Submitted by AGDA JESSICA DE FREITAS GALLETTI null (aj.mat@hotmail.com) on 2018-03-23T18:26:29Z No. of bitstreams: 1 Dissertacao Agda.pdf: 8703134 bytes, checksum: 38fab95cf6a37646cb9076182d7acefe (MD5) / Approved for entry into archive by Luciana Pizzani null (luciana@btu.unesp.br) on 2018-03-26T17:31:07Z (GMT) No. of bitstreams: 1 galletti_ajf_me_bot.pdf: 8692893 bytes, checksum: 24ce44d5b41a0465faf8c7d5f279a7bb (MD5) / Made available in DSpace on 2018-03-26T17:31:07Z (GMT). No. of bitstreams: 1 galletti_ajf_me_bot.pdf: 8692893 bytes, checksum: 24ce44d5b41a0465faf8c7d5f279a7bb (MD5) Previous issue date: 2018-02-23 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A cirrose é uma doença hepática assintomática que, muitas vezes, é descoberta quando o quadro é irreversível. Por isso, o tratamento consiste em uma série de medidas para controlar o avanço da enfermidade, visto que a principal consequência da cirrose é o aumento da pressão na veia portal, que por sua vez, acarreta no surgimento de varizes e no seu respectivo rompimento, podendo ser fatal. Estudos relacionados à esta doença são muito importantes, pois a análise estatística é uma ferramenta que permite auxiliar na tomada de decisões nos procedimentos médicos e acompanhamento de pacientes. Um método estatístico bastante explorado nas ciências biomédicas é a análise de sobrevivência, que consiste em descrever o tempo de um evento inicial até a ocorrência de um outro de interesse. No entanto, existem situações em que uma proporção da amostra não vivencia o desfecho de interesse, mesmo que acompanhado por um período longo de tempo. Nestes casos, tais observações são dita imunes ao desfecho de interesse e as metodologias tradicionais de análise de sobrevivência não são indicadas. Logo, os modelos de fração de cura ou de longa duração, desenvolvido a partir do modelo de mistura, são os utilizados nestas situações. Neste trabalho diverso modelos foram considerados para analisar os tempos de vida de pacientes submetidos à Ligadura Elástica de Varizes Esofágicas, ao qual foram anotados os tempos até o óbito durante o acompanhamento de 129 pacientes do Hospital das Clínicas da Faculdade de Medicina da UNESP, Campus Botucatu (SP), no período de 2006 a 2010. O modelo Weibull Modificado com fração de cura foi considerado adequado, indicando que quanto maior a idade e o grau da doença hepática, se os pacientes não usam o medicamento Beta-Bloqueador e são homens, menor é a chance deles serem sobreviventes de longa duração. / Cirrhosis is an asymptomatic liver disease that is often discovered when the patient's condition is irreversible. Therefore, the treatment consists of a series of measures to control the progression of the disease, since the main consequence of the cirrhosis is the increase of the portal venous pressure, which causes the appearance of varices and their respective rupture may be fatal. Studies related to that disease are very important, so the statistical analysis is a tool that helps to make decisions in medical procedures and patient follow-up. The most applied statistical method in the biomedical sciences is survival analysis, which consists of describing the time of occurrence until the event of interest. However, there are situations in which a proportion of the sample does not experience the interest outcome, even if they are accompanied by a long period of time. In such cases, such observations are said to be immune to the outcome of interest and traditional survival analysis methodologies are not appropriated. Therefore, the care fraction or long duration models can be used in these situations because they incorporate mixtures of models to solve the complexity inherent in the actual study. In this work, some statistical models were considered to analyze the survival times of patients, after surgery of Endoscopic Band Ligation of the Esophageal Varices, such as Exponential, Gamma and Weibull models. The data is related to survival times of 129 patients, who were treated in the Hospital das Clínicas of the Medical School of UNESP, Campus Botucatu (SP), from 2006 to 2010. The Modi ed Weibull distribution with cure rate was considered adequate to the data, indicating that older male patients with higher Child-Pugh score without taking beta blockers medicine are more likely not to be a long-term survivor.

