[EN] Atrial fibrilation (AF) is the most common cardiac arrhythmia, however, the knowledge about its causes and mechanisms is still uncompleted. Several studies suggest that atrial structural and electrophysiological remodeling are directly related to its development and perpetuation. To this respect, ECG and preoperative clinical data have been studied to analyze different aspects of atrial remodeling. Nonetheless, there is a lack of studies using ECG parameters to provide valuable clinical information in the study of AF aggressive treatments, such as the Cox-Maze surgery. In this work, ECG parameters such as fibrillatory (f) waves organization and amplitude are studied to predict patient's rhythm from the discharge after the Cox-Maze surgery until a twelve months follow up period. On the other hand, widely used clinical parameters such as age, AF duration and left atrial size (LA size) are studied to assess electrocardiographic results. In addition, clinical information known as a risk factor to develop AF such as weight and body mass index has also been analyze. After assess the individual indices, classification models were created in order to optimize the prediction capability. The results obtained reported that the ECG indices outperform the cinical indices. Nevertheless, the information contained in both types of indices is complementary as the generation of a classification model combining the indices shows. This model exceeded 90% accuracy in each period analyzed. In conclusion, studying the AF information contained in an ECG could provide new data to understand the AF and also could help to develop a reliable method to predict preoperatively the Cox-Maze outcome. / [ES] La fibrilación auricular (FA) es la arritmia cardiaca más comúnmente encontrada en la práctica clínica diaria, sin embargo, todavía no se comprenden completamente los mecanismos fisiológicos que causan el inicio y la perpetuación de la FA. Diversos estudios sugieren que el remodelado estructural y electrofisiológico de la aurícula está relacionado directamente con el desarrollo y perpetuación de la FA. En este sentido, se ha estudiado el ECG e información clínica preoperatoria para analizar distintos aspectos del remodelado. Sin embargo, hay una falta de estudios usando parámetros electrocardiográficos para proporcionar información clínica valiosa en el estudio de tratamientos agresivos de la FA como la cirugía Cox-Maze. En este trabajo, se estudian parámetros electrocardiográficos como la organización de las ondas fibrilatorias y su amplitud para predecir el ritmo de los pacientes desde el momento del alta, tras la cirugía Cox-Maze hasta 12 meses después de la operación. Por otro lado, para evaluar la capacidad de dichos índices, se han utilizado parámetros clínicos ampliamente utilizados como la edad, el tamaño de la aurícula izquierda y el tiempo en FA. Además, se han estudiado también parámetros clínicos conocidos como factores de riesgo para desarrollar FA como son el peso y el índice de masa corporal. Tras analizar la capacidad predictiva de los índices individualmente, éstos se han combinado mediante la generación de modelos de predicción para optimizar la precisión de las predicciones. Los resultados obtenidos señalan que la información contenida en el ECG obtuvo resultados estadísticamente significativos y predicciones más precisas que los índices clínicos. No obstante, el desarrollo de modelos de predicción combinando ambos tipos de índices superó al uso de éstos por separado, con resultados por encima del 90% en todos los períodos estudiados. En conclusión, el análisis del ECG podría aportar nuevos enfoques a la hora de estudiar la FA, y su uso como herramienta de predicción podría ayudar a desarrollar tratamientos más eficientes y personalizados. / [CA] La fibril·lació auricular (FA) és l'arítmia cardíaca més comunament trobada en la pràctica clínica diària, no obstant això, encara no es comprenen completament els mecanismes fisiològics que causen l'inici i la perpetuació de la FA. Diversos estudis suggerixen que el remodelat estructural i electrofisiològic de l'aurícula està relacionat directament amb el desenrotllament i perpetuació de la FA. En este sentit, s'ha estudiat l'ECG i informació clínica preoperatòria per a analitzar distints aspectes del remodelat. No obstant això, hi ha una falta d'estudis usant paràmetres electrocardiográficos per a proporcionar informació clínica valuosa en l'estudi de tractaments agressius de la FA com la cirurgia Cox-Maze. En este treball, s'estudien paràmetres electrocardiográficos com l'organització de les ones fibrilatorias i la seua amplitud per a predir el ritme dels pacients des del moment de l'alta, després de la cirurgia Cox-Maze fins a 12 mesos després de l'operació. Per un altre costat per a avaluar la capacitat dels dits índexs, s'han utilitzat paràmetres clínics àmpliament utilitzats com l'edat, la grandària de l'aurícula esquerra i el temps en FA. A més, s'han estudiat també paràmetres clínics coneguts com a factors de risc per a desenrotllar FA com són el pes i l'índex de massa