A comparison of covariate selection techniques applied to pre-exposure prophylaxis (PrEP) drug concentration data in men and transgender women at risk for HIV.
Journal
Journal of pharmacokinetics and pharmacodynamics
ISSN: 1573-8744
Titre abrégé: J Pharmacokinet Pharmacodyn
Pays: United States
ID NLM: 101096520
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
received:
12
10
2020
accepted:
05
05
2021
pubmed:
21
5
2021
medline:
11
2
2022
entrez:
20
5
2021
Statut:
ppublish
Résumé
Pre-exposure prophylaxis (PrEP) containing antiretrovirals tenofovir disoproxil fumarate (TDF) or tenofovir alafenamide (TAF) can reduce the risk of acquiring HIV. Concentrations of intracellular tenofovir-diphosphate (TFV-DP) measured in dried blood spots (DBS) have been used to quantify PrEP adherence; although even under directly observed dosing, unexplained between-subject variation remains. Here, we wish to identify patient-specific factors associated with TFV-DP levels. Data from the iPrEX Open Label Extension (OLE) study were used to compare multiple covariate selection methods for determining demographic and clinical covariates most important for drug concentration estimation. To allow for the possibility of non-linear relationships between drug concentration and explanatory variables, the component selection and smoothing operator (COSSO) was implemented. We compared COSSO to LASSO, a commonly used machine learning approach, and traditional forward and backward selection. Training (N = 387) and test (N = 166) datasets were utilized to compare prediction accuracy across methods. LASSO and COSSO had the best predictive ability for the test data. Both predicted increased drug concentration with increases in age and self-reported adherence, the latter with a steeper trajectory among Asians. TFV-DP reductions were associated with increasing eGFR, hemoglobin and transgender status. COSSO also predicted lower TFV-DP with increasing weight and South American countries. COSSO identified non-linear relationships between log(TFV-DP) and adherence, weight and eGFR, with differing trajectories for some races. COSSO identified non-linear log(TFV-DP) trajectories with a subset of covariates, which may better explain variation and enhance prediction. Future research is needed to examine differences identified in trajectories by race and country.
Identifiants
pubmed: 34013454
doi: 10.1007/s10928-021-09763-y
pii: 10.1007/s10928-021-09763-y
doi:
Substances chimiques
Anti-HIV Agents
0
Organophosphates
0
tenofovir diphosphate
0
Tenofovir
99YXE507IL
Adenine
JAC85A2161
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
655-669Subventions
Organisme : NIH HHS
ID : RO1 AI122298
Pays : United States
Organisme : NIH HHS
ID : UO1 AI64002
Pays : United States
Organisme : NIH HHS
ID : UO1 AI84735
Pays : United States
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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