Pharmaco-virological algorithm to target risk of drug resistance among a population of HIV-infected key populations in Togo.
Valentine Marie FerréAlexandra M Bitty-AndersonGilles PeytavinMinh P LêClaver A DagnraRomain CoppéeFifonsi A Gbeasor-KomlanviDiane DescampsCharlotte CharpentierDidier K EkoueviPublished in: Journal of medical virology (2023)
No data about antiretroviral (ARV) treatment coverage and virological response are available among key populations (female sex workers [FSW] and Men having Sex with Men [MSM]) in Togo. This study aimed to both describe Human Immunodeficiency Virus (HIV) immunovirological status and evaluate the pertinence of an original algorithm combining pharmacology (PK) and viral load (VL) to identify subjects at risk of ARV drug resistance. A cross-sectional multicentric study was conducted in 2017 in Togo. Our PK-virological algorithm (PK-VA) defines subjects at risk of resistance when exhibiting both detectable plasma drug concentrations and VL > 200 c/mL. Among the 123 FSW and 136 MSM included, 50% and 66% were receiving ARV, with 69% and 80% of them successfully-treated, respectively. Genotypes showed drug-resistance mutation in 58% and 63% of nonvirologically controlled (VL > 200 c/mL) ARV-treated FSW and MSM, respectively. PK-VA would have enabled to save 75% and 72% of genotypic tests, for FSW and MSM, respectively. We reported first data about HIV care cascade among key populations in Togo, highlighting they are tested for HIV but linkage to care remains a concern. Furthermore, 70%-80% of ARV-treated participants experienced virological success. In limited resources settings, where genotyping tests are beyond reach, PK-VA might be an easiest solution to sort out patients needing ARV adaptation due to resistance.
Keyphrases
- hiv infected
- antiretroviral therapy
- human immunodeficiency virus
- hiv testing
- hiv positive
- hiv infected patients
- men who have sex with men
- hiv aids
- machine learning
- newly diagnosed
- end stage renal disease
- deep learning
- electronic health record
- healthcare
- hepatitis c virus
- genome wide
- ejection fraction
- chronic kidney disease
- big data
- prognostic factors
- middle aged
- emergency department
- genetic diversity
- quality improvement
- south africa
- pain management
- neural network
- dna methylation