Made available in DSpace on 2016-05-11T12:52:25Z (GMT). No. of bitstreams: 2 173.pdf: 1393850 bytes, checksum: f42a39478517a9d553079202299ea4eb (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2014 / Introducción: La introducción de la Terapia Antirretroviral de Gran Actividad (TARGA), ha reducido la morbi-mortalidad de los pacientes con VIH/SIDA tratados, yla mejora en su calidad de vida, debido al control de la replicación viral del VIH y a lamejoría del sistema inmune, conllevando a la disminución de las infecciones oportunistas.La TARGA busca conseguir la supresión virológica del VIH, que sólo se consigue entreun 57 por cento a 78 por cento de los pacientes en TARGA. La identificación de factores asociados a falla virológica puede tener implicaciones para el tratamiento de los pacientes con antirretrovirales. Metodología: Se trata de un estudio retrospectivo de 98 pacientes nuevos que iniciaron esquema de antirretrovirales de primera línea entre Mayo del 2004a Julio del 2005 en el Programa TARGA del Hospital Nacional Hipólito Unanue ubicadoen Lima Este, Lima-Perú y que desarrollaron falla virológica. El modelo de riesgos proporcionales de Cox fue utilizado para identificar los factores asociados a fallavirológica. Resultados: De 98 pacientes en TARGA, 67.3 por cento eran varones con edad media de 35.65 años. El 94 por cento recibió AZT ó D4T +3TC+NNTR. Se encontró que el 13.2 por cento desarrollaron falla virológica. La variable régimen inicial de TARGA tuvo un nivel designificación estadística limítrofe, relacionado a la falla virológica, en el análisis multivariado de Cox. Los pacientes con el régimen inicial de DDI+3TC+NNTR (DDIfue usada en vez de AZT), tuvieron un incremento de riesgo de 7 veces mayor (HR: 7.0IC95 por cento 0.93-49.6) de desarrollar falla virológica. (AU)^ies / Introduction: The introduction of Highly Active Antiretroviral Therapy (HAART) has reduced morbidity and mortality of patients with HIV / AIDS treated, and improving their quality of life, due to the control of HIV viral replication and improvement of the immune system, leading to decreased opportunistic infections. HAART therapy seeks to achieve virologic suppression of HIV that is only achieved between 57 percent to 78 percent of patients with antirretroviral therapy. The identification of factors associated with virologic failure may have implications for the treatment of patients with antiretrovirals. Methodology: This isa retrospective study of 98 new HIV patients which starting antiretroviral therapy between May 2004 to July 2005 in the HAART Program Hipólito Unanue National Hospital in Lima East, Lima-Peru and who developed virologic failure. The proportional hazards model of Cox was used to study all factors associated with virologic failure. Results: Of 98 patients on HAART, 67.3 percent were male with mean age of 35.65 years. 94 percent received AZT ó D4T +3TC+NNTR We found that 13.2 percent developed virologic failure. The variable HAART regimen had a borderline level of statistical significance related a virologic failure, patients with initial regimen with DDI + 3TC + NNTR (DDI was useinstead of AZT), were increased 7-fold greater risk (HR: 7.0 95 percent CI 0.93-49.6) todevelop virologic failure. (AU)^ien

This work introduces nonparametric models which are used in time to event data analysis. It is focused on applying these methods in medicine where it is called survival analysis. The basic techniques and problems, which can appear in survival analysis, are presented and explained here. The Kaplan -- Meier estimator of survival function is discussed in the main part. This is the most frequented method used for estimating the survival function in patients who have undergone a specific treatment. The Kaplan -- Meier estimator is also a common device in the statistical packets. In addition to estimation of survival function, the estimation of hazard function and cumulative hazard function is presented. The hazard function shows the intensity of an individual experiencing the particular event in a short time period. Special problems occur when analyzing time to event data. A distinctive feature, often present in such data, is known as censoring. That is the situation when the individual does not experience the event of interest at the time of study. The thesis covers also an empiric part, where the results of an analysis of patients with the larynx carcinoma diagnosis are shown. These patients were treated in a hospital located in České Budějovice. This analysis is based on a theory presented in the previous chapters.