corporal. Després d'analitzar la capacitat predictiva dels índexs individualment, estos s'han combinat per mitjà de la generació de models de predicció per a optimitzar la precisió de les prediccions. Els resultats obtinguts assenyalen que la informació continguda en l'ECG va obtindre resultats estadísticament significatius i prediccions més precises que els índexs clínics. No obstant això, el desenrotllament de models de predicció combinant ambdós tipus d'índexs va superar a l'ús d'estos per separat, amb resultats per damunt del 90% en tots els períodes estudiats. En conclusió, l'anàlisi de l'ECG podria aportar nous enfocaments a l'hora d'estudiar la FA, i el seu ús com a ferramenta de predicció podria ajudar a desenrotllar tractaments més eficients i personalitzats. / Hernández Alonso, A. (2017). Development of new signal analysis methods as preoperative predictors of the Cox-Maze procedure outcome in atrial fibrillation [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90491

Network data, capturing the connections or interactions among subjects of interest, are widely used across numerous scientific disciplines. Recent years have seen a significant increase in time-varying network data, which record not only the number of interactions but also the precise timestamps when these events occur. These data call for novel analytical developments that specifically leverage the event time information. In this thesis, we propose frameworks for analyzing longitudinal/panel network data and continuous time network data. For the analysis of longitudinal network data, we introduce a semiparametric latent space model. The model consists of a static latent space component and a time-varying node-specific baseline component. We develop a semiparametric efficient score equation for the latent space parameter. Estimation is accomplished through a one-step update estimator and a suitably penalized maximum likelihood estimator. We derive oracle error bounds for both estimators and address identifiability concerns from a quotient manifold perspective. For analyzing continuous time network data, we introduce a Cox-type counting process latent space model. To accomodate the event history observations, each edge is modeled as a counting process, with intensity comprising three components: a time-dependent baseline function, an individual-level degree heterogeneity parameter, and a low-rank embedding for the interaction effects. A nuclear-norm penalized likelihood estimator is developed, and its oracle error bounds are established. Additionally, we discuss a several ongoing directions for this work.

One of the most common measures of clinical outcomes is the survival time. Accurately linking cancer molecular profiling with survival outcome advances clinical management of cancer. However, existing survival analysis relies intensively on statistical evidence from a single level of data, without paying much attention to the integration of interacting multi-level data and the underlying biology. Advances in genomic techniques provide unprecedented power of characterizing the cancer tissue in a more complete manner than before, opening the opportunity of designing biologically informed and integrative approaches for survival analysis. Many cancer tissues have been profiled for gene expression levels and genomic variants (such as copy number alterations, sequence mutations, DNA methylation, and histone modification). However, it is not clear how to integrate the gene expression and genetic variants to achieve a better prediction and understanding of the cancer survival. To address this challenge, we propose two approaches for data integration in order to both biologically and statistically boost the features selection process for proper detection of the true predictive players of survival. The first approach is data-driven yet biologically informed. Consistent with the biological hierarchy from DNA to RNA, we prioritize each survival-relevant feature with two separate scores, predictive and mechanistic. With mRNA expression levels in concern, predictive features are those mRNAs whose variation in expression levels are associated with the survival outcome, and mechanistic features are those mRNAs whose variation in expression levels are associated with genomic variants (copy number alterations (CNAs) in this study). Further, we propose simultaneously integrating information from both the predictive model and the mechanistic model through our new approach GEMPS (Gene Expression as a Mediator for Predicting Survival). Applied on two cancer types (ovarian and glioblastoma multiforme), our method achieved better prediction power than peer methods. Gene set enrichment analysis confirms that the genes utilized for the final survival analysis are biologically important and relevant. The second approach is a generic mathematical framework to biologically regularize the Cox's proportional hazards model that is widely used in survival analysis. We propose a penalty function that both links the mechanistic model to the clinical model and reflects the biological