting, using data from the Effects of Aspirin in Gestation and Reproduction trial, which assessed the effect of preconception low-dose aspirin on pregnancy outcomes. Compliance to aspirin or placebo was summarized weekly and was affected by time-varying confounders such as bleeding or nausea. We sought to estimate what the incidence of pregnancy by 26 weeks postrandomization would have been if we shifted each participant's probability of taking aspirin or placebo each week by odds ratios (OR) between 0.30 and 3.00. RESULTS: Under no intervention (OR = 1), the incidence of pregnancy was 77% (95% CI: 74%, 80%). Decreasing women's probability of complying with aspirin had little estimated effect on pregnancy incidence. When we increased women's probability of taking aspirin, estimated incidence of pregnancy increased, from 83% (95% confidence interval [CI] = 79%, 87%) for OR = 2 to 89% (95% CI = 84%, 93%) for OR=3. We observed similar results when we shifted women's probability of complying with a placebo. CONCLUSIONS: These results estimated that realistic interventions to increase women's probability of taking aspirin would have yielded little to no impact on the incidence of pregnancy, relative to similar interventions on placebo.

A Simulation Study Comparing the Performance of Time-Varying Inverse Probability Weighting and G-Computation in Survival Analysis.

Inverse probability weighting (IPW) and g-computation are commonly used in time-varying analyses. To inform decisions on which to use, we compared these methods using a plasmode simulation based on data from the Effects of Aspirin in Gestation and Reproduction (EAGeR) Trial (June 15, 2007-July 15, 2011). In our main analysis, we simulated a cohort study of 1,226 individuals followed for up to 10 weeks. The exposure was weekly exercise, and the outcome was time to pregnancy. We controlled for 6 confounding factors: 4 baseline confounders (race, ever smoking, age, and body mass index) and 2 time-varying confounders (compliance with assigned treatment and nausea). We sought to estimate the average causal risk difference by 10 weeks, using IPW and g-computation implemented using a Monte Carlo estimator and iterated conditional expectations (ICE). Across 500 simulations, we compared the bias, empirical standard error (ESE), average standard error, standard error ratio, and 95% confidence interval coverage of each approach. IPW (bias = 0.02; ESE = 0.04; coverage = 92.6%) and Monte Carlo g-computation (bias = -0.01; ESE = 0.03; coverage = 94.2%) performed similarly. ICE g-computation was the least biased but least precise estimator (bias = 0.01; ESE = 0.06; coverage = 93.4%). When choosing an estimator, one should consider factors like the research question, the prevalences of the exposure and outcome, and the number of time points being analyzed.

Mortality by cause of death during year 1 of the COVID-19 pandemic in a cohort of older adults from Baltimore Maryland who have injected drugs.

BACKGROUND: In 2020, the first year of the COVID-19 pandemic, overdose deaths increased. However, no studies have characterized changes in mortality during the pandemic in a well-characterized cohort of people who use drugs in active follow-up at the time of pandemic onset. DESIGN: We compared all-cause and cause-specific mortality in the first year of the pandemic (Mar-Dec 2020) to the five years preceding (Jan 2015-Feb 2020), among participants in the AIDS Linked to the IntraVenous Experience (ALIVE) study: a community-recruited cohort of adults from Baltimore who have injected drugs. 3510 participants contributed 17,498 person-years [py] of follow-up time. Cause and dates of death were ascertained through the National Death Index. Comparisons were made for the full cohort and within subgroups with potentially differential levels of vulnerability. RESULTS: All-cause mortality in 2020 was 39.6 per 1000 py, as compared to 37.2 per 1000 py pre- pandemic (Adjusted Incidence Rate Ratio = 1.09, 95%: confidence interval: 0.84-1.41). Increases were mostly attributable to chronic disease deaths; injury/poisoning deaths did not increase. No pre-post differences were statistically significant. CONCLUSION: In this exploratory analysis of an older cohort of urban-dwelling adults who have injected drugs, mortality changes during the first year of the pandemic differed from national trends and varied across potentially vulnerable subgroups. More research is needed to understand determinants of increased risk of mortality during the pandemic among subgroups of people who use drugs.

Estimation of the Average Causal Effect in Longitudinal Data With Time-Varying Exposures: The Challenge of Nonpositivity and the Impact of Model Flexibility.