Survival analysis is a statistical discipline that analyzes the time to occurrence of certain events. The aim of this thesis is to describe the possibilities of survival analysis in the environment of statistical software R. Theoretical knowledge is applied to real data, parametric and nonparametric estimates of survival functions are evaluated by different methods and compared with each other. In the section focusing on nonparametric models Kaplan-Meier and Nelson-Aalen functions are described. Among the parametric estimates there were included well-known probability distributions, survival functions and risk functions derived from these distributions are presented and there is discussed their usefulness in survival analysis. Another aim is to show the possibility of deriving transition probabilities from estimates and building a Markov chain model to capture the changes of studied cohort over time. The second part of the work contains a description of the applications of the theory of survival analysis. In this section there are shown possibilities of statistical modeling in the field of survival analysis using the software R. Outputs from R were used to create Markov model. There are presented possibilities of pharmacoeconomic models and description of the basic concepts of HTA. Cost-effectiveness calculations using ICER were conducted in accordance with the methodology of SUKL. It was shown that the statistical modelling of survival plays an important role in the evaluation of the cost-effectiveness of medicines.

Tato práce popisuje a aplikuje parametrické a neparametrické modely spolehlivosti na cenzorovaná data. Ukazuje implementaci spolehlivosti v metodologii Six Sigma. Metody jsou využity pro přežití/spolehlivost reálných technických dat.

The mechanisms that control growth processes in biology tissues have attracted continuous research interest despite their complexity. With the emergence of big data experimental approaches there is an urgent need to develop statistical and computational models to fit the experimental data and that can be used to make predictions to guide future research. In this work we apply statistical methods on growth process of different biological tissues, focusing on development of neuron dendrites and tumor cells. We first examine the neuron cell growth process, which has implications in neural tissue regenerations, by using a computational model with uniform branching probability and a maximum overall length constraint. One crucial outcome is that we can relate the parameter fits from our model to real data from our experimental collaborators, in order to examine the usefulness of our model under different biological conditions. Our methods can now directly compare branching probabilities of different experimental conditions and provide confidence intervals for these population-level measures. In addition, we have obtained analytical results that show that the underlying probability distribution for this process follows a geometrical progression increase at nearby distances and an approximately geometrical series decrease for far away regions, which can be used to estimate the spatial location of the maximum of the probability distribution. This result is important, since we would expect maximum number of dendrites in this region; this estimate is related to the probability of success for finding a neural target at that distance during a blind search. We then examined tumor growth processes which have similar evolutional evolution in the sense that they have an initial rapid growth that eventually becomes limited by the resource constraint. For the tumor cells evolution, we found an exponential growth model best describes the experimental data, based on the accuracy and robustness of models. Furthermore, we incorporated this growth rate model into logistic regression models that predict the growth rate of each patient with biomarkers; this formulation can be very useful for clinical trials. Overall, this study aimed to assess the molecular and clinic pathological determinants of breast cancer (BC) growth rate in vivo.

[pt] Esta dissertação tem como objetivo propor uma abordagem pouco utilizada na área financeira para prever cancelamentos em planos de previdência privada. Métodos e modelos provenientes da análise de sobrevivência foram utilizados para prever o cancelamento, além de estimar o risco associado de o cliente cancelar. Os modelos propostos, modelo de regressão paramétrico e modelo de riscos proporcionais de Cox, foram estimados utilizando-se uma base de dados de clientes acompanhados durante um período de 6 anos e meio de uma seguradora nacional. Os modelos mostraram-se equivalentes, tendo capacidade de generalização de 58 por cento. / [en] This paper aims to propose an approach rarely used in finance to predict cancellations in private pension plans. Methods and models from survival analysiswere used to predict the cancellation and estimate the risk associated with the cliente cancellation. The proposed models, regression model and parametric proportional hazards model of Cox, were estimated using a database of customers followed for a period of 6 and a half years of a national insurer. The models showed equivalence and generalizability of 58 per cent.

