Predicting outcomes following cognitive behavior therapy in child anxiety disorders: the influence of genetic, demographic and clinical information

Background. Within a therapeutic gene by environment (GxE) framework, we recently demonstrated that variation in the Serotonin Transporter Promoter Polymorphism; 5HTTLPR and marker rs6330 in Nerve Growth Factor gene; NGF is associated with poorer outcomes following cognitive behaviour therapy (CBT) for child anxiety disorders. The aim of this study was to explore one potential means of extending the translational reach of G×E data in a way that may be clinically informative. We describe a ‘risk-index’ approach combining genetic, demographic and clinical data and test its ability to predict diagnostic outcome following CBT in anxious children. Method. DNA and clinical data were collected from 384 children with a primary anxiety disorder undergoing CBT. We tested our risk model in five cross-validation training sets. Results. In predicting treatment outcome, six variables had a minimum mean beta value of 0.5: 5HTTLPR, NGF rs6330, gender, primary anxiety severity, comorbid mood disorder and comorbid externalising disorder. A risk index (range 0-8) constructed from these variables had moderate predictive ability (AUC = .62-.69) in this study. Children scoring high on this index (5-8) were approximately three times as likely to retain their primary anxiety disorder at follow-up as compared to those children scoring 2 or less. Conclusion. Significant genetic, demographic and clinical predictors of outcome following CBT for anxiety-disordered children were identified. Combining these predictors within a risk-index could be used to identify which children are less likely to be diagnosis free following CBT alone or thus require longer or enhanced treatment. The ‘risk-index’ approach represents one means of harnessing the translational potential of G×E data.

Challenges in quantifying wind generation's contribution to securing peak demand

Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.

Random sums of exchangeable variables and actuarial applications

In this paper we study the accumulated claim in some fixed time period, skipping the classical assumption of mutual independence between the variables involved. Two basic models are considered: Model I assumes that any pair of claims are equally correlated which means that the corresponding square-integrable sequence is exchangeable one. Model 2 states that the correlations between the adjacent claims are the same. Recurrence and explicit expressions for the joint probability generating function are derived and the impact of the dependence parameter (correlation coefficient) in both models is examined. The Markov binomial distribution is obtained as a particular case under assumptions of Model 2. (C) 2007 Elsevier B.V. All rights reserved.

Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups

This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.

Risco operacional em tesourarias bancárias

Esta dissertação desenvolve um estudo sobre o risco operacional nas tesourarias bancárias e tem por objetivo elaborar um modelo explicativo do impacto desse fenômeno no resultado da tesouraria. O estudo inicia com uma pesquisa dos modelos de firma bancária presentes na literatura especializada, visando conhecer o estado da arte da modelagem desse tipo de organização. Em seguida, é caracterizada a tesouraria bancária, com o objetivo de identificar seu papel e importância para a organização bancária. Na seqüência, o trabalho apresenta o conceito geral de risco e a classificação utilizada pela indústria financeira e também disserta sobre o risco operacional e sua importância para o gerenciamento dos bancos. Ao final do estudo, é desenvolvido o modelo de risco operacional em tesouraria e demonstrada sua influência no resultado final da tesouraria. Como conclusão geral, verifica-se que maiores probabilidades de ocorrência de falhas operacionais estão associadas a menor eficiência da tesouraria, com conseqüente impacto negativo no resultado.

Câncer de boca e orofaringe: tendências e análise de sobrevida em Natal (RN)

Introduction: Mouth cancer is classified as having one of the ten highest cancer incidences in the world. In Brazil, the incidence and mortality rates of oral cancer are among the highest in the world. Intraoral cancer (tongue, gum, floor of the mouth, and other non-specified parts of the mouth), the accumulated survival rate after five years is less than 50%. Objectives: Estimate the accumulated survival probability after five years and adjust the Cox regression model for mouth and oropharyngeal cancers, according to age range, sex, morphology, and location, for the city of Natal. Describe the mortality and incidence coefficients of oral and oropharyngeal cancer and their tendencies in the city of Natal, between 1980 and 2001 and between 1997 and 2001, respectively. Methods: Survival data of patients registered between 1997 and 2001 was obtained from the Population-based Cancer Record of Natal. Differences between the survival curves were tested using the log-rank test. The Cox proportional risk model was used to estimate risk ratios. The simple linear regression model was used for tendency analyses of the mortality and incidence coefficients. Results: The probability after five years was 22.9%. The patients with undifferentiated malignant neoplasia were 4.7 times more at risk of dying than those with epidermoid carcinoma, whereas the patients with oropharyngeal cancer had 2.0 times more at risk of dying than those with mouth cancer. The mouth cancer mortality and incidence coefficients for Natal were 4.3 and 2.9 per 100 000 inhabitants, respectively. The oropharyngeal cancer mortality and incidence coefficients were, respectively, 1.1 and 0.7 per 100 000 87 inhabitants. Conclusions: A low survival rate after five years was identified. Patients with oropharyngeal cancer had a greater risk of dying, independent of the factors considered in this study. Also independent of other factors, undifferentiated malignant neoplasia posed a greater risk of death. The magnitudes of the incidence coefficients found are not considered elevated, whereas the magnitudes of the mortality coefficients are high

