Please identify a quantitative research article evaluating mediation in your field and provide the citation.
Kahler, Christopher W., Tao Liu, Patricia A. Cioe, Vaughn Bryant, Megan M. Pinkston, Erna M. Kojic, Nur Onen, et al. 2016. “Direct and Indirect Effects of Heavy Alcohol Use on Clinical Outcomes in a Longitudinal Study of HIV Patients on ART.” AIDS and Behavior, July. doi:10.1007/s10461-016-1474-y.
What is the primary discipline of the authors?
Christopher W. Kahler – Center for Alcohol and Addiction Studies, Brown University School of Public Health; PhD in clinical psychology.
Tao Liu – Center for Statistical Sciences, Brown University School of Public Health; PhD in biostatistics.
Patirica A. Cioe – Center for Alcohol and Addiction Studies, Brown University School of Public Health; PhD in nursing.
Vaughn Bryant – Department of Clinical and Health Psychology, University of Florida; graduate student.
Megan M. Pinkston – Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University; PhD in clinical health psychology.
Erna M. Kojic – Department of Infectious Disease, Brown University; MD (infectious disease).
Nur Onen – Washington University School of Medicine; MD (infectious disease).
Jason V. Baker – Division of Infectious Diseases, University of Minnesota, Minneapolis; MD (infectious disease).
John Hammer – Denver Infectious Disease Consultants; MD (infectious disease).
John T. Brooks – Division of HIV/AIDS Prevention, CDC; MD (infectious disease).
Pragna Patel – Division of Global Health Protection, CDC; MD (infectious disease), MPH, DTM&H, AAHIVS.
What is the exposure of interest?
Past 30-day frequency of heavy drinking (consuming 5+ drinks on one occasion)
What is the outcome of interest?
HIV-related (detectable viral load and CD4+ T cell count) and non-HIV-related (hemoglobin and biomarkers of kidney function and liver fibrosis) clinical outcomes.
What is the hypothesized mediator of interest and how is it measured?
The mediator of interest is ART adherence. It is measured by self-report (participants were asked the number of missed doses in the past 3 days), and then dichotomized to either no missed doses or at least one missed dose since missing more than one dose was rare.
Describe the modeling approach and briefly report the estimated total, direct, and indirect effects (if these are reported).
The authors used structural equation models to model the exposure-mediator-outcome relationship, including confounding variables. They adjusted for time-dependent and time-independent confounders and clinical outcomes at the last visit in all models. Heavy drinking and ART adherence were allowed to have an interacting effect on the outcomes. Outcomes were modeled with either a log-linear model (for the dichotomized viral load outcome), or a linear model (for the continuous outcomes).
Just listing results for the HIV-related clinical outcomes (with 95% CIs) for simplicity:
Detectable viral load total effect 1.16 (1.00, 1.31), direct effect 1.13 (0.99, 1.27), indirect effect 1.03 (1.00, 1.05).
CD4+ T cell count total effect -11.33 (-17.80, -4.85), direct effect -10.61 (-17.10, -4.12), indirect effect -0.72 (-1.28, -0.15).
If the direct effect is reported, would you describe this as a natural direct effect, a controlled direct effect, or something else?
Natural direct effect: it is the effect of heavy drinking on health outcomes if ART adherence was kept at the “natural” level in the absence of heavy drinking (i.e., what adherence would be expected to be in an individual had no heavy drinking).
Do you think there is potential measurement error in the mediator and how would that affect the results?
Yes, I think there are two main potential reasons for measurement error in the mediator: people may not accurately report their ART adherence due to social desirability bias – there is clearly a “right” answer to the question about whether someone has skipped medication, and people may not respond honestly due to embarrassment; and/or they may not accurately recall whether they skipped medication. Since researchers were only asking about the past 3 days, this seems less likely but still possible. With social desirability bias, people would tend to over-report adherence, which would tend to increase the indirect effect. With inaccurate recall, it depends on whether people were more likely to over-report adherence (increase the indirect effect), more likely to under-report adherence (increase the direct effect), or if people were neither more likely to report one or the other (which I think would weaken the association between mediator and the outcome, and so would also increase the direct effect?).
Do you think there are unmeasured confounders of the mediator-outcome association and how would that affect the results of the mediation analysis?
I think there are at least a few unmeasured potential confounders – social support, health insurance status, and other comorbidities (HBV infection, HCV infection, and depression were included which are arguably the most important, but other comorbidities could also confound the relationship).
Do you have any critiques of the paper?
The authors did a good job of fulfilling the first three assumptions for controlling confounding in mediation analysis, but the fourth assumption is that there should be no mediator-outcome confounder that is itself affected by the exposure. I think it is certainly possible that heavy drinking could affect the time-dependent confounders employment, drug use, and depression. Given the complexity of the system, it also would have been beneficial to perform a sensitivity analysis for unmeasured confounding. Finally, it would have been helpful if the authors had been more specific/provided more description about how they conducted the mediation analysis itself.