Submitted by PPG Economia do desenvolvimento (economia-pg@pucrs.br) on 2017-12-19T18:30:22Z No. of bitstreams: 1 CARLOS_HERNAN_RODAS_CESPEDES_TES.pdf: 1347334 bytes, checksum: 034f22126306c06c90f7f135fc0970f5 (MD5) / Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-12-26T16:25:24Z (GMT) No. of bitstreams: 1 CARLOS_HERNAN_RODAS_CESPEDES_TES.pdf: 1347334 bytes, checksum: 034f22126306c06c90f7f135fc0970f5 (MD5) / Made available in DSpace on 2017-12-26T16:31:46Z (GMT). No. of bitstreams: 1 CARLOS_HERNAN_RODAS_CESPEDES_TES.pdf: 1347334 bytes, checksum: 034f22126306c06c90f7f135fc0970f5 (MD5) Previous issue date: 2017-12-01 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / (Ensaio I) This study investigates the demographics of companies at Rio Grande do Sul State from 2006 to 2013. First, the birth, mortality and turnover of companies are quantified, as well as their survival over time. Then, these demographic events are analyzed by size, economic activity, and geographic location. For this purpose, an identified database is used, which allows the longitudinal monitoring of all formal companies existing in Rio Grande do Sul over the period under study. (Ensaio II) This paper proposes an empirical research on the survival of the companies of Rio Grande do Sul State for the period 2007-2013. The Kaplan-Meier procedure is applied to obtain the functions of survival of the companies, according to the geographic location, the economic activity and the size. Then, the Cox procedure is applied, in order to determine the effect of the size of the companies on the survival time. The results obtained show that survival is relatively higher: in the companies with the largest number of employed persons; in the manufacturing industry and financial activities; and located in the Northeast region of Rio Grande do Sul state. (Ensaio III) The objective of this paper is to analyze the birth of companies in the counties of Rio Grande do Sul State between 2007 and 2013. For this, exploratory analysis of spatial data and the panel data regression are used. The results indicated the existence of spatial autocorrelation of the birth of companies and the formation of some clusters of the counties with high births of companies. The spatial auto regression (SAR) model evidenced the spillover effect of the birth of companies and made it possible to measure the direct and indirect impacts of the independent variables on the birth of companies. / (Ensaio I) Este estudo investiga a demografia de empresas do Rio Grande do Sul no per?odo de 2006 a 2013. Primeiro ? quantificado o nascimento, a mortalidade e a rotatividade de empresas, al?m da sobreviv?ncia delas ao longo do tempo. Depois, esses eventos demogr?ficos s?o analisados segundo o tamanho, o setor e a localiza??o geogr?fica das empresas. Para tanto, utiliza-se uma base de dados identificada, que possibilita o acompanhamento longitudinal de todas as empresas formais existentes no Rio Grande do Sul ao longo do per?odo em estudo. (Ensaio II) Este trabalho prop?e uma pesquisa emp?rica sobre a sobreviv?ncia das empresas do Rio Grande do Sul para o per?odo 2007-2013. ? aplicado o procedimento de Kaplan-Meier para obter as fun??es de sobreviv?ncia das empresas, conforme o local, a atividade econ?mica e o tamanho. Da mesma forma, aplica-se o procedimento de Cox, com a finalidade de determinar o efeito do tamanho das empresas sobre o tempo de sobreviv?ncia. Os resultados obtidos mostram que a sobreviv?ncia ? relativamente maior: nas empresas com maior numero de pessoas ocupadas; no setor da ind?stria de transforma??o e atividades financeiras; e localizadas na regi?o Nordeste do Rio Grande do Sul. (Ensaio III) O objetivo deste ensaio ? analisar o nascimento de empresas nos munic?pios do Rio Grande do Sul no per?odo entre 2007 e 2013. Para isso, utilizam-se procedimentos da an?lise explorat?ria de dados espaciais e regress?o em painel espacial. Os resultados indicaram a exist?ncia de autocorrela??o espacial do nascimento de empresas e a forma??o de alguns clusters de munic?pios com altos nascimentos de empresas. O modelo de autorregress?o espacial (SAR) evidenciou o efeito transbordamento do nascimento de empresas e possibilitou a mensura??o dos impactos diretos e indiretos das vari?veis independentes sobre o nascimento de empresas.