downstream regulatory effect of the genomic variants on the mRNA expression levels of the target genes. Fast and efficient optimization principles like the coordinate descent and majorization-minimization are adopted in the inference process of the coefficients of the Cox model predictors. Through this model, we develop the regulator-target gene relationship to a new one: regulator-target-outcome relationship of a disease. Assessed via a simulation study and analysis of two real cancer data sets, the proposed method showed better performance in terms of selecting the true predictors and achieving better survival prediction. The proposed method gives insightful and meaningful interpretability to the selected model due to the biological linking of the mechanistic model and the clinical model. Other important forms of clinical outcomes are monitoring angiogenesis (formation of new blood vessels necessary for tumor to nourish itself and sustain its existence) and assessing therapeutic response. This can be done through dynamic imaging, in which a series of images at different time instances are acquired for a specific tumor site after injection of a contrast agent. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive tool to examine tumor vasculature patterns based on accumulation and washout of the contrast agent. DCE-MRI gives indication about tumor vasculature permeability, which in turn indicates the tumor angiogenic activity. Observing this activity over time can reflect the tumor drug responsiveness and efficacy of the treatment plan. However, due to the limited resolution of the imaging scanners, a partial-volume effect (PVE) problem occurs, which is the result of signals from two or more tissues combining together to produce a single image concentration value within a pixel, with the effect of inaccurate estimation to the values of the pharmacokinetic parameters. A multi-tissue compartmental modeling (CM) technique supported by convex analysis of mixtures is used to mitigate the PVE by clustering pixels and constructing a simplex whose vertices are of a single compartment type. CAM uses the identified pure-volume pixels to estimate the kinetics of the tissues under investigation. We propose an enhanced version of CAM-CM to identify pure-volume pixels more accurately. This includes the consideration of the neighborhood effect on each pixel and the use of a barycentric coordinate system to identify more pure-volume pixels and to test those identified by CAM-CM. Tested on simulated DCE-MRI data, the enhanced CAM-CM achieved better performance in terms of accuracy and reproducibility. / Ph. D. / Disease outcome can refer to an event, state, condition, or behavior for some aspect of a patient’s health status. Event can express survival, while behavior can assess drug efficacy and treatment responsiveness. To gain deeper and, hence, better understanding about diseases, symptoms inspection has been shifted from the physical symptoms appearing externally on the human body to internal symptoms that require invasive and noninvasive techniques to find out and quantify them. These internal symptoms can be further divided into phenotypic and genotypic symptoms. Examples of phenotypes can include shape, structure, and volume of a specific human body organ or tissue. Examples of genotypes can be the dosage of the genetic information and the activity of genes, where genes are responsible for identifying the function of the cells constituting tissues. Linking disease phenotypes and genotypes to disease outcomes is of great importance to widen the understanding of disease mechanisms and progression. In this dissertation, we propose novel computational techniques to integrate data generated from different platforms, where each data type addresses one aspect of the disease internal symptoms, to provide wider picture and deeper understanding about a disease. We use imaging and genomic data with applications in ovarian, glioblastoma multiforme, and breast cancers to test the proposed techniques. These techniques aim to provide outcomes that are statistically significant, as what current peer methods do, beside biological insights, which current peer methods lack.

本論文主要目地是在研究財務比率對上市公司發生下市事件之預測。我們運用歷史事件研究法和Cox迴歸模型去研究上市公司發生下市事件之原因。同時，我們也針對Cox迴歸模型和Logit模型在發現對下市事件有顯著影響的財務比率作比較。 / This study applies the event history analysis and the Cox regression model to examine the causes of firm delisting, and also compares the performance of the Cox regression model with that of the logit model in detecting factors that have a statistically significant impact on the delisting event. The empirical results show that the hazard rate of firm delisting increases with the ratio of current liabilities to current assets, a binary variable indicating if the total liabilities of a firm is greater than its total assets, and a binary variable indicating if the net income of a firm was negative for the last two quarters, while the hazard rate of firm delisting decreases with increases in the firm size and the ratio of funds provided by operations to total liabilities.