Recidiva de câncer labial em pacientes atendidos no hospital DR. Luiz Antônio (Natal-RN) entre 1997-2004

Introduction: Cancer of the lip is very common in tropical countries, being noticeable the squamous cell carcinoma as the main histological type. Objective: Evaluate the socialdemographic profile, habits, occupation, clinical characteristics of the cancer lesions and the aftermath of treatment of the patients treated on the Luiz Antônio Hospital (Natal-RN). Design: Retrospective cohort. Methods: We analyzed 181 medical records of patients from the Luiz Antônio Cancer Hospital (Natal-RN) in the period between 1997 and 2004. The statistic evaluation of time between the diagnosis and the relapse or the cure of the patient were done through the Kaplan-Meier method and the comparison of survivor functions were done through the Log-rank test. Later, was estimated the proportional risk model of Cox. Results: The study population were composed by 69,1% males, 95,2% unlettered, the mean age of 66,5 years, 89,0% of smokers and 64,1% had an occupation involving sun exposure. In regard to the clinical characteristics, most lesions were in the lower lip (77,9%), the size of the tumor was smaller than 2 cm (51,8%), 92,6% had localized lesions. Were verified 16,3% of local relapse and 13% of regional. Almost the totally of the cases corresponded to squamous cell carcinoma (97,2%). We observed smaller accumulated probability of not occurrence of local relapse when the base and borders were free of lesions (p=0,041), as well as a smaller probability of regional relapse when the sort of treatment was surgery, associated with other therapeutics modalities (p=0,001). The patients with advanced pathologic stage (p=0,016), treated with surgery associated with other therapeutics modalities (p=0,001) and diameter above 4cm (p=0,019) presented a bigger possibility of any kind of relapse. The multivariable analysis pointed the complex treatments (surgery plus other therapeutics modalities) as a predictor variable for occurrence of new local lesions (p=0,001) and total (p=0,046), besides the age above 70 years to the regional relapse (p=0,050). Conclusion: Cancer of the lip occur in the lower lip, in males, smokers and individuals exposed to Sun light. The relapse was frequent, even being localized and without great consequences to the patient s health. The probability of relapse is related to the size and borders of the lesion and to the histological exam, as well as to the patient s age and complexity of the treatment chosen

A teoria da ruína aplicada em um modelo de empresa financeira com risco de crédito

In this work we study a new risk model for a firm which is sensitive to its credit quality, proposed by Yang(2003): Are obtained recursive equations for finite time ruin probability and distribution of ruin time and Volterra type integral equation systems for ultimate ruin probability, severity of ruin and distribution of surplus before and after ruin

Modelo de risco controlado por resseguro e desigualdades para a probabilidade de ruína

In the work reported here we present theoretical and numerical results about a Risk Model with Interest Rate and Proportional Reinsurance based on the article Inequalities for the ruin probability in a controlled discrete-time risk process by Ros ario Romera and Maikol Diasparra (see [5]). Recursive and integral equations as well as upper bounds for the Ruin Probability are given considering three di erent approaches, namely, classical Lundberg inequality, Inductive approach and Martingale approach. Density estimation techniques (non-parametrics) are used to derive upper bounds for the Ruin Probability and the algorithms used in the simulation are presented

Modelo de risco com dependência entre os valores das indenizações e seus intervalos entre ocorrências

We present a dependent risk model to describe the surplus of an insurance portfolio, based on the article "A ruin model with dependence between claim sizes and claim intervals"(Albrecher and Boxma [1]). An exact expression for the Laplace transform of the survival function of the surplus is derived. The results obtained are illustrated by several numerical examples and the case when we ignore the dependence structure present in the model is investigated. For the phase type claim sizes, we study by the survival probability, considering this is a class of distributions computationally tractable and more general

Specialist tool for monitoring the measurement degradation process of induction active energy meters

This paper presents a methodology and a specialist tool for failure probability analysis of induction type watt-hour meters, considering the main variables related to their measurement degradation processes. The database of the metering park of a distribution company, named Elektro Electricity and Services Co., was used for determining the most relevant variables and to feed the data in the software. The modeling developed to calculate the watt-hour meters probability of failure was implemented in a tool through a user friendly platform, written in Delphi language. Among the main features of this tool are: analysis of probability of failure by risk range; geographical localization of the meters in the metering park, and automatic sampling of induction type watt-hour meters, based on a risk classification expert system, in order to obtain information to aid the management of these meters. The main goals of the specialist tool are following and managing the measurement degradation, maintenance and replacement processes for induction watt-hour meters. © 2011 IEEE.

