Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings

OBJECTIVES: Genotypic HIV drug-resistance testing is typically 60%–65% predictive of response to combination antiretroviral therapy (ART) and is valuable for guiding treatment changes. Genotyping is unavailable in many resource-limited settings (RLSs). We aimed to develop models that can predict res...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Main Authors: Revell, A. D., Wang, D., Wood, R., Morrow, C., Tempelman, H., Hamers, R. L., Alvarez-Uria, G., Streinu-Cercel, A., Ene, L., Wensing, A. M. J., DeWolf, F., Nelson, M., Montaner, J. S., Lane, H. C., Larder, B. A.
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2013
Assuntos:
Original Research
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC3654223/
https://ncbi.nlm.nih.gov/pubmed/23485767
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jac/dkt041
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!

Registos relacionados