Made available in DSpace on 2015-03-03T15:28:33Z (GMT). No. of bitstreams: 1 HericaPAC_DISSERT.pdf: 752483 bytes, checksum: c4526cc225ac72a39965ad5818e0e718 (MD5) Previous issue date: 2012-08-14 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Survival models deals with the modeling of time to event data. However in some situations part of the population may be no longer subject to the event. Models that take this fact into account are called cure rate models. There are few studies about hypothesis tests in cure rate models. Recently a new test statistic, the gradient statistic, has been proposed. It shares the same asymptotic properties with the classic large sample tests, the likelihood ratio, score and Wald tests. Some simulation studies have been carried out to explore the behavior of the gradient statistic in fi nite samples and compare it with the classic statistics in diff erent models. The main objective of this work is to study and compare the performance of gradient test and likelihood ratio test in cure rate models. We first describe the models and present the main asymptotic properties of the tests. We perform a simulation study based on the promotion time model with Weibull distribution to assess the performance of the tests in finite samples. An application is presented to illustrate the studied concepts / Modelos de sobreviv?ncia tratam do estudo do tempo at? a ocorr?ncia de um evento. Contudo em algumas situa??es, uma propor??o da popula??o pode n?o estar mais sujeita a ocorr?ncia deste evento. Modelos que tratam desta abordagem s?o chamados de modelos de fra??o de cura. Existem poucos estudos na literatura sobre testes de hip?teses aplicados a modelos de fra??o de cura. Recentemente foi proposta uma nova estat?stica de teste, denominada estat?stica gradiente que possui distribui??o assint?tica equivalente a das estat?sticas usuais. Alguns estudos de simula??o v?m sendo desenvolvidos no sentido de explorar caracter?sticas dessa nova estat?stica e comparar com as estat?sticas cl?ssicas, aplicadas a diferentes modelos. Este trabalho tem como principal objetivo estudar e comparar o desempenho do teste gradiente e do teste da raz?o de verossimilhan?as, em modelos de fra??o de cura. Para isso descrevemos caracter?sticas do modelo e apresentamos os principais resultados assint?ticos dos testes. Consideramos um estudo de simula??o com base no modelo de tempo de promo??o com distribui??o Weibull, para avaliar o desempenho dos testes em amostras finitas. Uma aplica??o e realizada para ilustrar os conceitos estudados

Made available in DSpace on 2014-12-17T15:26:36Z (GMT). No. of bitstreams: 1 RafaelRL.pdf: 358856 bytes, checksum: bdbb6f9276930942314a39decee73909 (MD5) Previous issue date: 2008-08-11 / In this work, we study the survival cure rate model proposed by Yakovlev et al. (1993), based on a competing risks structure concurring to cause the event of interest, and the approach proposed by Chen et al. (1999), where covariates are introduced to model the risk amount. We focus the measurement error covariates topics, considering the use of corrected score method in order to obtain consistent estimators. A simulation study is done to evaluate the behavior of the estimators obtained by this method for finite samples. The simulation aims to identify not only the impact on the regression coefficients of the covariates measured with error (Mizoi et al. 2007) but also on the coefficients of covariates measured without error. We also verify the adequacy of the piecewise exponential distribution to the cure rate model with measurement error. At the end, model applications involving real data are made / Neste trabalho estudamos o modelo de sobreviv?ncia com fra??o de cura proposto por Yakovlev et al. (1993), fundamentado em uma estrutura de riscos competitivos concorrendo para causar o evento de interese, e a abordagem proposta por Chen et al. (1999), na qual covari?veis s?o introduzidas para modelar o n?mero de riscos. Estudamos o caso em que covari?veis s?o medidas com erro, e para a obten??o de estimadores consistentes consideramos a utiliza??o do m?todo do escore corrigido. Um estudo de simula??o ? realizado para avaliar o comportamento dos estimadores obtidos por este m?todo em amostras finitas. A simula??o visa identificar n?o apenas o impacto sobre os coeficientes de regress?o das covari?veis medidas com erro (Mizoi et al. 2007), mas tamb?m sobre os coeficientes de covari?veis medidas sem erro. Verificamos tamb?m a adequa??o da distribui??o exponencial por partes ao modelo com fra??o de cura e erro de medida. Ao final, s?o feitas aplica??es do modelo envolvendo conjuntos de dados reais

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<p>Recently, the Conway-Maxwell Poisson (COM-Poisson) cure rate model has been proposed which includes as special cases some of the well-known cure rate models discussed in the literature. Data obtained from cancer clinical trials are often right censored and the expectation maximization (EM) algorithm can be efficiently used for the determination of the maximum likelihood estimates (MLEs) of the model parameters based on right censored data.</p> <p>By assuming the lifetime distribution to be exponential, lognormal, Weibull, and gamma, the necessary steps of the EM algorithm are developed for the COM-Poisson cure rate model and some of its special cases. The inferential method is examined by means of an extensive simulation study. Model discrimination within the COM-Poisson family is carried out by likelihood ratio test as well as by information-based criteria. Finally, the proposed method is illustrated with a cutaneous melanoma data on cancer recurrence. As the lifetime distributions considered are not nested, it is not possible to carry out a formal statistical test to determine which among these provides an adequate fit to the data. For this reason, the wider class of generalized gamma distributions is considered which contains all of the above mentioned lifetime distributions as special cases. The steps of the EM algorithm are then developed for this general class of distributions and a simulation study is carried out to evaluate the performance of the proposed estimation method. Model discrimination within the generalized gamma family is carried out by likelihood ratio test and information-based criteria. Finally, for the considered cutaneous melanoma data, the two-way flexibility of the COM-Poisson family and the generalized gamma family is utilized to carry out a two-way model discrimination to select a parsimonious competing cause distribution along with a suitable choice of a lifetime distribution that provides the best fit to the data.</p> / Doctor of Philosophy (PhD)

