Long-term follow-up of metabolic activity in human alveolar echinococcosis using FDG-PET

AIM: [(18)F]fluoro-deoxyglucose positron-emission-tomography (FDG-PET) detects metabolic activity in alveolar echinococcosis (AE). The slow changes in metabolic and morphological characteristics require long-term follow-up of patients. This is the first study to evaluate metabolic activity over may years, hereby assessing the utility of FDG-PET for the evaluation of disease progression and response to treatment. PATIENTS, METHODS: 15 patients received a follow-up FDG-PET combined with computed tomography (integrated PET/CT) with a median of 6.5 years after the first PET in 1999. Number and location of enhanced metabolic activity in the area of AE lesions was determined. Quantification of intensity of metabolic activity was assessed by calculation of mean standardized uptake values. RESULTS: AE lesions in 11/15 patients had been metabolically inactive initially, but only two showed permanent inactivity over the course of 81 months. Interestingly, in two patients metabolic activity was newly detected after 80 and 82 months. Benzimidazole treatment was intermittently discontinued in seven cases. Persisting activity at FDG-PET demanded continued benzimidazole treatment in four patients. Neither treatment duration, lesional size, calcifications nor regressive changes correlated with metabolic activity. CONCLUSION: Treatment responses are heterogeneous and vary from progressive disease despite treatment to long-term inactive disease with discontinued treatment. Lack of metabolic activity indicates suppressed parasite activity and is not equivalent to parasite death. However, metabolic activity may remain suppressed for years, allowing for temporary treatment discontinuation. Relapses are reliably detected with PET and restarting benzimidazole treatment prevents parasite expansion.

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

Growth curves for cardio-metabolic risk factors in children and adolescents

OBJECTIVE: This study developed percentile curves for anthropometric (waist circumference) and cardiovascular (lipid profile) risk factors for US children and adolescents. STUDY DESIGN: A representative sample of US children and adolescents from the National Health and Nutrition Examination Survey from 1988 to 1994 (NHANES III) and the current national series (NHANES 1999-2006) were combined. Percentile curves were constructed, nationally weighted, and smoothed using the Lambda, Mu, and Sigma method. The percentile curves included age- and sex-specific percentile values that correspond with and transition into the adult abnormal cut-off values for each of these anthropometric and cardiovascular components. To increase the sample size, a second series of percentile curves was also created from the combination of the 2 NHANES databases, along with cross-sectional data from the Bogalusa Heart Study, the Muscatine Study, the Fels Longitudinal Study and the Princeton Lipid Research Clinics Study. RESULTS: These analyses resulted in a series of growth curves for waist circumference, total cholesterol, LDL cholesterol, triglycerides, and HDL cholesterol from a combination of pediatric data sets. The cut-off for abnormal waist circumference in adult males (102 cm) was equivalent to the 94(th) percentile line in 18-year-olds, and the cut-off in adult females (88 cm) was equivalent to the 84(th) percentile line in 18-year-olds. Triglycerides were found to have a bimodal pattern among females, with an initial peak at age 11 and a second at age 20; the curve for males increased steadily with age. The HDL curve for females was relatively flat, but the male curve declined starting at age 9 years. Similar curves for total and LDL cholesterol were constructed for both males and females. When data from the additional child studies were added to the national data, there was little difference in their patterns or rates of change from year to year. CONCLUSIONS: These curves represent waist and lipid percentiles for US children and adolescents, with identification of values that transition to adult abnormalities. They could be used conditionally for both epidemiological and possibly clinical applications, although they need to be validated against longitudinal data.