Risco de crédito: uma abordagem utilizando análise discriminante, regressão logística e redes neurais artificiais

Considering the relevance of researches concerning credit risk, model diversity and the existent indicators, this thesis aimed at verifying if the Fleuriet Model contributes in discriminating Brazilian open capital companies in the analysis of credit concession. We specifically intended to i) identify the economic-financial indicators used in credit risk models; ii) identify which economic-financial indicators best discriminate companies in the analysis of credit concession; iii) assess which techniques used (discriminant analysis, logistic regression and neural networks) present the best accuracy to predict company bankruptcy. To do this, the theoretical background approached the concepts of financial analysis, which introduced themes relative to the company evaluation process; considerations on credit, risk and analysis; Fleuriet Model and its indicators, and, finally, presented the techniques for credit analysis based on discriminant analysis, logistic regression and artificial neural networks. Methodologically, the research was defined as quantitative, regarding its nature, and explanatory, regarding its type. It was developed using data derived from bibliographic and document analysis. The financial demonstrations were collected by means of the Economática ® and the BM$FBOVESPA website. The sample was comprised of 121 companies, being those 70 solvents and 51 insolvents from various sectors. In the analyses, we used 22 indicators of the Traditional Model and 13 of the Fleuriet Model, totalizing 35 indicators. The economic-financial indicators which were a part of, at least, one of the three final models were: X1 (Working Capital over Assets), X3 (NCG over Assets), X4 (NCG over Net Revenue), X8 (Type of Financial Structure), X9 (Net Thermometer), X16 (Net Equity divided by the total demandable), X17 (Asset Turnover), X20 (Net Equity Profitability), X25 (Net Margin), X28 (Debt Composition) and X31 (Net Equity over Asset). The final models presented setting values of: 90.9% (discriminant analysis); 90.9% (logistic regression) and 97.8% (neural networks). The modeling in neural networks presented higher accuracy, which was confirmed by the ROC curve. In conclusion, the indicators of the Fleuriet Model presented relevant results for the research of credit risk, especially if modeled by neural networks.

CHARACTERIZATION OF THE BRAZPD II COHORT AND DESCRIPTION OF TRENDS IN PERITONEAL DIALYSIS OUTCOME ACROSS TIME PERIODS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Peritoneal dialysis in acute kidney injury: trends in the outcome across time periods

Peritoneal dialysis (PD) should be considered a suitable method of renal replacement therapy in acute kidney injury (AKI) patients. This study is the largest cohort providing patient characteristics, clinical practice, patterns and their relationship to outcomes in a developing country. Its objective was to describe the main determinants of patient and technique survival, including trends over time of PD treatment in AKI patients. This was a Brazilian prospective cohort study in which all adult AKI patients on PD were studied from January/2004 to January/2014. For comparison purposes, patients were divided into 2 groups according to the year of treatment: 2004-2008 and 2009-2014. Patient survival and technique failure (TF) were analyzed using the competing risk model of Fine and Gray. A total of 301 patients were included, 51 were transferred to hemodialysis (16.9%) during the study period. The main cause of TF was mechanical complication (47%) followed by peritonitis (41.2%). There was change in TF during the study period: compared to 2004-2008, patients treated at 2009-2014 had relative risk (RR) reduction of 0.86 (95% CI 0.77-0.96) and three independent risk factors were identified: period of treatment at 2009 and 2014, sepsis and age>65 years. There were 180 deaths (59.8%) during the study. Death was the leading cause of dropout (77.9% of all cases) mainly by sepsis (58.3%), followed cardiovascular disease (36.1%). The overall patient survival was 41% at 30 days. Patient survival improved along study periods: compared to 2004-2008, patients treated at 2009-2014 had a RR reduction of 0.87 (95% CI 0.79-0.98). The independent risk factors for mortality were sepsis, age>70 years, ATN-ISS > 0.65 and positive fluid balance. As conclusion, we observed an improvement in patient survival and TF along the years even after correction for several confounders and using a competing risk approach.

Modeling Age-Specific Mortality For Marine Mammal Populations

A method is presented for estimating age-specific mortality based on minimal information: a model life table and an estimate of longevity. This approach uses expected patterns of mammalian survivorship to define a general model of age-specific mortality rates. One such model life table is based on data for northern fur seals (Callorhinus ursinus) using Siler’s (1979) 5-parameter competing risk model. Alternative model life tables are based on historical data for human females and on a published model for Old World monkeys. Survival rates for a marine mammal species are then calculated by scaling these models by the longevity of that species. By using a realistic model (instead of assuming constant mortality), one can see more easily the real biological limits to population growth. The mortality estimation procedure is illustrated with examples of spotted dolphins (Stenella attenuata) and harbor porpoise (Phocoena phocoena).