Antiretroviral hair levels, self-reported adherence, and virologic failure in second-line regimen patients in resource-limited settings

Objective: To evaluate associations between hair antiretroviral hair concentrations as an objective, cumulative adherence metric, with self-reported adherence and virologic outcomes.

Design: Analysis of cohort A of the ACTG-A5288 study. These patients in resource-limited settings were failing second-line protease inhibitor-based antiretroviral therapy (ART) but were susceptible to at least one nucleoside reverse transcriptase inhibitor (NRTI) and their protease inhibitor, and continued taking their protease inhibitor-based regimen.

Methods: Antiretroviral hair concentrations in participants taking two NRTIs with boosted atazanavir (n = 69) or lopinavir (n = 112) were analyzed at weeks 12, 24, 36 and 48 using liquid-chromatography--tandem-mass-spectrometry assays. Participants' self-reported percentage of doses taken in the previous month; virologic failure was confirmed HIV-1 RNA at least 1000 copies/ml at week 24 or 48.

Results: From 181 participants with hair samples (61% women, median age: 39 years; CD4+ cell count: 167 cells/μl; HIV-1 RNA: 18 648 copies/ml), 91 (50%) experienced virologic failure at either visit. At 24 weeks, median hair concentrations were 2.95 [interquartile range (IQR) 0.49-4.60] ng/mg for atazanavir, 2.64 (IQR 0.73--7.16) for lopinavir, and 0.44 (IQR 0.11--0.76) for ritonavir. Plasma HIV-1 RNA demonstrated inverse correlations with hair levels (rs -0.46 to -0.74) at weeks 24 and 48. Weaker associations were seen with self-reported adherence (rs -0.03 to -0.24). Decreasing hair concentrations were significantly associated with virologic failure, the hazard ratio (95% CI) for ATV, LPV, and RTV were 0.69 (0.56-0.86), 0.77 (0.68-0.87), and 0.12 (0.06-0.27), respectively.

Conclusion: Protease inhibitor hair concentrations showed stronger associations with subsequent virologic outcomes than self-reported adherence in this cohort. Hair adherence measures could identify individuals at risk of second-line treatment failure in need of interventions.