Introdução: O adenocarcinoma ampular é uma neoplasia maligna rara, com frequência de 1% em relação a todos os tumores gastrintestinais e, de 6 a 25% dos casos de neoplasias periampulares. Como distintos epitélios convalescem dentro da ampola de Vater, a origem histológica desses tumores ainda é uma questão desafiadora na prática clínica. As diferenças nas classificações histomorfológicas tornam difícil a avaliação e comparação dos estudos clínicos desses tumores. Por isso, a divisão histológica em dois tipos principais (intestinal e pancreatobiliar) é necessária para comparação terapêutica e prognóstica desta neoplasia. Materiais e métodos: No presente estudo foram incluídos 27 pacientes no período de 2007 a 2013 com diagnóstico de Adenocarcinoma Ampular no HCFMRP-USP. Foi realizada a avaliação histológica e imuno-histoquímica com os anticorpos CK7, CK20, CDX2, MUC1, MUC2, MUC5AC e, em seguida, avaliado a sobrevida global. Resultados: A média de sobrevida global foi de 40,26 meses. 63% eram carcinomas do tipo intestinal e 37% eram do tipo pancreatobiliar. A expressão dos marcadores CK20, MUC 2 e CDX 2 foram mais frequentes nos tumores do tipo intestinal, já os marcadores CK7, MUC 1 e MUC5AC foram expressos com maior frequência no tipo pancreatobiliar. O CDX2 é o marcador com maior sensibilidade e especificidade para o tipo intestinal quando usado de forma isolada (p<0,01). A associação de CK7 e MUC1 apresentou alta sensibilidade (80%) para o subtipo pancreatobiliar, enquanto as associações CK20 e CDX2 ou MUC2 e CDX2 apresentavam especificidade de 100% para o subtipo intestinal. A média global de sobrevida foi de 40,26 meses. Não houve interferência do tipo histológico (p=0,48), estadiamento (p=0,90) ou realização de quimioterapia (p=0.30) na sobrevida global. Conclusão: O presente estudo propõe que a utilização de um painel imuno-histoquímica composto por CDX2, CK7 e MUC1 permite a classificação com maior acurácia dos adenocarcinomas ampulares em tipo intestinal ou pancreatobiliar. Não foi possível afirmar que a realização de quimioterapia, o estadiamento patológico ou o perfil histopatológico influenciou na sobrevida global, porém o grande impacto deste estudo foi a possibilidade de classificar, a partir de um painel imuno-histoquímico reduzido, os dois subtipos histológicos usuais dos adenocarcinoma ampulares e com isso estabelecer um protocolo para direcionar melhor os pacientes. / Background: Ampullary carcinoma is a rare malignant neoplasm, with a frequency of 1% of all gastrointestinal tumors and represents 6 to 25% of the cases of periampullary neoplasms. As distinct epithelia convalesce within the ampulla of Vater, the histological origin of these tumors is still a challenging question in clinical practice. Differences in histomorphological classifications make difficult to evaluate and compare the clinical trials of these tumors. Therefore, the histological division into two main types (intestinal and pancreatobiliary) is necessary for therapeutic and prognostic comparison of this cancer. Methods: 27 patients were included between 2007 and 2013 with diagnosis of ampullary carcinoma from HCFMRP-USP. Histological and immunohistochemical evaluation was performed with the antibodies CK7, CK20, CDX2, MUC1, MUC2, MUC5AC and then was evaluated the overall survival. Results: The overall survival rate was 40.26 months. Sixty three percent were intestinal type carcinomas and 37% were pancreatobiliary type. Expression of the CK20, MUC 2 and CDX 2 were more frequent in intestinal tumors, whereas the CK7, MUC 1 and MUC5AC markers were expressed more frequently in the pancreatobiliary type. The immunostaining of CDX2 presented highest sensitivity and specificity for the intestinal type when used alone (p <0.01). The association of CK7 and MUC1 showed high sensitivity (80%) for the pancreatobiliary type, while CK20 and CDX2 or MUC2 and CDX2 associations had 100% specificity for the intestinal type. The overall survival rate was 40.26 months. There was no significative relation of histological type (p = 0.48), staging (p = 0.90) or chemotherapy (p = 0.30) with the overall survival. Conclusions: This study suggests that the use of an immunohistochemical panel of CDX2, CK7 and MUC1 allows the classification with higher accuracy in the intestinal or pancreatobiliary type. It was not possible to affirm that chemotherapy, pathological staging or histopathological profile influenced the overall survival, but the major impact of this study was the possibility to classify, from a reduced immunohistochemical panel, the two usual histological subtypes of ampullary adenocarcinoma and thus establish a protocol to better target patients.