Many breast cancer diagnoses and second cancers are associated with BRCA gene mutations. Early detection of cancer is necessary to improve health outcomes, particularly with second cancers. Little is known about the influence of risk factors on time to diagnosis of second primary cancers after diagnosis with BRCA-related breast cancer. The purpose of this cohort study was to examine the risk of diagnosis of second primary cancers among women diagnosed with breast cancer after adjusting for BRCA status, age, and ethnicity. The study was guided by the empirical evidence supporting the mechanism of action in the mutation of BRCA leading to the development of cancer. Composite endpoint was used to define second primary cancer occurrences, and Kaplan-Meier survival curves were used to compare the median time-to-event among comparison groups and BRCA gene mutation status. Cox proportional hazards was used to examine the relationships between age at diagnosis, ethnicity, BRCA gene mutation status, and diagnosis of a second primary cancer. The overall median time to event for diagnosis of second primary cancers was 14 years. The hazard ratios for BRCA2 = 1.47, 95% CI [1.03 - 2.11], White = 1.511, 95% CI [1.18 - 1.94], and American Indian/Hawaiian = 1.424, 95% CI [1.12 -1.81] showing positive significant associations between BRCA2 mutation status and risk of diagnosis of second primary colorectal, endometrial, cervical, kidney, thyroid, and bladder cancers. Data on risk factors for development of second cancers would allow for identification of appropriate and timely screening procedures, determining the best course of action for prevention and treatment, and improving quality of life among breast cancer survivors.

Health problems of the human beings in a society are one of the main components of the social security systems due to the dimension of the financial burden it might bring on individuals, employers, insurance companies and governments. Morbidity measures, such as incidence and prevalence of a specific disease in a certain population enable researchers to estimate for individuals the probability of being diagnosed or being prone to the diseases. This information is usually not tractable because of the non-availability of the convenient data or recordings for many countries as well as Turkey. Even if it is available, it is commonly limited with largely varying characteristics about the type and coverage of the diseases. In this regard, the pattern that a population follows for an acute disease may not be the same for chronic diseases. Having those indicators determined for a group of insureds will enable underwriters to have more profitable and economical premium calculation and precision on required reserve estimation. v Based on their characteristics such as acute or chronic behaviour, the gender, and the location of residency of people, the diseases show different behaviour on their occurrences. From the insurer

Les aliments peuvent être contaminés par certaines substances chimiques, qui, lorsqu'elles sont ingérées à des doses trop importantes, peuvent engendrer des problèmes de santé. Notre but est d'évaluer la probabilité que l'exposition au contaminant dépasse durablement une dose tolérable par l'organisme que nous appelons risque. La modélisation de la queue de distribution par des lois extrêmes permet de quantifier un risque très faible. Dans les autres cas, l'estimateur empirique du risque s'écrit comme une U-statistique généralisée, ce qui permet d'en dériver les propriétés asymptotiques. Des développements statistiques permettent d'intégrer à ce modèle la censure des données de contamination. Enfin, un modèle économétrique de décomposition de données ménage en données individuelles nous permet de proposer une nouvelle méthode de quantification du risque de long terme prenant en compte l'accumulation du contaminant et sa lente dégradation par l'organisme.