Uncertainty effect on leak localisation in a DMA

The leak localisation methodologies based on data and models are affected by both uncertainties in the model and in the measurements. This uncertainty should be quantified so that its effect on the localisation methods performance can be estimated. In this paper, a model-based leak localisation methodology is applied to a real District Metered Area using synthetic data. In the generation process of the data, uncertainty in demands is taken into account. This uncertainty was estimated so that it can justify the uncertainty observed in the real measurements. The leak localisation methodology consists, first, in generating the set of possible measurements, obtained by Monte Carlo Simulation under a certain leak assumption and considering uncertainty, and second, in falsifying sets of nodes using the correlation with a leak residual model in order to signal a set of possible leaky nodes. The assessment is done by means of generating the confusion matrix with a Monte Carlo approach.Peer ReviewedPostprint (author's final draft

La fuerza del tren inferior como principal predictor de la calidad de vida en pacientes con alzheimer. Lower body strength as the main producer of the quality of life in patients with alzheimer

Objetivo: Analizar los factores predictores de la CVRS en pacientes diagnosticados de Alzheimer. Métodos: Se evaluó la CVRS, la capacidad funcional, el estilo de vida objetivo, la composición corporal y la función cognitiva en 15 enfermos de Alzheimer con una edadmedia de 80.4 años. Resultados: La fuerza del tren inferior, el riesgo de caída y el índice de masa corporal fueron determinantes significativos de la CVRS (R²=0.77, P=0.002), siendola fuerza del tren inferior el mejor predictor independiente de la CVRS, contribuyendo en un 49% a la variación de la CVRS. La resistencia aeróbica, el tiempo tumbado, el tiempo de sueño,el deterioro cognitivo y el tiempo en los test de equilibrio y marcha también se encuentran asociados con la CVRS. Conclusión: La fuerza del tren inferior, el miedo a caer y el índicede masa corporal son determinantes significativos de la CVRS en personas mayores con Alzheimer, siendo la fuerza del tren inferior la que explica la mayor proporción de la varianza de la CVRS de los enfermos de Alzheimer

REGSTATTOOLS: freeware statistical tools for the analysis of disease population databases used in health and social studies

Background: The repertoire of statistical methods dealing with the descriptive analysis of the burden of a disease has been expanded and implemented in statistical software packages during the last years. The purpose of this paper is to present a web-based tool, REGSTATTOOLS http://regstattools.net intended to provide analysis for the burden of cancer, or other group of disease registry data. Three software applications are included in REGSTATTOOLS: SART (analysis of disease"s rates and its time trends), RiskDiff (analysis of percent changes in the rates due to demographic factors and risk of developing or dying from a disease) and WAERS (relative survival analysis). Results: We show a real-data application through the assessment of the burden of tobacco-related cancer incidence in two Spanish regions in the period 1995-2004. Making use of SART we show that lung cancer is the most common cancer among those cancers, with rising trends in incidence among women. We compared 2000-2004 data with that of 1995-1999 to assess percent changes in the number of cases as well as relative survival using RiskDiff and WAERS, respectively. We show that the net change increase in lung cancer cases among women was mainly attributable to an increased risk of developing lung cancer, whereas in men it is attributable to the increase in population size. Among men, lung cancer relative survival was higher in 2000-2004 than in 1995-1999, whereas it was similar among women when these time periods were compared. Conclusions: Unlike other similar applications, REGSTATTOOLS does not require local software installation and it is simple to use, fast and easy to interpret. It is a set of web-based statistical tools intended for automated calculation of population indicators that any professional in health or social sciences may require

Optimal pressure sensor placement for leak localisation using a relaxed isolation index : application to the Barcelona water network