Introdução: Apesar dos avanços e uniformização preconizada pelas diretrizes mundiais de ressuscitação cardiopulmonar (RCP), ainda é insuficiente o conhecimento da efetividade da RCP intra-hospitalar no Brasil. Neste estudo avaliamos variáveis clínicas e demográficas de pacientes submetidos à RCP e preditores independentes associados à sobrevivência imediata (recuperação da circulação espontânea acima de 24h), sobrevivência até a alta hospitalar, em seis e doze meses. Métodos: este estudo transversal incluiu, de forma prospectiva, 763 pacientes em parada cardiorrespiratória (PCR) entre 1º de novembro de 2007 a 1º de novembro de 2010, ocorrida no ambiente intra-hospitalar de 17 hospitais gerais e institutos de especialidades. As manobras de RCP foram executadas em 575 pacientes. Resultados: A modalidade de PCR mais frequente foi a assistolia (40,7%), seguida de atividade elétrica sem pulso (39,3%). A sobrevivência imediata foi de 48,8%, sobrevivência até a alta hospitalar foi de 13%, de 4,3% em seis e de 3,8% em doze meses. Os preditores independentes associados à sobrevivência imediata foram o ritmo inicial em fibrilação ventricular ou taquicardia ventricular sem pulso (Razão de Taxas RT 1,31; IC 95% 1,10 a 1,55; p=0,002); presença de sinais de consciência da vítima, ao chegar a equipe atendimento (RT 1,37; IC95% 1,16 a 1,61; p<0,001); uso de epinefrina durante a RCP (RT 1,61; IC 95% 1,32 a 1,98; p < 0,001); hipoglicemia como causa da PCR (RT 1,68; IC 95% 1,11 a 2,55; p=0,014). Foram preditores independentes associados à menor sobrevivência imediata: hipotensão como causa da PCR (RT 0,74; IC 95% 0,61 a 0,90; p=0,003); sedentarismo como antecedente à PCR (RT 0,76; IC 95% 0,66 a 0,88; p< 0,001) e tempos da duração da RCP: maiores tempos com menor sobrevivência. Como preditores independentes associados à sobrevivência até a alta hospitalar, foram identificados: presença de médicos e enfermeiros treinados em ACLS e/ou BLS na equipe de atendimento (HR 3,07; IC 95% 1,39 a 6,78; p=0,006) e ritmo sinusal após a recuperação da circulação espontânea (HR 1,44; IC 95% 1,26 a 1,75; p=0,002). Como preditores independentes para maior sobrevivência em seis meses identificou-se: uso de epinefrina (HR 4,09; IC 95% 1,14 a 14,69; p=0,030), ritmo sinusal após a recuperação da circulação espontânea (HR 4,09; IC 95% 1,14 a 14,69; p=0,030) e antecedente de infarto do miocárdio (HR 4,08; IC 95% 1,51 a 11,06; p=0,006). Não foram identificados preditores independentes para sobrevivência em doze meses. Conclusões: Foram identificados como preditores independentes para sobrevivência imediata o ritmo inicial em fibrilação ventricular ou taquicardia ventricular sem pulso, presença de sinais de consciência da vítima, uso de epinefrina durante a RCP, hipoglicemia como causa da PCR. Como preditores independentes associados à sobrevivência até a alta hospitalar a presença de médicos e enfermeiros treinados em ACLS e/ou BLS e o ritmo sinusal após a recuperação da circulação espontânea. Os achados sugerem perfil multicêntrico nacional da ressuscitação, fornecendo dados potencialmente representativos da ressuscitação cardiopulmonar intra-hospitalar no Brasil. / Introduction: in spite of