Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (p. 123-129).

Thesis (Ph. D.)--University of Oklahoma. / Includes bibliographical references.

Abstract To date, most epidemiological studies have shown a weak or moderate association between dental diseases such as periodontal infections, dental caries and tooth loss, and atherosclerotic vascular diseases. However, the nature of this association is not known; it may be due to the biological effect of oral infections on initiation or progress of atherosclerosis or it may be non-causal due to determinants in common, either biological or behavioural. Methodological shortcomings, inconsistent results and a lack of definite proof from intervention studies have led to the conclusion that causality between dental diseases and atherosclerotic vascular diseases has not been established. The aim of this study was to produce evidence on the nature of the association between dental diseases and atherosclerotic vascular diseases. The study uses data from the 1966 Birth Cohort of Northern Finland (N = 11,637). The data were collected in 1997–1998, when the cohort members had reached 31 years of age. The respondents were asked through a postal questionnaire about their oral health. In addition, respondents were asked about their general health and oral and general health habits. The response rate was 75.3%. Those who lived in Northern Finland or the capital city region were invited to clinical health examination (N = 8,463). Altogether 5,696 subjects supplied the data, representing 67.3% of those who were invited to the clinical examination. While the study showed an association of self-reported gingivitis, dental caries and tooth loss with the prevalent angina pectoris, it also showed that these self-reported dental diseases were not important determinants for elevated C-reactive protein levels. This suggests that the associations that were found between dental conditions and prevalent angina pectoris are mainly caused by factors other than biological mechanisms related to infection or inflammation. The lack of a biological explanation related to infections or inflammatory processes suggests that other biological mechanisms or biases, including confounding, should be considered as an alternative explanation. However, it must be noted that the possibility that oral infections also contribute to the development of atherosclerosis should not be rejected either.

Background: Black South African women are known to have a high usage rate of injectable contraceptives. Breast cancer is the second leading cancer after malignant cervical neoplasms in black South African women. There is evidence that sex hormones are associated with an increased risk of developing breast cancer. In the Western Cape, investigators suggested that injectable contraceptives, more specifically DMPA, may increase breast cancer risk. In another study conducted in the same province, a weak association between breast cancer and women taking combined oestrogen/progesterone oral contraceptives was found, though no risk associated with injectable progestogen contraceptives (DMPA) was confirmed. Study Objective: This study aimed to determine whether there is an association between hormonal contraceptive use and an increased risk of cancer of the breast. Methods: Data was obtained from an ongoing case control study set up by MRC/Wits/NHLS Cancer Epidemiology Research Group (CERG) in 1995 to investigate risk factors associated with cancer among the black population in Johannesburg. Data was processed using STATA, version8 and analysed using univariate, bivariate and multivariate unmatched logistic regression models. Results: There was evidence that an overall use of oral contraceptives increases the risk of breast cancer; cases (n= 221), controls :( n= 153), OR=2.01 (95% CI:1.45, 2.80), p<0.0001. There was evidence of an association between use of injectable contraception and the risk of breast cancer; cases (n=244), controls (n=202), OR=1.51(CI: 1.14, 2.01),p=0.004 Surprisingly, no other use characteristic of either hormonal contraceptive method was statistically significantly associated with the risk of breast cancer in our dataset. The combined use of both oral and injectable contraception was associated with an increased risk of breast cancer, OR=1.68(1.21, 2.33), p =0.002. There was a strong effect modification (interaction) between oral contraceptive use and injectable progesterone associated with the risk of breast cancer, (p=0.008). Conclusion: After adjusting for all potential risk and confounding factors, as collected in the dataset, there was evidence of an association between combined oral contraceptive use and breast cancer. An association between cancer of the breast and overall use of injectable progesterone use was also established. There was evidence of association between the use of both hormonal contraceptive methods and an increased risk of breast cancer. However, whether these findings reflect the reality in terms of causal relationship or are the result of bias must be ascertained.

