No abstract

Background: Virus-associated cell membrane proteins acquired by HIV-1 during budding may give information on the cellular source of circulating virions. In the present study, by applying immunosorting of the virus and of the cells with antibodies targeting monocyte (CD36) and lymphocyte (CD26) markers, it was possible to directly compare HIV-1 quasispecies archived in circulating monocytes and T lymphocytes with that present in plasma virions originated from the same cell types. Five chronically HIV-1 infected patients who underwent therapy interruption after prolonged HAART were enrolled in the study. The analysis was performed by the powerful technology of ultra-deep pyrosequencing after PCR amplification of part of the env gene, coding for the viral glycoprotein (gp) 120, encompassing the tropism-related V3 loop region. V3 amino acid sequences were used to establish heterogeneity parameters, to build phylogenetic trees and to predict co-receptor usage.

BackgroundOptimal adherence to antiretroviral therapy is critical to prevent HIV drug resistance (HIVDR) epidemic. The objective of the study was to investigate the best performing adherence assessment method for predicting virological failure in resource-limited settings (RLS).MethodThis study was a single-centre prospective cohort, enrolling 220 HIV-infected adult patients attending an HIV/AIDS Care and Treatment Centre in Dar es Salaam, Tanzania, in 2010. Pharmacy refill, self-report (via visual analog scale [VAS] and the Swiss HIV Cohort study-adherence questionnaire), pill count, and appointment keeping adherence measurements were taken.Univariate logistic regression (LR) was done to explore a cut-off that gives a better trade-off between sensitivity and specificity, and a higher area under the curve (AUC) based on receiver operating characteristic curve in predicting virological failure. Additionally, the adherence models were evaluated by fitting multivariate LR with stepwise functions, decision trees, and random forests models, assessing 10-fold multiple cross validation (MCV). Patient factors associated with virological failure were determined using LR.ResultsViral load measurements at baseline and one year after recruitment were available for 162 patients, of whom 55 (34%) had detectable viral load and 17 (10.5%) had immunological failure at one year after recruitment. The optimal cut-off points significantly predictive of virological failure were 95%, 80%, 95% and 90% for VAS, appointment keeping, pharmacy refill, and pill count adherence respectively. The AUC for these methods ranged from 0.52 to 0.61, with pharmacy refill giving the best performance at AUC 0.61.Multivariate logistic regression with boost stepwise MCV had higher AUC (0.64) compared to all univariate adherence models, except pharmacy refill adherence univariate model, which was comparable to the multivariate model (AUC = 0.64). Decision trees and random forests models were inferior to boost stepwise model.Pharmacy refill adherence (<95%) emerged as the best method for predicting virological failure. Other significant predictors in multivariate LR were having a baseline CD4 T lymphocytes count < 200 cells/μl, being unable to recall the diagnosis date, and a higher weight.ConclusionPharmacy refill has the potential to predict virological failure and to identify patients to be considered for viral load monitoring and HIVDR testing in RLS.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2458-14-1035) contains supplementary material, which is available to authorized users.

We evaluated factors associated with normalization of the absolute CD4+ T-cell counts, per cent CD4+ T cells and CD4+/CD8+ T-cell ratio. A multicentre observational study was carried out in patients with sustained HIV-RNA <50 copies/mL. Outcomes were: CD4-count >500/mm(3) and multiple T-cell marker recovery (MTMR), defined as CD4+ T cells >500/mm(3) plus%CD4 T cells >29%plus CD4+/CD8+ T-cell ratio >1. Kaplan-Meier survival analysis and Cox regression analyses to predict odds for achieving outcomes were performed. Three hundred and fifty-two patients were included and followed-up for a median of 4.1 (IQR 2.1-5.9) years, 270 (76.7%) achieving a CD4+ T-cell count >500 cells/mm(3) and 197 (56%) achieving MTMR. Using three separate Cox models for both outcomes we demonstrated that independent predictors were: both absolute CD4+ and CD8+ T-cell counts, %CD4+ T cells, a higher CD4+/CD8+ T-cell ratio, and age. A likelihood-ratio test showed significant improvements in fitness for the prediction of either CD4+ >500/mm(3) or MTMR by multivariable analysis when the other immune markers at baseline, besides the absolute CD4+ count alone, were considered. In addition to baseline absolute CD4+ T-cell counts, pretreatment %CD4+ T cells and the CD4+/CD8+ T-cell ratio influence recovery of T-cell markers, and their consideration should influence the decision to start antiretroviral therapy. However, owing to the small sample size, further studies are needed to confirm these results in relation to clinical endpoints.