Our study focus was on distal and more impactful outcomes of antiretroviral therapy, specifically HIV viral suppression. Self-reported use of amphetamines, opioids as individual substances and multiple substance use predicted having a detectable pVL. However, surprisingly hazardous alcohol use was not predictive.

Our study found that hazardous alcohol use was associated with worse ART adherence but not with having detectable HIV pVL as others have noted (Nolan et al., 2017). A large meta-analysis also found a significant and reliable association between alcohol use and antiretroviral medication nonadherence; however, it did not address the effects of alcohol on viral suppression (Hendershot et al., 2009). Important differences in study design, secular trends in the type of antiretroviral therapy, and instruments used to measure alcohol use could account for differences in our findings from other studies that observed hazardous alcohol use to be associated with detectable viral loads. Some were based on cross-sectional assessments (Conen et al., 2009). The ones with the longitudinal design were conducted in the late 1990s to early 2000s when antiretroviral therapy was poorly tolerated, requiring a significant pill burden, and many PWH with hazardous alcohol use avoided taking them while drinking (Chander et al., 2006, Conigliaro et al., 2003). Our study, conducted in a more contemporary antiretroviral era, suggests that, despite imperfect adherence, PWH with hazardous alcohol use can take enough medications to keep their pVL undetectable. Nonetheless, we did not assess patterns of alcohol intake which have been shown to impact pVL, with those with binge drinking having more likelihood of having detectable pVL (Conigliaro et al., 2003). Like our findings, a prospective randomized controlled trial failed to show the same association between hazardous alcohol use and detectable pVL (Samet et al., 2005). Noteworthy, in many of these cohorts, either exposure was defined as any alcohol use or instruments other than AUDIT-C were used (Palepu et al., 2003). We believe that our inability to detect an effect of hazardous alcohol use on pVL was not attributable to the specific AUDIT-C cutoff score used. We assessed, using ROC analysis, the full numeric range of AUDIT-C scores and found that the measure did not discriminate between those with and without HIV viral suppression.

This study found that up to 40% of the effects of having a detectable pVL appeared to be mediated by our measure of medication adherence. Thus, mediation analyses restricted to substances that were associated with having a detectable pVL (amphetamines, opioids, and multiple substance use) did not support our a priori hypothesis that their effects on viral suppression would be largely mediated through antiretroviral adherence. There are several potential explanations for this observation. This could represent a true finding, pointing to the effect of these substances not mediated through antiretroviral adherence. Another potential explanation is the occurrence of pharmacokinetic or pharmacodynamic drug-drug interactions that adversely influence antiretroviral effects independent of adherence behavior (Desai et al., 2020). Other possible explanations are related to measurement issues: the specific metric chosen for substance use (any past 3-month use on NIDA ASSIST), the timing of the substance use recall period with respect to subsequent viral load measurement (median 24 days), and use of an insensitive measure of medication adherence (although we selected the most discriminating of the candidate measures available (Table 2). Residual confounding and collider effects resulting in selection bias owing to missing values must also be considered. These issues merit further exploration and replication.

Among the few published reports of mediation analyses examining the effects of alcohol or substance use on viral non-suppression, we identified 3 concerning effects of alcohol or methamphetamine use. All three reported that the predominant effects were direct and not mediated through selected measures of adherence. Kahler et al. used a longitudinal cohort design (n = 533 patients) to examine the extent to which the effect of 30-day heavy drinking on viral non-suppression was mediated by antiretroviral adherence (measured by the number of missed doses over a 3-day period) (Kahler et al., 2017). These investigators found a significant natural indirect effect (NIE) on the risk ratio scale (1.03 [95% CI: 1.00–1.05]), corresponding to a 20 percent mediation effect. Cook et al. reported results of a mediation analysis using baseline data (n = 619 patients) for which the adherence measure was based on a 30-day number of days with missing doses and drinking measures included specifications for low, binge, and heavy drinking according to AUDIT-C criteria (Cook et al., 2017). For heavy drinking, the predominant effect on viral non-suppression was direct, with only 9.1% mediated through adherence. We were able to identify only one mediation analysis for the effects of methamphetamine use and antiretroviral adherence on HIV viral non-suppression (Feelemyer et al., 2020). Employing a cohort design (n = 645 patients), the investigators reported that the effect of methamphetamine use was predominantly direct. Unfortunately, the indirect effect was not reported. So, our findings of the predominant direct effects of amphetamine, opioid, and polysubstance use on viral non-suppression are consistent with previous reports.

Limitations of our findings are that they represent a single-center experience, a cross-sectional rather than a longitudinal design, and are based on a data set with missing values that limited complete case analysis for multivariable components of the analysis. The self-report nature of substance use and adherence might have potentially impacted the observed associations. Often, self-report substance use underestimates the use (Khalili et al., 2021), and self-reported adherence tends to overestimate adherence (Stirratt et al., 2015). Also, participant characteristics linked to social determinants of health, such as being unsheltered, mental health, and poverty, were not included in the analysis; hence, their contribution to observed effects could not be explored in this study. Our analysis mainly included white individuals and MSM, and our results might not be generalizable to HIV cohorts with more diverse characteristics. Nonetheless, we conclude that the mediation analysis findings are provocative and merit examination in expanded longitudinal cohorts with longitudinal mediation modeling (O'Laughlin, Martin, & Ferrer, 2018).