Consensus statement of the European guidelines on clinical management of HIV-1 tropism testing

Introduction: Testing for HIV tropism is recommended before prescribing a chemokine receptor blocker. To date, in most European countries HIV tropism is determined using a phenotypic test. Recently, new data have emerged supporting the use of a genotypic HIV V3-loop sequence analysis as the basis for tropism determination. The European guidelines group on clinical management of HIV-1 tropism testing was established to make recommendations to clinicians and virologists. Methods: We searched online databases for articles from Jan 2006 until March 2010 with the terms: tropism or CCR5-antagonist or CCR5 antagonist or maraviroc or vicriviroc. Additional articles and/or conference abstracts were identified by hand searching. This strategy identified 712 potential articles and 1240 abstracts. All were reviewed and finally 57 papers and 42 abstracts were included and used by the panel to reach a consensus statement. Results: The panel recommends HIV-tropism testing for the following indications: i) drug-naïve patients in whom toxicity or limited therapeutic options are foreseen; ii) patients experiencing therapy failure whenever a treatment change is considered. Both the phenotypic Enhanced Trofile assay (ESTA) and genotypic population sequencing of the V3-loop are recommended for use in clinical practice. Although the panel does not recommend one methodology over another it is anticipated that genotypic testing will be used more frequently because of its greater accessibility, lower cost and shorter turnaround time. The panel also provides guidance on technical aspects and interpretation issues. If using genotypic methods, triplicate PCR amplification and sequencing testing is advised using the G2P interpretation tool (clonal model) with an FPR of 10%. If the viral load is below the level of reliable amplification, proviral DNA can be used, and the panel recommends performing triplicate testing and use of an FPR of 10%. If genotypic DNA testing is not performed in triplicate the FPR should be increased to 20%. Conclusions: The European guidelines on clinical management of HIV-1 tropism testing provide an overview of current literature, evidence-based recommendations for the clinical use of tropism testing and expert guidance on unresolved issues and current developments. Current data support both the use of genotypic population sequencing and ESTA for co-receptor tropism determination. For practical reasons genotypic population sequencing is the preferred method in Europe.

Respiratory infection in congenital cardiac disease. Hospitalizations in young children in Spain during 2004 and 2005: the CIVIC Epidemiologic Study.

OBJECTIVES To evaluate the rate of hospitalization for acute respiratory tract infection in children less than 24 months with haemodynamically significant congenital cardiac disease, and to describe associated risk factors, preventive measures, aetiology, and clinical course. MATERIALS AND METHODS We followed 760 subjects from October 2004 through April 2005 in an epidemiological, multicentric, observational, follow-up, prospective study involving 53 Spanish hospitals. RESULTS Of our cohort, 79 patients (10.4%, 95% CI: 8.2%-12.6%) required a total of 105 admissions to hospital related to respiratory infections. The incidence rate was 21.4 new admissions per 1000 patients-months. Significant associated risk factors for hospitalization included, with odds ratios and 95% confidence intervals shown in parentheses: 22q11 deletion (8.2, 2.5-26.3), weight below the 10th centile (5.2, 1.6-17.4), previous respiratory disease (4.5, 2.3-8.6), incomplete immunoprophylaxis against respiratory syncytial virus (2.2, 1.2-3.9), trisomy 21 (2.1, 1.1-4.2), cardiopulmonary bypass (2.0, 1.1-3.4), and siblings aged less than 11 years old (1.7, 1.1-2.9). Bronchiolitis (51.4%), upper respiratory tract infections (25.7%), and pneumonia (20%) were the main diagnoses. An infectious agent was found in 37 cases (35.2%): respiratory syncytial virus in 25, Streptococcus pneumoniae in 5, and Haemophilus influenzae in 4. The odds ratio for hospitalization due to infection by the respiratory syncytial virus increases by 3.05 (95% CI: 2.14 to 4.35) in patients with incomplete prophylaxis. The median length of hospitalization was 7 days. In 18 patients (17.1%), the clinical course of respiratory infection was complicated and 2 died. CONCLUSIONS Hospital admissions for respiratory infection in young children with haemodynamically significant congenital cardiac disease are mainly associated with non-cardiac conditions, which may be genetic, malnutrition, or respiratory, and to cardiopulmonary bypass. Respiratory syncytial virus was the most commonly identified infectious agent. Incomplete immunoprophylaxis against the virus increased the risk of hospitalization.

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown. METHODS AND FINDINGS The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed. CONCLUSIONS These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.