Year: 2024
Type: article
Abstract: BACKGROUND: Incomplete adherence to daily tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) reduces effectiveness. Adherence biomeasures (ie, drug concentrations in biological specimen) are more accurate than self-report. TDF/FTC's intracellular active metabolites (tenofovir-diphosphate; TFVdp and FTC-triphosphate; FTCtp) can be quantified in different types of blood samples to estimate adherence. To optimize adherence estimation, we investigated approaches to measure TFVdp and FTCtp in 4 blood matrices. METHODS: Twelve HIV-negative, healthy volunteers were enrolled in a single-center, open-label, 3-phase, directly observed therapy study. LC-MS/MS methods quantified TFVdp/FTCtp in dried blood spots, volumetrically accurate microsampling, upper layer packed cells, and peripheral blood mononuclear cells (PBMCs). Noncompartmental analysis estimated half-lives and accumulation ratios. Correlations characterized relationships between clinical variables and exposure. Regression models were fit to determine concentrations associated with <4 and ≥4 doses/week; correct classification percentages were determined. RESULTS: Terminal half-life estimates of 3-4 vs 15-22 days distinguished between moderate-term (FTCtp in all samples; TFVdp in PBMCs) versus long-term (TFVdp in red blood cell-containing matrices) measures. Model-derived thresholds accurately categorized <4 and ≥4 doses/week when including both metabolites for 14- and 28-day dosing periods (81%-91% and 82%-85%, respectively). Within each classification and regression trees analyses containing both moderate- and long-term measures, dried blood spots exhibited highest accuracy to predict stable (74%-94%) and changing (42%-47%) adherence patterns. CONCLUSIONS: We demonstrate higher accuracy of moderate-term biomeasures to classify adherence over a 14-day period compared with long-term biomeasures to classify adherence over a 28-day period. Combined moderate- and long-term biomeasures predicted stable and changing adherence patterns, with dried blood spots exhibiting highest accuracy.
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: University of Pittsburgh, National Institutes of Health, Center for AIDS Research, University of Washington, University of North Carolina at Chapel Hill, University of Pittsburgh School of Pharmacy, National Heart, Lung, and Blood Institute, National Institute of Allergy and Infectious Diseases, National Center for Advancing Translational Sciences, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill
OpenAlex ID: W4404583090