Background This study aimed to examine the evolution of genotypic drug resistance prevalence in treatment-failing patients in the multicentre, Italian, Antiretroviral Resistance Cohort Analysis (ARCA). Methods Patients with a drug resistance genotype test performed between 1999 and 2006 at failure of a combination antiretroviral therapy and with complete treatment history were selected. The prevalence of resistance was measured overall, per calendar year, per drug class and per treatment line at failure. Results The overall resistance prevalence was 81%. Resistance to nucleoside reverse transcriptase inhibitors (NRTIs) declined after 2002 (68% in 2006; χ 2 for trend P=0.004); resistance to non-NRTIs (NNRTIs) stabilized after 2004; and resistance to protease inhibitors (PIs) declined after 2001 (43% in 2006; P=0.004). In first-line failures, NRTI resistance decreased after 2002 ( P=0.006), NNRTI resistance decreased after 2003 ( P=0.001) and PI resistance decreased after 2001 ( P<0.001). Independent predictors of resistance to any class were HIV type-1 transmission by heterosexual contacts as compared with injecting drug use, a higher number of experienced regimens, prior history of suboptimal therapy, higher viral load and CD4 + T-cell counts, more recent calendar year and viral subtype B carriage, whereas the use of PI-based versus NNRTI-based regimens at failure was associated with a reduced risk of resistance. There was an increase of type-1 thymidine analogue and of protease mutations L33F, I47A/V, I50V and I54L/M, whereas L90M decreased over calendar years. Conclusions During more recent years, emerging drug resistance has decreased, particularly in first-line failures. The prevalence continues to be high in multiregimen-failing patients.
HIV-1 genotypic susceptibility scores (GSSs) were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART) switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed. We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90th day after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems (Rega, ANRS and HIVdb) and other covariates by means of Cox regression and random survival forests (RSF). Prediction models were validated via the bootstrap and c-index measure. The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70), while RSF showed a better performance (c-index≈0.73, p < 0.0001 vs. Cox regression). Variable importance according to RSF was concordant with the Cox hazards. GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART.
The purpose of this paper is to contextualize the case of a patient with a synchronous diagnosis of colorectal cancer (CRC) and endocarditis from S. gallolyticus subsp. pasteuranus (former S. Bovis) within the current evidence, in order to determine if this condition is indicative of an underlying CRC and if it has any pathophysiologic significance.First, we describe the clinical case. Then, we review the literature focused on the association between infections from the former S. Bovis group and CRC and on the possible role of certain microbiota species on the occurrence of CRC. At last, we discuss the implications of this case considering the current evidence.There is a strong association between all the species of the former S. Bovis group and CRC. There is initial evidence that these bacteria may contribute to CRC by a genomic passenger mechanism.There are two main conclusions for this paper. The first one is that CRC neoplasms and endocarditis from all species of the former S. bovis group have a strong association. Any case of infection by these subspecies should prompt to a diagnostic completion by colonoscopy. The second one is that there is an increased need for detailed reports/series and original articles based on the evaluation of gut microbiota in patients with CRC, with the aim to clarify if the association between bacteria and CRC is causative or sporadic and to better understand the possible causative mechanism of specific bacteria in initiating and promoting CRC.
Gillini, Laura Aian*; Cingolani, Antonella*; Murri, Rita*; De Luca, Andrea*; Di Giambenedetto, Simona*; Wu, Albert†; Cauda, Roberto*; Chaisson, Richard E.† Author Information
Background: HIV-1 drug resistance can be measured with phenotypic drug-resistance tests. However, the output of these tests, the resistance factor (RF), requires interpretation with respect to the in vivo activity of the tested variant. Specifically, the dynamic range of the RF for each drug has to be divided into a suitable number of clinically meaningful intervals. Methods: We calculated a susceptible-to-intermediate and an intermediate-to-resistant cutoff per drug for RFs predicted by geno2pheno [resistance] . Probability densities for therapeutic success and failure were estimated from 10,444 treatment episodes. The density estimation procedure corrects for the activity of the backbone drug compounds and for therapy failure without drug resistance. For estimating the probability of therapeutic success given an RF, we fit a sigmoid function. The cutoffs are given by the roots of the third derivative of the sigmoid function. Results: For performance assessment, we used geno2pheno [resistance] RF predictions and the cutoffs for predicting therapeutic success in 2 independent sets of therapy episodes. HIVdb was used for performance comparison. On one test set (n = 807), our cutoffs and HIVdb performed equally well receiver operating characteristic curve [(ROC)–area under the curve (AUC): 0.68]. On the other test set (n = 917), our cutoffs (ROC–AUC: 0.63) and HIVdb (ROC–AUC: 0.65) performed comparatively well. Conclusions: Our method can be used for calculating clinically relevant cutoffs for (predicted) RFs. The method corrects for the activity of the backbone drug compounds and for therapy failure without drug resistance. Our method's performance is comparable with that of HIVdb. RF cutoffs for the latest version of geno2pheno [resistance] have been estimated with this method.
ObjectivesTo explore the durability of three first-line tenofovir/emtricitabine-based regimens in combination with atazanavir/ritonavir, efavirenz or lopinavir/ritonavir in HIV-1-infected patients.
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