En recherche médicale, les cohortes permettent de mieux comprendre l'évolution d'une pathologie et d'améliorer la prise en charge des patients. La mise en évidence de liens de causalité entre certains facteurs de risque et l'évolution de l'état de santé des patients est possible grâce à des études étiologiques. L'analyse de cohortes permet aussi d'identifier des marqueurs pronostiques de l'évolution d'un état de santé. Cependant, les facteurs de confusion constituent souvent une source de biais importante dans l'interprétation des résultats des études étiologiques ou pronostiques. Dans ce manuscrit, nous présentons deux travaux de recherche en Biostatistique dans la thématique des scores de propension. Dans le premier travail, nous comparons les performances de différents modèles permettant d'évaluer la causalité d'une exposition sur l'incidence d'un événement en présence de données censurées à droite. Dans le second travail, nous proposons un estimateur de courbes ROC dépendantes du temps standardisées et pondérées permettant d'estimer la capacité prédictive d'un marqueur en prenant en compte les facteurs de confusion potentiels.En cohérence avec l'objectif de fournir des outils statistiques adaptés, nous présentons également dans ce manuscrit une application nommée Plug-Stat®. En lien direct avec la base de données, elle permet de réaliser des analyses statistiques adaptées à la pathologie afin de faciliter la recherche épidémiologique et de mieux valoriser les données de cohortes observationnelles. / In medical research, cohorts help to better understandthe evolution of a pathology and improve the care ofpatients. Causal associations between risk factors andoutcomes are regularly studied through etiological studies. Cohorts analysis also allow the identification of new markers for the prediction of the patient evolution.However, confounding factors are often source of bias in the interpretation of the results of etiologic or prognostic studies.In this manuscript, we presented two research works in Biostatistics, the common topic being propensity scores.In the first work, we compared the performances of different models allowing to evaluate the causality of an exposure on an outcome in the presence of rightc ensored data. In the second work, we proposed anestimator of standardized and weighted time-dependentROC curves. This estimator provides a measure of theprognostic capacities of a marker by taking into accountthe possible confounding factors. Consistent with our objective to provide adapted statistical tools, we also present in this manuscript an application, so-calledPlug-Stat®. Directly linked with the database, it allows toperform statistical analyses adapted to the pathology in order to facilitate epidemiological studies and improve the valorization of data from observational cohorts.

Les études observationnelles en pharmacoépidémiologie sont souvent mises en place pour évaluer un médicament mis sur le marché récemment ou concurrencé par de nombreuses alternatives thérapeutiques. Cette situation conduit à devoir évaluer l'effet d'un médicament dans une cohorte comprenant peu de sujets traités, c'est à dire une population où l'exposition d'intérêt est rare. Afin de prendre en compte les facteurs de confusion dans cette situation, certains auteurs déconseillent l'utilisation du score de propension au profit du score pronostique, mais cette recommandation ne s'appuie sur aucune étude évaluant spécifiquement les faibles prévalences de l'exposition, et ignore le type d'estimation, conditionnelle ou marginale, fournie par chaque méthode d'utilisation du score pronostique.La première partie de ce travail évalue les méthodes basées sur le score de propension pour l'estimation d'un effet marginal en situation d'exposition rare. La deuxième partie évalue les performances des méthodes basées sur le score pronostique rapportées dans la littérature, introduit de nouvelles méthodes basées sur le score pronostique adaptées à l'estimation d'effets conditionnels ou marginaux, et les compare aux performances des méthodes basées sur le score de propension. La dernière partie traite des estimateurs de la variance des effets du traitement. Nous présentons les conséquences liées à la non prise en compte de l'étape d'estimation du score de propension et du score pronostique dans le calcul de la variance. Nous proposons et évaluons de nouveaux estimateurs tenant compte de cette étape. / Pharmacoepidemiologic observational studies are often conducted to evaluate newly marketed drugs or drugs in competition with many alternatives. In such cohort studies, the exposure of interest is rare. To take into account confounding factors in such settings, some authors advise against the use of the propensity score in favor of the prognostic score, but this recommendation is not supported by any study especially focused on infrequent exposures and ignores the type of estimation provided by each prognostic score-based method.The first part of this work evaluates the use of propensity score-based methods to estimate the marginal effect of a rare exposure. The second part evaluates the performance of the prognostic score based methods already reported in the literature, compares them with the propensity score based methods, and introduces some new prognostic score-based methods intended to estimate conditional or marginal effects. The last part deals with variance estimators of the treatment effect. We present the opposite consequences of ignoring the estimation step of the propensity score and the prognostic score. We show some new variance estimators accounting for this step.

Nous présentons des méthodes statistiques reposant sur des problèmes de factorisation matricielle. Une première méthode permet l'inférence rapide de la structure de populations à partir de données génétiques en incluant l'information de proximité géographique. Une deuxième méthode permet de corriger les études d'association pour les facteurs de confusion. Nous présentons dans ce manuscrit les modèles, ainsi que les aspects théoriques des algorithmes d'inférence. De plus, à l'aide de simulations numériques, nous comparons les performances de nos méthodes à celles des méthodes existantes. Enfin, nous utilisons nos méthodes sur des données biologiques réelles. Nos méthodes ont été implémentées et distribuées sous la forme de packages R : tess3r et lfmm. / We present statistical methods based on matrix factorization problems. A first method allows efficient inference of population structure from genetic data and including geographic proximity information. A second method corrects the association studies for confounding factors. We present in this manuscript the models, as well as the theoretical aspects of the inference algorithms. Moreover, using numerical simulations, we compare the performance of our methods with those of existing methods. Finally, we use our methods on real biological data. Our methods have been implemented and distributed as R packages: tess3r and lfmm.