the advances and worldwide standardization for cardiopulmonary resuscitation recommended by international guidelines, knowledge on the effectiveness of in-hospital cardiopulmonary resuscitation (CPR) is not yet sufficient in Brazil. In this study, we evaluated both demographic and clinical variables in patients underwent cardiopulmonary resuscitation and independent predictors associated to immediate (recovery of spontaneous circulation up to 24 h), until hospital discharge, six and twelve months survival rates. Methods: This cross-sectional study included, prospectively, 763 patients who presented in-hospital cardiac arrest between November 1st 2007 and 01 November 1st 2010, from 17 general hospitals and specialty institutes. CPR procedures were performed in 575 patients. RESULTS: The cardiac arrest modality most frequently found was asystole (40.7%), followed by pulseless electrical activity (39,3%). Immediate survival was 48,8%, survival until hospital discharge was 13%, 4.3% in six months and 3.8% in twelve months. Independent predictors associated with higher immediate survival were: ventricular fibrillation or ventricular tachycardia without pulse as the initial rhythm of cardiac arrest (Rate Ratio- RR 1.31; IC 95% 1.10 to 1.55; p = 0.002); presence of victim consciousness signs when arrival of the emergency staff (RR 1.37; IC95% 1.16 to 1.61; p < 0.001); use of epinephrine during CPR (RR 1.61; IC 95% 1.32 to 1.98; p < 0.001); hypoglycemia as cause of cardiac arrest (RR 1.68; IC 95% 1.11 to 2.55; p = 0.014). Independent predictors associated with lower immediate survival were: hypotension as cause of cardiac arrest (RR 0.74; IC 95% 0.61 to 0.90; p = 0.003); sedentary lifestyle prior to cardiac arrest (RR 0.76; IC 95% 0.66 to 0.88; p < 0.001) and duration of the cardiopulmonary resuscitation: the longer the duration, the lower the survival. Independent predictors associated with hospital discharge survival were: presence of doctors and nurses with ACLS and/or BLS previous training, in the emergency team (HR 3.07; IC 95% 1.39 to 6.78; p = 0.006) and sinus rhythm after recovery of spontaneous circulation (HR 1.44; IC 95% 1.26 to 1.75; p = 0.002). Independent predictors of higher six-month survival rate were use of epinephrine (HR 4.09; IC 95% 1.14 to 14.69; p = 0.030), sinus rhythm after return of spontaneous circulation (HR 4.09; IC 95% 1.14 to 14.69; p = 0.030) and previous myocardial infarction (HR 4.08; IC 95% 1.51 to 11.06; p = 0.006). Independent predictors of 12-month survival were not identified. Conclusion: As independent predictors for immediate survival we identified: ventricular fibrillation or ventricular tachycardia without pulse as the initial rhythm, presence of signs of awareness of the victim, use of epinephrine during RCP, hypoglycemia as cause of PCR. As independent predictors associated survival until discharged the presence of doctors and nurses trained in ACLS and BLS and the sinus rhythm after recovery of spontaneous circulation (ROSC). These findings suggest a multicentre and national resuscitation profile, providing relevant information, potentially representative of the in-hospital cardiopulmonary resuscitation in Brazil.

