Causal indirect effect of an HIV curative treatment: mediators subject to an assay limit and measurement error

Music City Center 

Causal mediation analysis decomposes the total effect of a treatment on an outcome into the indirect effect, operating through the mediator, and the direct effect, operating through other pathways. One can estimate the pure or organic indirect effect by combining a hypothesized treatment effect on the mediator with outcome data without treatment. This methodology holds significant promise in selecting prospective treatments based on their indirect effect for further evaluation in randomized clinical trials.
We apply this methodology to assess which of two measures of HIV persistence is a more promising target for future HIV curative treatments. We combine a hypothesized treatment effect on two mediators, and outcome data without treatment, to compare the indirect effect of treatments targeting these mediators. Some HIV persistence measurements fall below the assay limit, leading to left-censored mediators. To address this issue, we assume that the outcome model extends to mediators below the assay limit and use maximum likelihood estimation. To address measurement error in the mediators, we adjust our estimates. Using data from completed ACTG studies, we estimate the pure or organic indirect effect of potential curative HIV treatments on viral suppression through weeks 4 and 8 after HIV medication interruption, mediated by two HIV persistence measures.

causal mediation analysis

causal inference

assay lower limit

measurement error

HIV/AIDS

indirect effects 

Biopharmaceutical Section