The purpose of this study was to determine and compare the outcomes of tuberculosis (TB) treatment among Human Immunodeficiency Virus (HIV) co-infected TB patients, and identify factors associated with these outcomes. A quantitative cross-sectional analytic design was used. Patient level secondary data was collected and analysed for the study. A total of 575 TB patients, including 360 non-HIV infected, 169 HIV co-infected and 46 without a documented HIV status, were enrolled. The overall treatment success rate was 91.5%, and HIV co-infected TB patients had a high rate (11.8%) of unfavourable outcomes. The cure rate was significantly lower (10.1% versus 24.2%) and the death rate higher in HIV co-infected patients (8.3% versus 2.5%). Age and TB classification were significantly associated with treatment outcome. No association was found with starting ART, Cotrimoxazole prophylactic treatment or enrolment in HIV care, but 22% of HIV co-infected TB patients were taking ART when they developed TB disease / Health Studies / M.A. (Public Health)

Na literatura da área da análise de sobrevivência existem os modelos tradicionais, ou sem fração de cura, e os modelos de longa duração, ou com fração de cura. Recentemente tem sido proposto um modelo mais geral, conhecido como o modelo com fatores de risco latentes com esquemas de ativação. Nesta tese são deduzidas novas propriedades que possuem a função de sobrevivência, a função de taxa de risco e o valor esperado, quando e considerado o modelo com fatores de risco latentes. Estas propriedades são importantes, já que muitos outros modelos que tem aparecido na literatura recentemente podem ser considerados como casos particulares do modelo com fatores de risco latentes. Além disto, são propostos novos modelos de sobrevivência e estes são aplicados a conjuntos de dados reais. Também é realizado um estudo de simulação e uma análise de sensibilidade, para mostrar a qualidade destes modelos / In the survival literature we can find traditional models without cure fraction and longterm models with cure fraction. A more general risk factor model with latent activation scheme has been recently proposed. In this thesis we deduce new properties for the survival function, hazard function and expected value for this model. Since many recent survival models can be regarded as particular cases of the risk factor model with latent activation scheme these properties are of great relevance. In addition we propose new survival models that are applied to real data examples. A simulation and sensibility analysis are also performed to asses the goodness of fit of these models

Esse trabalho contribui com o desenvolvimento de um novo modelo para dados de sobrevivência com sobreviventes de longo termo visando uma formulação e interpretação mais realista do que a apresentada pelos modelos com fração de curados usuais. Motivados pelo estudo do tempo de sobrevivência residual para pacientes oncológicos, o modelo usa o processo de nascimento e morte para permitir a variação do número de fatores de risco latentes durante um período precedente ao acompanhamento médico, considerando, então, um cenário de riscos competitivos para obtenção da função da sobrevivência (imprópria) dos pacientes. Simulações a aplicações à dados do Instituto do Câncer do Estado de São Paulo mostraram vantagens sobre o modelo de tempos de promoção. / This work contributes with a new cure rate survival model developed aiming more realistic formulation and interpretations than the usual long-term survival models. Motivated by studying residual survival times in oncological patients, the model uses birth and death process to allow free variation on the number of latent risk factors during a pre-follow up period, then considers competing risks scenario for accessing the patients survival. Simulations and application to Instituto do Câncer do Estado de São Paulo data showed improvement over the promotion time model.

Esse trabalho contribui com o desenvolvimento de um novo modelo para dados de sobrevivência com sobreviventes de longo termo visando uma formulação e interpretação mais realista do que a apresentada pelos modelos com fração de curados usuais. Motivados pelo estudo do tempo de sobrevivência residual para pacientes oncológicos, o modelo usa o processo de nascimento e morte para permitir a variação do número de fatores de risco latentes durante um período precedente ao acompanhamento médico, considerando, então, um cenário de riscos competitivos para obtenção da função da sobrevivência (imprópria) dos pacientes. Simulações a aplicações à dados do Instituto do Câncer do Estado de São Paulo mostraram vantagens sobre o modelo de tempos de promoção. / This work contributes with a new cure rate survival model developed aiming more realistic formulation and interpretations than the usual long-term survival models. Motivated by studying residual survival times in oncological patients, the model uses birth and death process to allow free variation on the number of latent risk factors during a pre-follow up period, then considers competing risks scenario for accessing the patients survival. Simulations and application to Instituto do Câncer do Estado de São Paulo data showed improvement over the promotion time model.

The purpose of this study was to determine and compare the outcomes of tuberculosis (TB) treatment among Human Immunodeficiency Virus (HIV) co-infected TB patients, and identify factors associated with these outcomes. A quantitative cross-sectional analytic design was used. Patient level secondary data was collected and analysed for the study. A total of 575 TB patients, including 360 non-HIV infected, 169 HIV co-infected and 46 without a documented HIV status, were enrolled. The overall treatment success rate was 91.5%, and HIV co-infected TB patients had a high rate (11.8%) of unfavourable outcomes. The cure rate was significantly lower (10.1% versus 24.2%) and the death rate higher in HIV co-infected patients (8.3% versus 2.5%). Age and TB classification were significantly associated with treatment outcome. No association was found with starting ART, Cotrimoxazole prophylactic treatment or enrolment in HIV care, but 22% of HIV co-infected TB patients were taking ART when they developed TB disease / Health Studies / M.A. (Public Health)