Journal
JOURNAL OF CLINICAL EPIDEMIOLOGY
Volume 62, Issue 6, Pages 632-641Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jclinepi.2008.07.015
Keywords
Bayesian statistics; Epidemiologic methods; Hierarchical regression; Highly active antiretroviral therapy; HIV; Metabolic syndrome
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Objective: Hierarchical modeling has been Proposed as a Solution to the multiple exposure problem. We estimate associations between mtabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. Study Design and Setting: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes, We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. Results: One thousand (WO hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate tor exposure to atazanavir increased front hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). Conclusion: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model. (C) 2008 Elsevier Inc. All rights reserved.
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