Background: We evaluated the concept of whether liver failure patients with a superimposed kidney injury receiving a simultaneous liver and kidney transplant (SLKT) have similar outcomes compared to patients with liver failure without a kidney injury receiving a liver transplantation (LT) alone. Methods: Using data from the United Network of Organ Sharing (UNOS) database, patients were divided into five groups based on pre-transplant model for end-stage liver disease (MELD) scores and categorized as not having (serum creatinine (sCr) <= 1.5 mg/dL) or having (sCr > 1.5 mg/dL) renal dysfunction. Of 30,958 patients undergoing LT, 14,679 (47.5%) had renal dysfunction, and of those, 5,084 (16.4%) had dialysis. Results: Survival in those (liver failure with renal dysfunction) receiving SLKT was significantly worse (P < 0.001) as compared to those with sCr < 1.5 mg/dL (liver failure only). The highest mortality rate observed was 21% in the 36+ MELD group with renal dysfunction with or without SLKT. In high MELD recipients (MELD > 30) with renal dysfunction, presence of renal dysfunction affects the outcome and SLKT does not improve survival. In low MELD recipients (16 - 20), presence of renal dysfunction at the time of transplantation does affect post-transplant survival, but survival is improved with SLKT. Conclusions: SLKT improved 1-year survival only in low MELD (16 - 20) recipients but not in other groups. Performance of SLKT should be limited to patients where a benefit in survival and post-transplant outcomes can be demonstrated.

L'analyse de survie constitue bien souvent l'objectif principal des études cliniques en cancérologie. Les données de survie découlent d'un événement subi par les sujets de l'étude, événement qui correspond par exemple au décès pour la survie globale et à la progression tumorale pour la survie sans progression. Les méthodes non-paramétriques de Kaplan-Meier et semi-paramétriques de Cox représentent les modèles standards les plus utilisés pour modéliser ces données de survie, mais ne s'appliquent que dans le cas d'un seul événement temporel. La survie globale est considérée comme le critère clinique optimal pour juger de l'efficacité d'un traitement. La survie sans progression est un critère intermédiaire, qui représente un critère potentiel de substitution pour la survie globale. Depuis plusieurs années, un intérêt croissant s'est porté sur la validation statistique de critères intermédiaires. Cette validation passe par la mesure de la corrélation entre le critère clinique principal et le critère intermédiaire. Ainsi, une modélisation bivariée apparait intéressante afin de décrire la structure de dépendance entre les survies sans progression et globale. L'objectif de cette thèse concerne la modélisation de la structure d'association entre les survies sans progression et globale ainsi que la quantification de cette association via des mesures de dépendance. Pour cela, nous étudions en premier lieu les extensions du modèle de Cox qui peuvent traiter la dépendance statistique entre les données. Nous proposons ensuite une nouvelle modélisation paramétrique de la survie globale basée sur une distribution conditionnelle et sur les survies sans progression et post-progression. De plus, nous examinons différents modèles paramétriques de survie bivariée en termes de mesures de corrélation. Ces modèles sont fondés sur deux approches : les distributions marginales et l'indépendance conditionnelle. Enfin, nous appliquons et comparons les modèles étudiés en utilisant les données d'un essai clinique randomisé de phase III, impliquant des patients atteints de cancer du poumon non à petites cellules localement avancé. / Analysis of survival often represents the main aim in cancer clinical studies. Survival data arise from an event experienced by the study subjects. This event corresponds for example to the death for overall survival and to tumor progression for progression-free survival. The Kaplan-Meier nonparametric estimator and the Cox semiparametric model are the most used standard methods for modeling survival data, although they are applied only in the case of unique temporal event. Overall survival is the optimal clinical endpoint for assessing the efficiency of treatment. Progression-free survival is an intermediate endpoint considered as a potential surrogate of overall survival. For the past few years, we observed an increasing focus on statistical validation of intermediate endpoints and this through measurement of the correlation between the principal clinical endpoint and the intermediate one. Thus, bivariate modeling could be of interest for describing the dependence structure between progression-free survival and overall survival. The aim of this thesis is the modeling of the structure of association between progression-free survival and overall survival as well as the quantification of this association using dependence measures. For this, we study at first extensions of Cox model able to address the topic concerning the statistical dependence between data. Next, we propose a new parametric modeling of overall survival based on two survival times : progression-free survival and post-progression survival, assumed to be linked by a conditional distribution. Moreover, we examine different parametric models for bivariate survival data concerning correlation measurement. These models are based on the marginal distributions and the conditional independence. Finally, we apply and compare these models using data from a phase III randomized clinical trial, involving patients with locally advanced non-small cell lung cancer.

