Evaluation of human immunodeficiency virus biomarkers: inferences from interval and clinical cohort studies

Among individuals infected with the human immunodeficiency virus (HIV), biomarkers that predict mortality are also used to determine the time when antiretroviral therapy is initiated. No studies have evaluated the impact of the frequency of marker measurements for either their predictive value of mortality or how they may influence inference of the effect of therapy initiation in analyses from observational data.

We identified 244 persons who were contemporaneously enrolled in both the AIDS Link to the IntraVenous Experience (an interval cohort) and the Johns Hopkins HIV Clinical Cohort between 1995 and 2004. Data from each study were used separately in 2 ways. We applied time-dependent proportional hazards models to examine the predictive associations between markers and mortality, and marginal structural models to examine the causal inference of therapy on mortality. Biomarkers were used to derive the inverse probability weights.

The timing frequencies of marker measurements in the interval cohort (CD4 interquartile range = 175-194 days) were less heterogeneous than in the clinical cohort (interquartile range = 38-121 days). Despite this, the results were concordant for CD4 (R = 0.537 [95% confidence interval = 0.345-0.707] and (R = 0.488 [0.297-0.666], respectively). Similar concordance was found for the HIV-1 RNA and hemoglobin analyses. When evaluating the causal effect of highly active antiretroviral therapy (HAART), the relative hazards were 0.34 for the interval cohort study (95% CI = 0.15-0.77) and 0.27 for the clinical cohort study (0.11-0.66).

Utilizing a unique co-enrollment of patients in 2 different types of cohort studies, we find empirical evidence that inferences drawn from these different structures are similar.