This thesis surveys the method of extending Cox proportional hazard models (1972) and the general class of semiparametric model (2004) in the upgrades or downgrades of credit ratings by S&P. The two kinds of models can be used to modify the relationship of covariates to a recurrent event data of upgrades or downgrades. The benchmark credit-scoring model with a quintet of financial ratios which is inspired by the Z-Score model is employed. These financial ratios include measures of short-term liquidity, leverage, sales efficiency, historical profitability and productivity. The evidences of empirical results show that the financial ratios of historical profitability, leverage, and sales efficiency are significant factors on the rating transitions of upgrades. For the downgrades data setting, the financial ratios of short-term liquidity, productivity, and leverage are significant factors in the extending Cox models, whereas only the historical profitability is significant in the general class of semiparametric model. The empirical analysis of S&P credit ratings provide evidence supporting that the transitions of credit ratings are related to some determined financial ratios under these new econometrics methods.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Le but de ce mémoire de maîtrise est de décrire les propriétés de la loi double Pareto-lognormale, de montrer comment on peut introduire des variables explicatives dans le modèle et de présenter son large potentiel d'applications dans le domaine de la science actuarielle et de la finance. Tout d'abord, nous donnons la définition de la loi double Pareto-lognormale et présentons certaines de ses propriétés basées sur les travaux de Reed et Jorgensen (2004). Les paramètres peuvent être estimés en utilisant la méthode des moments ou le maximum de vraisemblance. Ensuite, nous ajoutons une variable explicative à notre modèle. La procédure d'estimation des paramètres de ce mo-\\dèle est également discutée. Troisièmement, des applications numériques de notre modèle sont illustrées et quelques tests statistiques utiles sont effectués. / The purpose of this Master's thesis is to describe the double Pareto-lognormal distribution, show how the model can be extended by introducing explanatory variables in the model and present its large potential of applications in actuarial science and finance. First, we give the definition of the double Pareto-lognormal distribution and present some of its properties based on the work of Reed and Jorgensen (2004). The parameters could be estimated by using the method of moments or maximum likelihood. Next, we add an explanatory variable to our model. The procedure of estimation for this model is also discussed. Finally, some numerical applications of our model are illustrated and some useful statistical tests are conducted.

Le but premier des services de protection de la jeunesse est de mettre fin à une situation de compromission et d’éviter que celle-ci ne se reproduise. Cependant, une meilleure connaissance des facteurs de risque d’incidence LSJPA chez les jeunes pris en charge en raison de leurs comportements problématiques permettrait de mieux identifier et ainsi, d’adapter les interventions chez ceux se révélant être les plus à risque de délinquance juvénile. La présente étude propose donc de décrire l’ampleur et le risque d’incidence c’est-à-dire, l’application d’une sanction ou d’une mesure en vertu de la LSJPA chez ces jeunes et de déterminer, parmi les facteurs associés au jeune et ceux inhérents à l’intervention, quels en sont les meilleurs prédicteurs. Pour ce faire, des données clinico-administratives des 16 centres jeunesse du Québec ont été utilisées. Ainsi, tous les enfants et adolescents dont le dossier a été fermé à la suite d’une première intervention en protection de la jeunesse en raison de troubles de comportement entre le 1er janvier 2005 et le 31 décembre 2009 ont été observés (N = 6 630). Des analyses de survie (modèle Kaplan-Meier) ainsi que des régressions de Cox ont été effectuées. Les résultats indiquent qu’un jeune pris en charge en raison de troubles de comportement a 39,7% de risque de migrer vers les services judiciaires pour adolescents dans les cinq années qui suivent la fermeture de son dossier. Sans grande surprise, les garçons présentent un plus grand risque que leurs homologues féminins. Il appert également que le risque d’incidence varie en fonction du sexe et de la présence de maltraitance lors de la prise en charge initiale. De plus, les facteurs associés à l’usager lui-même semblent avoir un impact plus important sur l’incidence que ceux associés à la prise en charge. Aussi, la récurrence dans les services de protection en raison de troubles de comportement mais également en raison de nouveaux éléments liés à la maltraitance sont au