Use of variability in national and regional data to estimate the prevalence of lymphangioleiomyomatosis.

Background: Understanding the true prevalence of lymphangioleiomyomatosis (LAM) is important in estimating disease burden and targeting specific interventions. As with all rare diseases, obtaining reliable epidemiological data is difficult and requires innovative approaches.Aim: To determine the prevalence and incidence of LAM using data from patient organizations in seven countries, and to use the extent to which the prevalence of LAM varies regionally and nationally to determine whether prevalence estimates are related to health-care provision.Methods: Numbers of women with LAM were obtained from patient groups and national databases from seven countries (n = 1001). Prevalence was calculated for regions within countries using female population figures from census data. Incidence estimates were calculated for the USA, UK and Switzerland. Regional variation in prevalence and changes in incidence over time were analysed using Poisson regression and linear regression.Results: Prevalence of LAM in the seven countries ranged from 3.4 to 7.8/million women with significant variation, both between countries and between states in the USA. This variation did not relate to the number of pulmonary specialists in the region nor the percentage of population with health insurance, but suggests a large number of patients remain undiagnosed. The incidence of LAM from 2004 to 2008 ranged from 0.23 to 0.31/million women/per year in the USA, UK and Switzerland.Conclusions: Using this method, we have found that the prevalence of LAM is higher than that previously recorded and that many patients with LAM are undiagnosed.

Health literacy [Document électronique] : an economic perspective and data for Switzerland. Part 2, A review of health literacy measures and a cost assessment of limited health literacy

Summary : 1. Measuring health literacy in Switzerland: a review of six surveys: 1.1 Comparison of questionnaires - 1.2 Measures of health literacy in Switzerland - 1.3 Discussion of Swiss data on HL - 1.4 Description of the six surveys: 1.4.1 Current health trends and health literacy in the Swiss population (gfs-UNIVOX), 1.4.2 Nutrition, physical exercise and body weight : opinions and perceptions of the Swiss population (USI), 1.4.3 Health Literacy in Switzerland (ISPMZ), 1.4.4 Swiss Health Survey (SHS), 1.4.5 Survey of Health, Ageing and Retirement in Europe (SHARE), 1.4.6 Adult literacy and life skills survey (ALL). - 2 . Economic costs of low health literacy in Switzerland: a rough calculation. Appendix: Screenshots cost model

Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest

The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.

Truncated robust distance for clinical laboratory safety data monitoring and assessment.

Laboratory safety data are routinely collected in clinical studies for safety monitoring and assessment. We have developed a truncated robust multivariate outlier detection method for identifying subjects with clinically relevant abnormal laboratory measurements. The proposed method can be applied to historical clinical data to establish a multivariate decision boundary that can then be used for future clinical trial laboratory safety data monitoring and assessment. Simulations demonstrate that the proposed method has the ability to detect relevant outliers while automatically excluding irrelevant outliers. Two examples from actual clinical studies are used to illustrate the use of this method for identifying clinically relevant outliers.

Comparative analysis of human and mouse expression data illuminates tissue-specific evolutionary patterns of miRNAs.

MicroRNAs (miRNAs) constitute an important class of gene regulators. While models have been proposed to explain their appearance and expansion, the validation of these models has been difficult due to the lack of comparative studies. Here, we analyze miRNA evolutionary patterns in two mammals, human and mouse, in relation to the age of miRNA families. In this comparative framework, we confirm some predictions of previously advanced models of miRNA evolution, e.g. that miRNAs arise more frequently de novo than by duplication, or that the number of protein-coding gene targeted by miRNAs decreases with evolutionary time. We also corroborate that miRNAs display an increase in expression level with evolutionary time, however we show that this relation is largely tissue-dependent, and especially low in embryonic or nervous tissues. We identify a bias of tag-sequencing techniques regarding the assessment of breadth of expression, leading us, contrary to predictions, to find more tissue-specific expression of older miRNAs. Together, our results refine the models used so far to depict the evolution of miRNA genes. They underline the role of tissue-specific selective forces on the evolution of miRNAs, as well as the potential co-evolution patterns between miRNAs and the protein-coding genes they target.

Hyperhidrosis: a new and often early symptom in Fabry disease. International experience and data from the Fabry Outcome Survey.

Hypohidrosis is a classic feature of Fabry disease; in contrast, hyperhidrosis has only been rarely described. The aim of the study is to characterise the baseline descriptive data on hyperhidrosis (frequency, age at onset, sex ratio and outcome with and without enzyme replacement therapy) in hemizygous male and heterozygous female patients with Fabry disease. We describe case histories of five patients with Fabry disease and hyperhidrosis seen at three different centres. We have also analysed a cohort of 21 paediatric patients in the UK and a large European cohort of patients enrolled in the Fabry Outcome Survey (FOS). Five patients (three female, two male) with hyperhidrosis were originally identified, although each had additional symptoms related to Fabry disease. The age at onset of hyperhidrosis was less than 18 years in four cases. In the cohort of 21 paediatric patients (12 female, nine male), one female had hyperhidrosis; the age at onset of this symptom was 11 years. In the FOS cohort, 66 of 714 patients with Fabry disease had hyperhidrosis (44 of 369 females, 11.9%; 22 of 345 males, 6.4%). The female predominance was observed in seven of nine countries from which data were analysed. Hyperhidrosis is an increasingly recognised feature of the Fabry disease phenotype. It is more prevalent in females than in males and often appears in childhood or adolescence. The efficacy of enzyme replacement therapy on this recently recognised symptom should be assessed.

A combined molecular clinical predictor of survival validated with the rtog-0525 cohort

For glioblastoma (GBM), survival classification has primarily relied on clinical criteria, exemplified by the Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA). We sought to improve tumor classification by combining tumor biomarkers with the clinical RPA data. To accomplish this, we first developed 4 molecular biomarkers derived from gene expression profiling, a glioma CpG island methylator phenotype, a novel MGMT promoter methylation assay, and IDH1 mutations. A molecular predictor (MP) model was created with these 4 biomarkers on a training set of 220 retrospectively collected archival GBMtumors. ThisMPwas further combined with RPA classification to develop a molecular-clinical predictor (MCP). The median survivals for the combined, 4-class MCP were 65 months, 31 months, 13 months, and 9 months, which was significantly improved when compared with the RPA alone. The MCP was then applied to 725 samples from the RTOG-0525 cohort, showing median survival for each risk group of NR, 26 months, 16 months, and 11 months. The MCP was significantly improved over the RPA at outcome prediction in the RTOG 0525 cohort with a 33%increase in explained variation with respect to survival, validating the result obtained in the training set. To illustrate the benefit of the MCP for patient stratification, we examined progression-free survival (PFS) for patients receiving standard-dose temozolomide (SD-TMZ) vs. dose-dense TMZ (DD-TMZ) in RPA and MCP risk groups. A significant difference between DD-TMZ and SD-TMZ was observed in the poorest surviving MCP risk group with a median PFS of 6 months vs. 3 months (p ¼ 0.048, log-rank test). This difference was not seen using the RPA classification alone. In summary, we have developed a combined molecular-clinical predictor that appears to improve outcome prediction when compared with clinical variables alone. This MCP may serve to better identify patients requiring intensive treatments beyond the standard of care.