Water distribution networks are large complex systems that are affected by leaks, which often entail high costs and may severely jeopardize the overall water distribution performance. Successful leak localisation is paramount in order to minimize the impact of these leaks when occurring. Sensor placement is a key issue in the leak localisation process, since the overall performance and success of the leak isolation method highly depends on the choice of the sensors gathering data from the network. Common problems when leak isolating in large scale highly-gridded real water distribution networks include leak mislabelling and large isolation areas obtention due to similarity of the measurements, which may be caused by topological issues and led to incomplete coverage of the whole network. The sensor placement strategy may minimize these undesired effects by setting the sensor placement optimisation problem with the appropriate assumptions e.g. geographically cluster alike leak behaviors, taking into account real aspects of the practical application such as the acceptable isolation distance. Here, a sensor placement methodology considering these assets and a general sensor distribution assessment method for leak diagnosis in water distribution systems is presented for a real District Metered Area (DMA) located within the Barcelona water distribution network.Peer ReviewedPostprint (author's final draft

Parameter uncertainty modelling in water distribution network models

The use of water distribution network (WDN) models is an extended practice [13]. Confidence on decisions taken upon such models depends highly on their accuracy [11]. The parameters uncertainty has to be defined in order to include it in the model. Some of the parameters in a network (e.g. pipes lengths and diameters) can be easily measured and their uncertainty can be calculated on a statistical basis [4]. Demands cannot be measured directly and they have to be estimated using other measurements [10][8]. The uncertainty in the measurements used for that estimation is propagated to the parameters [1]. Besides, demands have their own stochastic nature that induces uncertainty. This paper describes how the pressure measurements are used to infer the uncertainty model in demands for a real network. The real data are treated in order to avoid the effect of boundary conditions. An uncertainty model for demands is calculated to justify the observed behaviour of the measurements. Montecarlo simulations are used for the validation.Peer ReviewedPostprint (published version

No Excess Mortality up to 10 Years in Early Stages of Breast Cancer in Women Adherent to Oral Endocrine Therapy: A Probabilistic Graphical Modeling Approach

Breast cancer (BC) is globally the most frequent cancer in women. Adherence to endocrine therapy (ET) in hormone-receptor-positive BC patients is active and voluntary for the first five years after diagnosis. This study examines the impact of adherence to ET on 10-year excess mortality (EM) in patients diagnosed with Stages I to III BC (N = 2297). Since sample size is an issue for estimating age- and stage-specific survival indicators, we developed a method, ComSynSurData, for generating a large synthetic dataset (SynD) through probabilistic graphical modeling of the original cohort. We derived population-based survival indicators using a Bayesian relative survival model fitted to the SynD. Our modeling showed that hormone-receptor-positive BC patients diagnosed beyond 49 years of age at Stage I or beyond 59 years at Stage II do not have 10-year EM if they follow the prescribed ET regimen. This result calls for developing interventions to promote adherence to ET in patients with hormone receptor-positive BC and in turn improving cancer survival. The presented methodology here demonstrates the potential use of probabilistic graphical modeling for generating reliable synthetic datasets for validating population-based survival indicators when sample size is an issue

Highly sensitive MLH1 methylation analysis in blood identifies a cancer patient with low-level mosaic MLH1 epimutation

Constitutional MLH1 methylation (epimutation) is a rare cause of Lynch syndrome. Low-level methylation (<= 10%) has occasionally been described. This study aimed to identify low-level constitutional MLH1 epimutations and determine its causal role in patients with MLH1-hypermethylated colorectal cancer. Eighteen patients with MLH1-hypermethylated colorectal tumors in whom MLH1 methylation was previously undetected in blood by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) were screened for MLH1 methylation using highly sensitive MS-melting curve analysis (MS-MCA). Constitutional methylation was characterized by different approaches. MS-MCA identified one patient (5.6%) with low-level MLH1 methylation ( 1%) in blood and other normal tissues, which was confirmed by clonal bisulfite sequencing in blood. The patient had developed three clonally related gastrointestinal MLH1-methylated tumor lesions at 22, 24, and 25 years of age. The methylated region in normal tissues overlapped with that reported for other carriers of constitutional MLH1 epimutations. Low-level MLH1 methylation and reduced allelic expression were linked to the same genetic haplotype, whereas the opposite allele was lost in patient's tumors. Mutation screening of MLH1 and other hereditary cancer genes was negative. Herein, a highly sensitive MS-MCA-based approach has demonstrated its utility for the identification of low-level constitutional MLH1 epigenetic mosaicism. The eventual identification and characterization of additional cases will be critical to ascertain the cancer risks associated with constitutional MLH1 epigenetic mosaicism

