Causal mediation analysis with mediator values below an assay limit.

Publisher: Wiley Country of Publication: England NLM ID: 8215016 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0258 (Electronic) Linking ISSN: 02776715 NLM ISO Abbreviation: Stat Med Subsets: MEDLINE

Original Publication: Chichester ; New York : Wiley, c1982-

Mediation Analysis* ; HIV Infections*/drug therapy ; Causality* ; Computer Simulation* ; Biomarkers*/blood; Humans ; Randomized Controlled Trials as Topic ; Likelihood Functions ; Models, Statistical ; Anti-HIV Agents/therapeutic use

Causal indirect and direct effects provide an interpretable method for decomposing the total effect of an exposure on an outcome into the indirect effect through a mediator and the direct effect through all other pathways. A natural choice for a mediator in a randomized clinical trial is the treatment's targeted biomarker. However, when the mediator is a biomarker, values can be subject to an assay lower limit. The mediator is affected by the treatment and is a putative cause of the outcome, so the assay lower limit presents a compounded problem in mediation analysis. We propose two approaches to estimate indirect and direct effects with a mediator subject to an assay limit: (1) extrapolation and (2) numerical optimization and integration of the observed likelihood. Since these estimation methods solely rely on the so-called Mediation Formula, they apply to most approaches to causal mediation analysis: natural, separable, and organic indirect, and direct effects. A simulation study compares the two estimation approaches to imputing with half the assay limit. Using HIV interruption study data from the AIDS Clinical Trials Group described in Li et al 2016, AIDS; Lok and Bosch 2021, Epidemiology, we illustrate our methods by estimating the organic/pure indirect effect of a hypothetical HIV curative treatment on viral suppression mediated by two HIV persistence measures: cell-associated HIV-RNA and single-copy plasma HIV-RNA.
(© 2024 John Wiley & Sons Ltd.)

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UM1 AI068634 United States AI NIAID NIH HHS; UM1 AI068636 United States AI NIAID NIH HHS; UM1 AI068634 United States AI NIAID NIH HHS; UM1 AI068636 United States AI NIAID NIH HHS; DMS 1854934 Center for Hierarchical Manufacturing, National Science Foundation

Keywords: HIV/AIDS; assay lower limit; causal inference; causal mediation analysis; indirect and direct effects

Date Created: 20240401 Date Completed: 20240520 Latest Revision: 20240520

20240520

10.1002/sim.10065

38556761