Aplicación de modelos estructurales marginales para estimar los efectos de la terapia antirretroviral en 5 cohortes de seroconvertores al virus de la inmunodeficiencia humana

Abstract

Objectives Standard methods to evaluate population effectiveness of treatments in observational studies have important limitations to appropriately adjust for time-dependent confounders. In this paper, we describe a recently developed methodological approach, marginal structural models (MSM), and use it to estimate the effectiveness of highly active antiretroviral therapy (HAART) on AIDS or death incidence. Subjects and methods We analyzed all subjects followed after 1997 as part of the GEMES project (comprised by several cohorts of HIV seroconverters in Spain) and who had not used HAART before the start of follow-up. To estimate the effect of HAART on AIDS or death incidence, we estimated the parameters of a marginal structural Cox model by fitting an inverse probability weighted logistic regression model. The estimation of the weights was based on CD4 count, time since seroconversion, sex, age, transmission category and previous treatment. Results 917 eligible subjects were followed for an average of 3.4 years and we observed 139 events. 42.1% of the participants received HAART during the study. The estimated rate ratio was 1.01 (95% confidence interval [CI], 0.68- 1.49) using a Cox model without covariates and 0.90 (95% CI, 0.61-1.32) using a Cox model with time-dependent covariates. The causal rate ratio estimated for MSM was 0.74, (95% CI, 0.49-1.12). Conclusions The beneficial effect of HAART estimated by the MSM, but largely missed by conventional methods, is consistent with the findings of previous randomized studies. The MSM appropriately adjusted for the time-dependent covariate CD4 count, which is both a time-varying confounder and is affected by prior treatment.