Mammographic density and breast cancer in women from high risk families

Introduction: Mammographic density (MD) is one of the strongest determinants of sporadic breast cancer (BC). In this study, we compared MD in BRCA1/2 mutation carriers and non-carriers from BRCA1/2 mutation-positive families and investigated the association between MD and BC among BRCA1/2 mutation carriers per type of mutation and tumor subtype. Methods: The study was carried out in 1039 female members of BRCA1 and BRCA2 mutation-positive families followed at 16 Spanish Genetic Counseling Units. Participants' density was scored retrospectively from available mammograms by a single blinded radiologist using a 5-category scale (75 %). In BC cases, we selected mammograms taken prior to diagnosis or from the contralateral breast, whereas, in non-cases, the last screening mammogram was evaluated. MD distribution in carriers and non-carriers was compared using ordinal logistic models, and the association between MD and BC in BRCA1/2 mutation carriers was studied using logistic regression. Huber-White robust estimators of variance were used to take into account correlations between family members. A similar multinomial model was used to explore this association by BC subtype. Results: We identified and scored mammograms from 341 BRCA1, 350 BRCA2 mutation carriers and 229 non-carriers. Compared to non-carriers, MD was significantly lower among BRCA2 mutation carriers (odds ratio (OR) =0.71; P-value=0.04), but not among BRCA1 carriers (OR=0.84; P-value=0.33). MD was associated with subsequent development BC (OR per category of MD=1.45; 95 % confidence interval=1.18-1.78, P-value<0.001), with no significant differences between BRCA1 and BRCA2 mutation carriers (P-value=0.48). Finally, no statistically significant differences were observed in the association of MD with specific BC subtypes. Conclusions: Our study, the largest to date on this issue, confirms that MD is an independent risk factor for all BC subtypes in either BRCA1 and BRCA2 mutation carriers, and should be considered a phenotype risk marker in this context

Excess mortality among breast cancer patients in early stages in Tarragona and Gerona

Objetivo: analizar la supervivencia poblacional del cáncer de mama (CM) en estadios precoces, estimando la tendencia temporal del exceso de mortalidad (EM) a largo plazo en periodos anuales y quinquenales, y determinando, si es posible, una proporción de pacientes que puedan considerarse curadas. Método: Se incluyó la cohorte de pacientes diagnosticadas de CM en estadios I y II antes de los 60 anos de edad en Gerona y Tarragona (N = 2453). Se calcularon la supervivencia observada (SO) y la supervivencia relativa (SR) al CM hasta los 20 aaños de seguimiento. Para valorar el EM se estimó la SR a intervalos anuales (SRI) y quinquenales (SR5). Los resultados se presentan por grupos de edad (≤49 y 50-59), estadio (I/II) y periodo de diagnóstico (1985-1994 y 1995-2004). Resultados: en el estadio I, la SO y la SR fueron mayores en 1995-2004 que en 1985-1994: 3,5% a los 15 años de seguimiento y 4,5% a los 20 años. La SO superó el 80% en el estadio I y se mantuvo inferior al 70% en el estadio II. Sin embargo, el EM a largo plazo no desapareció (SRI <1) independientemente del grupo de edad, el estadio y el periodo de diagnóstico. A los 15 años de seguimiento, el EM a 5 años osciló entre el 1-5% en el estadio I (SR5 ≥0,95) y el 5-10% en el estadio II. Conclusiones: En nuestra cohorte, a los 15 años de seguimiento se detectó que el EM anual no desapareció y el quinquenal fue del 1-10%. Por ello, no se pudo determinar una proporción de curación del CM durante el periodo de estudio