The thesis presents fundamental characteristics of survival analysis in the case of competing risks and their relationships. In the case without regression, basic nonparametric estimates and a logarithmic likelihood function for parameter estimates is given. The main focus is on Cox's proportional hazards model (PH), a model with accelerated time (AFT) and a flexible regression model (FG) are also mentioned. The identifiability of the associated survival function is solved using copulas. Basics of copula theory and the measurement of dependence by correlation coefficients (Pearson, Spearman and Kendal) are described in a separate chapter. A substantial part of the theory is practically used in a generated case without regression.

Background: Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor with poor clinical outcome. Identification and development of new markers could be beneficial for the diagnosis and prognosis of GBM patients. Deregulation of microRNAs (miRNAs or miRs) is involved in GBM. Therefore, we attempted to identify and develop specific miRNAs as prognostic and predictive markers for GBM patient survival.Methods: Expression profiles of miRNAs and genes and the corresponding clinical information of 480 GBM samples from The Cancer Genome Atlas (TCGA) dataset were downloaded and interested miRNAs were identified. Patients' overall survival (OS) and progression-free survival (PFS) associated with interested miRNAs and miRNA-interactions were performed by Kaplan-Meier survival analysis. The impacts of miRNA expressions and miRNA-interactions on survival were evaluated by Cox proportional hazard regression model. Biological processes and network of putative and validated targets of miRNAs were analyzed by bioinformatics.Results: In this study, 6 interested miRNAs were identified. Survival analysis showed that high levels of miR-326/miR-130a and low levels of miR-323/miR-329/miR-155/miR-210 were significantly associated with long OS of GBM patients, and also showed that high miR-326/miR-130a and low miR-155/miR-210 were related with extended PFS. Moreover, miRNA-323 and miRNA-329 were found to be increased in patients with no-recurrence or long time to progression (TTP). More notably, our analysis revealed miRNA-interactions were more specific and accurate to discriminate and predict OS and PFS. This interaction stratified OS and PFS related with different miRNA levels more detailed, and could obtain longer span of mean survival in comparison to that of one single miRNA. Moreover, miR-326, miR-130a, miR-155, miR-210 and 4 miRNA-interactions were confirmed for the first time as independent predictors for survival by Cox regression model together with clinicopathological factors: Age, Gender and Recurrence. Plus, the availability and rationality of the miRNA-interaction as predictors for survival were further supported by analysis of network, biological processes, KEGG pathway and correlation analysis with gene markers.Conclusions: Our results demonstrates that miR-326, miR-130a, miR-155, miR-210 and the 4 miRNA-interactions could serve as prognostic and predictive markers for survival of GBM patients, suggesting a potential application in improvement of prognostic tools and treatments.

