Quantifying an Adherence Path-Specific Effect of Antiretroviral Therapy in the Nigeria PEPFAR Program
By Caleb H. Miles, Ilya Shpitser, Phyllis Kanki, Seema Meloni, E. T. Tchetgen Tchetgen. 2014
29 citations recorded by the source corpus.
ABSTRACT Since the early 2000s, evidence has accumulated for a significant differential effect of first-line antiretroviral therapy (ART) regimens on human immunodeficiency virus (HIV) viral load suppression. This finding was replicated in our data from the Harvard President’s Emergency Plan for AIDS Relief (PEPFAR) program in Nigeria. Investigators were interested in finding the source of these differences, that is, understanding the mechanisms through which one regimen outperforms another, particularly via adherence. This question can be naturally formulated via mediation analysis with adherence playing the role of a mediator. Existing mediation analysis results, however, have relied on an assumption of no exposure-induced confounding of the intermediate variable, and generally require an assumption of no unmeasured confounding for nonparametric identification. Both assumptions are violated by the presence of drug toxicity. In this article, we relax these assumptions and show that certain path-specific effects remain identified under weaker conditions. We focus on the path-specific effect solely mediated by adherence and not by toxicity and propose an estimator for this effect. We illustrate with simulations and present results from a study applying the methodology to the Harvard PEPFAR data. Supplementary materials for this article are available online.
Subfields: Infectious Diseases, Statistics and Probability
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In Statistics and Probability
- Razieh Nabi
- Ilya Shpitser
- Judea Pearl
- Silvia Chiappa
- Xintao Wu
- Lu Zhang
- Yongkai Wu
- E. T. Tchetgen Tchetgen
Citations in the corpus
- Fair Inference on Outcomes (2017, methodology): “PSEs such as (2) has been used in the context of observational studies of HIV patients for assessing the role of adherence in determining viral failure outcomes (Miles et al. 2017).”