RESUMO
Reducing racial/ethnic disparities in human immunodeficiency virus (HIV) disease is a high priority. Reductions in HIV racial/ethnic disparities can potentially be achieved by intervening on important intermediate factors. The potential population impact of intervening on intermediates can be evaluated using observational data when certain conditions are met. However, using standard stratification-based approaches commonly employed in the observational HIV literature to estimate the potential population impact in this setting may yield results that do not accurately estimate quantities of interest. Here we describe a useful conceptual and methodological framework for using observational data to appropriately evaluate the impact on HIV racial/ethnic disparities of interventions. This framework reframes relevant scientific questions in terms of a controlled direct effect and estimates a corresponding proportion eliminated. We review methods and conditions sufficient for accurate estimation within the proposed framework. We use the framework to analyze data on 2,329 participants in the CFAR [Centers for AIDS Research] Network of Integrated Clinical Systems (2008-2014) to evaluate the potential impact of universal prescription of and ≥95% adherence to antiretroviral therapy on racial disparities in HIV virological suppression. We encourage the use of the described framework to appropriately evaluate the potential impact of targeted interventions in addressing HIV racial/ethnic disparities using observational data.
Assuntos
Fármacos Anti-HIV/uso terapêutico , Etnicidade/estatística & dados numéricos , Infecções por HIV/epidemiologia , Disparidades em Assistência à Saúde/etnologia , Grupos Raciais/estatística & dados numéricos , Adulto , Feminino , HIV , Infecções por HIV/tratamento farmacológico , Infecções por HIV/etnologia , Disparidades nos Níveis de Saúde , Humanos , Masculino , Estudos Observacionais como Assunto , Estados Unidos/epidemiologiaRESUMO
BACKGROUND: Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and nondifferential measurement error in a marginal structural model. METHODS: We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3,686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. RESULTS: In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality (hazard ratio [HR]: 1.2 [95% confidence interval [CI] = 0.6, 2.3]). The HR for current smoking and therapy [0.4 (95% CI = 0.2, 0.7)] was similar to the HR for no smoking and therapy (0.4; 95% CI = 0.2, 0.6). CONCLUSIONS: Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies.
Assuntos
Fármacos Anti-HIV/uso terapêutico , Viés , Interpretação Estatística de Dados , Infecções por HIV/tratamento farmacológico , Modelos Estatísticos , Fumar/efeitos adversos , Modificador do Efeito Epidemiológico , Feminino , Seguimentos , Infecções por HIV/mortalidade , Humanos , Masculino , Método de Monte Carlo , Estudos Observacionais como Assunto , Estados UnidosRESUMO
BACKGROUND: Contemporary data on patterns of antiretroviral therapy (ART) use in the United States are needed to inform efforts to improve the HIV care cascade. METHODS: We conducted a cross-sectional study of patients in the Centers for AIDS Research Network of Integrated Clinical Systems cohort who were in HIV care in 2010 to assess ART use and outcomes, stratified by nadir CD4 count (≤350, 351-500, or >500 cells/mm), demographics, psychiatric diagnoses, substance use, and engagement in continuous care (≥2 visits ≥3 months apart in 2010). RESULTS: Of 8633 patients at 7 sites who had ≥1 medical visit and ≥1 viral load in 2010, 94% had ever initiated ART, 89% were on ART, and 70% had an undetectable viral load at the end of 2010. Fifty percent of ART-naive patients had nadir CD4 counts >500 cells per cubic millimeter, but this group comprised just 3% of the total population. Among patients who were ART naive at the time of cohort entry (N = 4637), both ART initiation and viral suppression were strongly associated with nadir CD4 count. Comparing 2009 and 2010, the percentages of patients with viral suppression among those with nadir CD4 counts 351-500 and >500 cells per cubic millimeter were 44% vs. 57% and 25% vs. 33%, respectively. Engagement in care was the only factor consistently associated with ART use and viral suppression across nadir CD4 count strata. CONCLUSIONS: Our findings suggest that ART use and viral suppression among persons in HIV care may be more common than estimated in some previous studies and increased from 2009 to 2010.
Assuntos
Fármacos Anti-HIV/uso terapêutico , Infecções por HIV/tratamento farmacológico , Infecções por HIV/virologia , HIV/fisiologia , Adolescente , Adulto , Contagem de Linfócito CD4 , Estudos Transversais , Esquema de Medicação , Feminino , HIV/efeitos dos fármacos , Infecções por HIV/imunologia , Humanos , Masculino , Pessoa de Meia-Idade , RNA Viral/sangue , Estados Unidos , Carga Viral , Adulto JovemRESUMO
CONTEXT: Plasma human immunodeficiency virus (HIV) RNA level predicts HIV disease progression, but the extent to which it explains the variability in rate of CD4 cell depletion is poorly characterized. OBJECTIVE: To estimate the proportion of variability in rate of CD4 cell loss predicted by presenting plasma HIV RNA levels in untreated HIV-infected persons. DESIGN: Repeated-measures analyses of 2 multicenter cohorts, comprising observations beginning on May 12, 1984, and ending on August 26, 2004. Analyses were conducted between August 2004 and March 2006. SETTING: Two cohorts of HIV-infected persons: patients followed up at 4 US teaching medical institutions or participating in either the Research in Access to Care for the Homeless Cohort (REACH) or the San Francisco Men's Health Study (SFMHS) cohorts and participants in the Multicenter AIDS Cohort Study (MACS) cohort. PARTICIPANTS: Antiretroviral treatment-naive, chronically HIV-infected persons (n = 1289 and n = 1512 for each of the 2 cohorts) untreated during the observation period (> or =6 months) and with at least 1 HIV RNA level and 2 CD4 cell counts available. Approximately 35% were nonwhite, and 35% had risk factors other than male-to-male sexual contact. MAIN OUTCOME MEASURES: The extent to which presenting plasma HIV RNA level could explain the rate of model-derived yearly CD4 cell loss, as estimated by the coefficient of determination (R2). RESULTS: In both cohorts, higher presenting HIV RNA levels were associated with greater subsequent CD4 cell decline. In the study cohort, median model-estimated CD4 cell decrease among participants with HIV RNA levels of 500 or less, 501 to 2000, 2001 to 10,000, 10,001 to 40,000, and more than 40,000 copies/mL were 20, 39, 48, 56, and 78 cells/microL, respectively. Despite this trend across broad categories of HIV RNA levels, only a small proportion of CD4 cell loss variability (4%-6%) could be explained by presenting plasma HIV RNA level. Analyses using multiple HIV RNA measurements or restricting to participants with high HIV RNA levels improved this correlation minimally (R2, 0.09), and measurement error was estimated to attenuate these associations only marginally (deattenuated R2 in the 2 cohorts, 0.05 and 0.08, respectively). CONCLUSIONS: Presenting HIV RNA level predicts the rate of CD4 cell decline only minimally in untreated persons. Other factors, as yet undefined, likely drive CD4 cell losses in HIV infection. These findings have implications for treatment decisions in HIV infection and for understanding the pathogenesis of progressive immune deficiency.