There are important challenges to the estimation and identification of average causal effects in longitudinal data with time-varying exposures. Here, we discuss the difficulty in meeting the positivity condition. Our motivating example is the per-protocol analysis of the Effects of Aspirin in Gestation and Reproduction (EAGeR) Trial. We estimated the average causal effect comparing the incidence of pregnancy by 26 weeks that would have occurred if all women had been assigned to aspirin and complied versus the incidence if all women had been assigned to placebo and complied. Using flexible targeted minimum loss-based estimation, we estimated a risk difference of 1.27% (95% CI: -9.83, 12.38). Using a less flexible inverse probability weighting approach, the risk difference was 5.77% (95% CI: -1.13, 13.05). However, the cumulative probability of compliance conditional on covariates approached 0 as follow-up accrued, indicating a practical violation of the positivity assumption, which limited our ability to make causal interpretations. The effects of nonpositivity were more apparent when using a more flexible estimator, as indicated by the greater imprecision. When faced with nonpositivity, one can use a flexible approach and be transparent about the uncertainty, use a parametric approach and smooth over gaps in the data, or target a different estimand that will be less vulnerable to positivity violations.

Impact of Hepatitis C Treatment Uptake on Cirrhosis and Mortality in Persons Who Inject Drugs : A Longitudinal, Community-Based Cohort Study.

BACKGROUND: Hepatitis C virus (HCV) infection can be cured, and the United States has joined the World Health Organization in calling for HCV elimination by 2030. However, historically low uptake of HCV treatment among people who inject drugs (PWID) threatens HCV elimination and exacerbates social and racial health disparities. OBJECTIVE: To assess whether all-oral HCV treatments were accessed by PWID and reduced liver disease burden and mortality. DESIGN: Community-based, longitudinal cohort study of persons with a history of injection drug use. SETTING: Baltimore, Maryland. PARTICIPANTS: 1323 participants enrolled in the ALIVE (AIDS Linked to the IntraVenous Experience) study from 2006 to 2019 and chronically infected with HCV. MEASUREMENTS: Liver stiffness measures (LSMs) by transient elastography, HCV RNA, and mortality from the National Death Index. RESULTS: Among 1323 persons with evidence of chronic HCV infection at baseline, the median age was 49 years. Most were Black (82%), male (71%), and HIV-negative (66%). The proportion in whom HCV RNA was detected decreased from 100% (by definition) in 2006 to 48% in 2019. Across 10 350 valid LSMs, cirrhosis was detected in 15% of participants in 2006, 19% in 2015, and 8% in 2019. Undetectable HCV RNA was significantly associated with reduced odds of cirrhosis (adjusted odds ratio, 0.28 [95% CI, 0.17 to 0.45]) and reduced all-cause mortality risk (adjusted hazard ratio, 0.54 [CI, 0.38 to 0.77]). LIMITATION: Noninvasive markers of liver fibrosis have not been validated in persons with sustained virologic response. CONCLUSION: Many community-based PWID in Baltimore are receiving HCV treatment, which is associated with sharp decreases in liver disease and mortality. Additional efforts will be needed to reduce residual barriers to treatment and to eliminate HCV as a public health threat for PWID. PRIMARY FUNDING SOURCE: National Institutes of Health.

Illustrating How to Simulate Data From Directed Acyclic Graphs to Understand Epidemiologic Concepts.

Simulation methods are a powerful set of tools that can allow researchers to better characterize phenomena from the real world. As such, the ability to simulate data represents a critical set of skills that epidemiologists should use to better understand epidemiologic concepts and ensure that they have the tools to continue to self-teach even when their formal instruction ends. Simulation methods are not always taught in epidemiology methods courses, whereas causal directed acyclic graphs (DAGs) often are. Therefore, this paper details an approach to building simulations from DAGs and provides examples and code for learning to perform simulations. We recommend using very simple DAGs to learn the procedures and code necessary to set up a simulation that builds on key concepts frequently of interest to epidemiologists (e.g., mediation, confounding bias, M bias). We believe that following this approach will allow epidemiologists to gain confidence with a critical skill set that may in turn have a positive impact on how they conduct future epidemiologic studies.