Spontaneous viral clearance, viral load, and genotype distribution of hepatitis C virus (HCV) in HIV-infected patients with anti-HCV antibodies in Europe

BACKGROUND: Variables influencing serum hepatitis C virus (HCV) RNA levels and genotype distribution in individuals with human immunodeficiency virus (HIV) infection are not well known, nor are factors determining spontaneous clearance after exposure to HCV in this population. METHODS: All HCV antibody (Ab)-positive patients with HIV infection in the EuroSIDA cohort who had stored samples were tested for serum HCV RNA, and HCV genotyping was done for subjects with viremia. Logistic regression was used to identify variables associated with spontaneous HCV clearance and HCV genotype 1. RESULTS: Of 1940 HCV Ab-positive patients, 1496 (77%) were serum HCV RNA positive. Injection drug users (IDUs) were less likely to have spontaneously cleared HCV than were homosexual men (20% vs. 39%; adjusted odds ratio [aOR], 0.36 [95% confidence interval {CI}, 0.24-0.53]), whereas patients positive for hepatitis B surface antigen (HBsAg) were more likely to have spontaneously cleared HCV than were those negative for HBsAg (43% vs. 21%; aOR, 2.91 [95% CI, 1.94-4.38]). Of patients with HCV viremia, 786 (53%) carried HCV genotype 1, and 53 (4%), 440 (29%), and 217 (15%) carried HCV genotype 2, 3, and 4, respectively. A greater HCV RNA level was associated with a greater chance of being infected with HCV genotype 1 (aOR, 1.60 per 1 log higher [95% CI, 1.36-1.88]). CONCLUSIONS: More than three-quarters of the HIV- and HCV Ab-positive patients in EuroSIDA showed active HCV replication. Viremia was more frequent in IDUs and, conversely, was less common in HBsAg-positive patients. Of the patients with HCV viremia analyzed, 53% were found to carry HCV genotype 1, and this genotype was associated with greater serum HCV RNA levels

A review of evolutionary algorithms for data mining

Summary. Evolutionary Algorithms (EAs) are stochastic search algorithms inspired by the process of neo-Darwinian evolution. The motivation for applying EAs to data mining is that they are robust, adaptive search techniques that perform a global search in the solution space. This chapter first presents a brief overview of EAs, focusing mainly on two kinds of EAs, viz. Genetic Algorithms (GAs) and Genetic Programming (GP). Then the chapter reviews the main concepts and principles used by EAs designed for solving several data mining tasks, namely: discovery of classification rules, clustering, attribute selection and attribute construction. Finally, it discusses Multi-Objective EAs, based on the concept of Pareto dominance, and their use in several data mining tasks

Does less frequent routine monitoring of patients on a stable, fully suppressed cART regimen lead to an increased risk of treatment failure?

SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Hepatitis C virus coinfection does not influence the CD4 cell recovery in HIV-1-infected patients with maximum virologic suppression

BACKGROUND: Conflicting data exist whether hepatitis C virus (HCV) affects the CD4 cell recovery in patients with HIV starting antiretroviral treatment. OBJECTIVE: To investigate the influence of HCV coinfection on the CD4 recovery in patients with maximum virologic suppression within the EuroSIDA cohort. METHODS: Patients tested for anti-HCV antibodies and with at least 2 consecutive HIV viral loads (VLs) <50 copies per milliliter after starting combination antiretroviral therapy were eligible for inclusion. For each pair of VL <50 copies per milliliter, the annual change in CD4 count was calculated and compared between (1) HCV-seronegative vs. HCV-seropositive patients, (2) HCV genotypes 1-4 in HCV-RNA+ patients, and (3) viremic vs. aviremic (HCV-RNA < 615 IU/mL) in HCV-seropositive patients. Results were adjusted for known confounders. RESULTS: Four thousand two hundred eight patients were included, representing 39,474 pairs of HIV VL measurements with VL <50 copies per milliliter and 12,492 person-years of follow-up. The unadjusted annual change in CD4 count for HCV-seropositive and HCV-seronegative patients was 35.5 cells per milliliter (95% confidence interval 27.2 to 43.9) and 38.3 cells per milliliter (95%confidence interval 34.8 to 41.9), respectively. After adjustment, there was no difference in CD4 change when comparing, according to HCV serostatus (P = 0.17), between genotypes (P = 0.23) or when comparing HCV viremic vs. aviremic patients (P = 0.57). Adjusting additionally for HCV treatment and HCV-RNA VL did not change the findings.CONCLUSIONS: HCV serostatus did not influence the CD4 recovery in patients with HIV with maximum virologic suppression after starting combination antiretroviral therapy. Furthermore, no difference in CD4 gain was found when comparing distinct HCV genotypes in HCV-RNA+ patients or when comparing HCV viremic vs. aviremic HCV-seropositive patients