Background: Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor with poor clinical outcome. Identification and development of new markers could be beneficial for the diagnosis and prognosis of GBM patients. Deregulation of microRNAs (miRNAs or miRs) is involved in GBM. Therefore, we attempted to identify and develop specific miRNAs as prognostic and predictive markers for GBM patient survival.Methods: Expression profiles of miRNAs and genes and the corresponding clinical information of 480 GBM samples from The Cancer Genome Atlas (TCGA) dataset were downloaded and interested miRNAs were identified. Patients' overall survival (OS) and progression-free survival (PFS) associated with interested miRNAs and miRNA-interactions were performed by Kaplan-Meier survival analysis. The impacts of miRNA expressions and miRNA-interactions on survival were evaluated by Cox proportional hazard regression model. Biological processes and network of putative and validated targets of miRNAs were analyzed by bioinformatics.Results: In this study, 6 interested miRNAs were identified. Survival analysis showed that high levels of miR-326/miR-130a and low levels of miR-323/miR-329/miR-155/miR-210 were significantly associated with long OS of GBM patients, and also showed that high miR-326/miR-130a and low miR-155/miR-210 were related with extended PFS. Moreover, miRNA-323 and miRNA-329 were found to be increased in patients with no-recurrence or long time to progression (TTP). More notably, our analysis revealed miRNA-interactions were more specific and accurate to discriminate and predict OS and PFS. This interaction stratified OS and PFS related with different miRNA levels more detailed, and could obtain longer span of mean survival in comparison to that of one single miRNA. Moreover, miR-326, miR-130a, miR-155, miR-210 and 4 miRNA-interactions were confirmed for the first time as independent predictors for survival by Cox regression model together with clinicopathological factors: Age, Gender and Recurrence. Plus, the availability and rationality of the miRNA-interaction as predictors for survival were further supported by analysis of network, biological processes, KEGG pathway and correlation analysis with gene markers.Conclusions: Our results demonstrates that miR-326, miR-130a, miR-155, miR-210 and the 4 miRNA-interactions could serve as prognostic and predictive markers for survival of GBM patients, suggesting a potential application in improvement of prognostic tools and treatments.

Thesis (M.Sc. (Statistics)) -- University of Limpopo, 2019 / Recurrent peritonitis is a major problem of peritoneal dialysis (PD) due to its association with technique failure in the dialysis process. The literature on peritonitis focused only on investigating major risk factors associated with the first episode of peritonitis. However, this dissertation investigates factors associated to multiple episodes of peritonitis, to a maximum of 6 episodes. The correlation of recurrent episodes of a patient is considered. The univariate counting process, stratified, gap-time and marginal hazard regression models are applied to select the significant covariates to the multivariate regression hazard models. Regression coefficient for covariates are found to be statistically significant at 5% level. The application of Akaike information criterion (AIC) and Schwarz bayesian criterion (SBC) assisted to filter out the best method which is the stratified regression hazard model. The major risk factors associated with recurrent episodes of peritonitis are examined from the selected good fitting model. In conclusion, the selected model identified two independent risk factors to be significantly associated with recurrent episodes of peritonitis: marital status and glomerularfiltrationrate. Twocategoriesofmaritalstatus, divorceandwidowerare the significant factors compared to married patients (when taking married patients as the reference category). / VLIROUC Programme

An efficient way of analyzing survival clinical data such as cancer data is a great concern to health experts. In this study, we investigate and propose an efficient way of handling survival clinical data. Simulation studies were conducted to compare performances of various forms of survival model techniques using an R package ``survsim". Models performance was conducted with varying sample sizes as small ($n5000$). For small and mild samples, the performance of the semi-parametric outperform or approximate the performance of the parametric model. However, for large samples, the parametric model outperforms the semi-parametric model. We compared the effectiveness and reliability of our proposed techniques using a real clinical data of mild sample size. Finally, systematic steps on how to model and explain the proposed techniques on real survival clinical data was provided.

Survival Analysis in the context of Political Science is frequently used to study the duration of agreements, political party influence, wars, senator term lengths, etc. This paper surveys a collection of methods implemented on a modified version of the Power-Sharing Event Dataset (which documents civil war peace agreement durations in the Post-Cold War era) in order to identify the research questions that are optimally addressed by each method. A primary comparison will be made between a Cox Proportional Hazards Model using some advanced capabilities in the glmnet package, a Survival Random Forest Model, and a Survival SVM. En route to this comparison, issues including Cox Model variable selection using the LASSO, identification of clusters using Hierarchal Clustering, and discretizing the response for Classification Analysis will be discussed. The results of the analysis will be used to justify the need and accessibility of the Survival Random Forest algorithm as an additional tool for survival analysis.