nombre des éléments à surveiller avec beaucoup d’attention puisqu’ils sont fortement liés à une migration vers la LSJPA. Les implications cliniques sont discutées et une ouverture sur de futurs travaux est faite. / Among children and youth who have been maltreated, several studies point to the elevated risk of developmental problems such as delinquency and justice system involvement. Presenting serious behavioral problems is a sufficient condition to receive child protection services (CPS) in the province of Quebec; this offers the opportunity to focus on this condition and on the role it may play or not in the subsequent risk of Youth Criminal Justice Act (YCJA) involvement. The primary role of CPS is to end an abusive situation and to prevent its recurrence. However, a better understanding of the risk factors that lead to an YCJA involvement would help to identify and to adapt interventions for those at greatest risk of juvenile delinquency. The aim of this study is to describe the risk of an YCJA event after a first intervention of CPS due to behavioral problems, and to determine the individual and intervention related factors associated with this YCJA involvement. Administrative data from 16 youth centers in the province of Quebec has been used. Thus, all children and adolescents who have had their file closed after a first CPS intervention due to behavioral problems between January 1st 2005 and December, 31st 2009 were observed (N = 6,630). Survival analysis (Kaplan-Meier model) and Cox regression analyzes were performed. The results indicate that youths in the sample present a 39.7% overall risk of YCJA involvement within the 5-year follow-up period. Boys present a higher risk of YCJA involvement than girls, an unsurprising result. It also appears that the risk varies by gender and the presence of co-occurrence of maltreatment at initial report. Individual risk factors seem to have a greater impact on YCJA involvement than those associated with the CPS intervention. Moreover, recurrences of CPS due to behavioral problems but also because of new information related to child’s maltreatment are particularly important since they are strongly associated with future YCJA involvement. Implications for theory, research, and practice are discussed.

L’évolution d’une cellule tumorale initiée à une tumeur solide nécessite, à chaque étape, un microenvironnement favorable à sa survie et à sa croissance. Le microenvironnement tumoral est comparé à un foyer d’inflammation chronique dont la composition cellulaire et moléculaire est complexe. Les cellules souches mésenchymateuses (CSM) représentent l’un des principaux acteurs cellulaires présents. Elles migrent vers les sites tumoraux où elles soutiennent l’inflammation, l’angiogenèse et le développement tumoral en activant plusieurs voies de signalisation. Une des voies majeures qui contribuent à l’inflammation est la voie de signalisation NF-B. L’initiation de cette voie provient de la membrane cellulaire entre autres des cavéoles. Nous soumettons l’hypothèse que l’une des cavines, protéines associées aux cavéoles, modulerait le phénotype inflammatoire etou migratoire dans les CSM traitées à la cytokine TNF- (facteur de nécrose tumorale ) en modulant la voie de signalisation NF-B. En effet, nous avons observé une régulation à la hausse de l’expression de la COX-2 (cyclooxygénase-2) et une diminution de l’expression d’IκB qui sont synonymes de l’activation de la voie NF-B dans les CSM que nous avons traitées au TNF-. Nous avons trouvé que le TNF- induit la migration des CSM, et que la répression génique de la Cavine-2 augmente significativement la migration des CSM traitées par le TNF-. La répression génique de la Cavine-2 vient aussi amplifier la tubulogenèse dans les CSM en réponse au TNF-. D’un point de vue moléculaire, la répression génique de la Cavine-2 a montré une très forte amplification de l'expression protéique de la COX-2 dans les CSM en réponse au TNF-. Dans ces mêmes cellules où la Cavine-2 a été réprimée, et suite à un traitement au TNF-, le pic de phosphorylation est plus intense et la courbe de phosphorylation est plus prolongée dans le temps. Ces observations nous permettent d’affirmer que la Cavine-2 a un rôle répresseur sur l’expression de COX-2. Collectivement, nos résultats montrent que la Cavine-2 peut être proposée comme un gène suppresseur de tumeur et est de ce fait, une bonne cible thérapeutique dans les CSM qui permettraient d’agir à des stades précoces du développement tumoral. / The evolution of an initiated tumor cell into a solid tumor requires at each stage a favorable microenvironment for its survival and growth. The tumor microenvironment is compared to a chronic inflammation site with a cellular and molecular complex composition. Mesenchymal stem cells (MSC) have important