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2007. / Härtill 5 uppsatser.

Les réglementations conduisent à multiplier les évaluations du risque écologique lié au rejet des substances chimiques dans les milieux aquatiques avec pour objectif de protéger les populations naturelles. Cependant, ce niveau de protection visé ne peut être utilisé facilement pour établir un lien direct entre une contamination et ses effets. Pour palier cette difficulté, les approches multi-échelles basées sur l'étude des effets des contaminations sur des marqueurs individuels puis sur l'extrapolation de ces effets au niveau des poipulations à partir de modèles de dynamique de population représentent des démarches prometteuses et commencent à être bien acceptées dans les démarches prédictives.Cependant, leur utilisation pour le diagnostic de la qualité des milieux aquatiques reste pour le moment très rare, d'une part en raison de la forte variabilité des réponses des marqueurs individuels in situ liée à l'influence de divers facteurs environnementaux confondants pour l'évaluation de la toxicité, et d'autre part à cause du manque de pertinence environnementale des modèles actuellement proposés. Centré sur l'utilisation de deux espèces couramment observées dans les cours d'eau européens et présentant des caractéristiques écologiques et phylogéniques contrastées : le crustacé Gammarus fossarum et le mollusque Potamopyrgus antipodarum, ce travail doctoral a permis : 1- de proposer une méthodologie pour prendre en compte l'influence des facteurs de confusion dans le but d'améliorer la lecture des bioessais in situ basés sur la mesure des marqueurs individuels sur des organismes encagés et 2- de développer des modèles de dynamique de population écologiquemnt pertinents. / The regulatory framework lead to increase the assessments of the ecological risk linked to the dischaarge of chemical substances in aquatic environment with the aim to protect natural populations. However, this target level of protection cannot be used so easily to etablish a direcet link between a contamination and its effects. In order to overcome this difficulty, the multi-scale approaches based on the study of the effects of the contaminations on individual markers and then on the extrapolation of these effects at the population level with population dynamic models reprensent promising tools and start to bewell accepted in predictive processes. Yet, their use for the diagnosis of water quality remainsrare for the moment, on the one hand, because of the important varaibility of answers of individual makers in situ linked to the influence of diverse confounding environmental factors for the assessments of toxicity and, on the other hand, because pf the lack of environmental relevance of models currently proposed. Focused on the use of 2 species widely observed in European rivers and presenting contrastingecological and phylogenetic characteristics : the Grammar fossarum crutacean and the Potamopyrgus antipodarum mollusc, this doctoral degree first propose a methodology to consider the influenceof confounding factors in order to improve the reading of biological in situ tests based on the measurment of individual markers on caged organisms and second, to develop ecologically relevant population models. Thus, this work allowed to underline the importance of the consideration of confounding factors (i.e. temperature), in different in situ tests based on the measurment of individul markers on caged organisms. Moreover, population models for both species have been defined in order to test the influence of life histories and seasonal variations on demographic sensitivity of populations.

[pt] Neste trabalho, os modelos Poisson-gama são estendidos para uma formulação mais geral onde o preditor linear das covariáveis é substituído por um preditor aditivo de funções genéricas destas covariáveis. Como nos modelos aditivos generalizados (MAG), as funções lineares das covariáveis constituem um caso particular de modelo aditivo e as funções suavizadores utilizadas são as splines cúbicas naturais. A formulação semi-paramétrica permite ampliar o campo de aplicação desta classe de modelos. Os modelos semi-paramétricos são estimados por um processo iterativo combinando maximização da verossimilhança e algoritmo backfitting. Todos os algoritmos de estimação e diagnósticos estão implementados nas linguagens de programação R e C. / [en] This work is aimed at extending the Poisson-Gamma models towards a more general specification, where the linear predictor of covariates is replaced by an additive predictor of generic functions of these covariates. Just like the generalized additive models (GAM), the linear functions of covariates are a particular case of additive models and the natural cubic splines are used as smoothing functions. The semiparametric specification allows to enlarge the possibilities of application of these models. The semiparametric models are fitted by an iterative process that combines maximization of likelihood and backfitting algorithm. All the routines for model fitting and diagnostics are implemented in R and C programming languages.