roles in tumor microenvironment. They migrate to tumor sites where they maintain the inflammation, angiogenesis and tumor development by activating multiple signaling pathways. One of the major pathways that contribute to inflammation is the NF-B signaling pathway. The initiation of this pathway comes from the cell membrane and caveolae. Our hypothesis is that one of cavins, proteins associated to caveolae, modulates the inflammatory phenotype and migration in MSC treated with TNF-. We suggest that this process is modulated by a NF-B signaling pathway. Indeed, we observed an up-regulation of the expression of the cyclooxygenase-2 (COX-2) and a decrease in the expression of IκB which suggest that activation of the NF-B pathway is involved in the MSC treated with TNF. We found that the TNF- induced migration in the MSC, and the knockout of Cavin-2 significantly increased migration of MSC treated with TNF-. The silencing of Cavin-2 considerably increased tubulogenesis of MSC treated with TNF-. At the molecular level, knockout of Cavin-2 showed a very strong amplification of protein expression of COX-2 in the MSC in response to TNF-. In these same cells where Cavin-2 was repressed and treated with TNF-, the peak of phosphorylation of pIB is more intense and the phosphorylation curve is sustained in time. These observations allow us to assert that Cavin-2 has a repressing role on the expression of COX-2. Collectively, our results show that the gene encoding Cavin-2 can be proposed as tumor suppressor gene. This study allowed us to identify new therapeutic targets: Cavins proteins.

Diversos estudos têm demonstrado que a atividade coordenada das células epiteliais com o estroma é fundamental no crescimento e diferenciação em situações fisiológicas e patológicas, inclusive no câncer. Vários relatos acentuam a importância do compartimento estromal nos tumores malignos e indicam fortemente que interações contínuas entre o carcinoma e as células estromais (resultando em regulamento e modulação recíproca) são condições prévias para desenvolvimento e progressão de carcinomas. Comparativamente, pouca informação está disponível sobre as características e o papel do estroma durante o processo carcinogênico e a maioria dos dados são baseados em estudos isolados. Nos animais tratados com o carcinógeno Dimetilhidrazina foi identificado na mucosa colônica o aparececimento de “Focos de Estroma Ativado" (FEA) que diferem do foco inflamatório esporádico encontrado na mucosa normal dos animais controles devido à imuno-expressão aumentada de células CD34, CD68, α-actina de músculo liso (ASMA), COX-2 positivas e densidade microvascular. Além disso, o FEA cercou um número aumentado de criptas colônicas em fissão que freqüentemente apresentavam células epiteliais com núcleos hipercromáticos. Este último achado pode sugerir correlação entre as alterações estromais e epiteliais dentro dos FEA. Embora esses achados sejam novos, são consistentes com observações prévias que o estroma tem um papel significante na carcinogênese. Juntamente com dados da literatura, este trabalho sugere que, no cólon, a “field cancerization" epitelial pode ser acompanhada através de alterações estromais e isto pode apontar novos marcadores de transformação neoplásica. / There has been considerable that the activity of epithelial cells with their stroma is fundamental in controlling growth and differentiation in normal and pathological situations, including cancer. A number of reports stress the importance of the stromal compartment in malignant tumors and strongly indicate that continuous interactions between the carcinoma and stromal cells (resulting in their reciprocal regulation and modulation) are prerequisites for carcinoma development and progression. Comparatively, less information is available about the features and role of the stroma for the carcinogenic process. In animals treated with the carcinogen Dimethyl-hydrazine we identified the appearing of mucosal “Activated Stromal Foci" (ASF) that differ from the sporadic inflammatory foci found in the normal mucosa of the control animals because of the presence of increased immune-expression of CD34, CD68, α-smooth muscle actin (ASMA), COX-2 positive cells and microvessel density. Furthermore, the ASF surrounded a increased number of colonic crypts in fission when compared to areas of normal stroma. This last finding suggests that stromal activation and epithelial changes may be correlated. These findings are novel but expected and consistent with previous observations that the stroma has a significant role in carcinogenesis. Taken together with literature data, our findings suggest that in the colon, the epithelial field cancerization may be accompanied by stromal changes and this may point to the finding of new markers of neoplastic transformation.