Modern medical practice and science involve complex phenotypic definitions. Understanding patterns of association across this range of phenotypes requires co-analysis of high-dimensional association studies in order to characterise shared and distinct elements. In this thesis I address several problems in this area, with a general linking aim of making more efficient use of available data. The main application of these methods is in the analysis of genome-wide association studies (GWAS) and similar studies. Firstly, I developed methodology for a Bayesian conditional false discovery rate (cFDR) for levering GWAS results using summary statistics from a related disease. I extended an existing method to enable a shared control design, increasing power and applicability, and developed an approximate bound on false-discovery rate (FDR) for the procedure. Using the new method I identified several new variant-disease associations. I then developed a second application of shared control design in the context of study replication, enabling improvement in power at the cost of changing the spectrum of sensitivity to systematic errors in study cohorts. This has application in studies on rare diseases or in between-case analyses. I then developed a method for partially characterising heterogeneity within a disease by modelling the bivariate distribution of case-control and within-case effect sizes. Using an adaptation of a likelihood-ratio test, this allows an assessment to be made of whether disease heterogeneity corresponds to differences in disease pathology. I applied this method to a range of simulated and real datasets, enabling insight into the cause of heterogeneity in autoantibody positivity in type 1 diabetes (T1D). Finally, I investigated the relation of subtypes of juvenile idiopathic arthritis (JIA) to adult diseases, using modified genetic risk scores and linear discriminants in a penalised regression framework. The contribution of this thesis is in a range of methodological developments in the analysis of high-dimensional association study comparison. Methods such as these will have wide application in the analysis of GWAS and similar areas, particularly in the development of stratified medicine.

Il existe une grande variabilité dans la réponse aux chimiothérapies anticancéreuses. Ses sources sont diverses: génétiques, physiologiques, comorbidités, médicaments associés, etc. La marge thérapeutique de ces médicaments étant généralement étroite, une telle variabilité peut avoir de graves conséquences: toxicités graves ou absence d'effet thérapeutique. Plusieurs approches pour adapter individuellement les posologies ont été proposées: a priori (basées sur l'information génétique, la taille corporelle, les fonctions d'élimination, etc.) et a posteriori (sur les informations de mesures d'exposition au médicament et/ou effets). La modélisation à effets-mixtes de la pharmacocinétique et de la pharmacodynamie (PK-PD), combinée avec une estimation bayésienne des effets individuels, est la meilleure méthode pour individualiser des schémas posologiques a posteriori. Dans cette thèse, une nouvelle approche pour ajuster les doses sur la base des prédictions données par un modèle pour les observations catégorielles de toxicité a été développée et explorée par simulation. Les aspects plus techniques concernant l'estimation des paramètres individuels ont été analysés pour déterminer les facteurs de bonne performance de la méthode. Ces travaux étaient basés sur l'exemple du syndrome mains-pieds induit par la capécitabine dans le traitement du cancer colorectal. Une revue des modèles pharmacodynamiques de données discrètes (catégorielles, de comptage, de survie) a été effectuée. Enfin, des analyses PK-PD de l'hydroxyurée dans le traitement de la drépanocytose ont été réalisées pour comparer des différentes posologies et déterminer les modalités optimales de suivi du traitement / There is high variability in response to cancer chemotherapies among patients. Its sources are diverse: genetic, physiologic, comorbidities, concomitant medications, environment, compliance, etc. As the therapeutic window of anticancer drugs is usually narrow, such variability may have serious consequences: severe (even life-threatening) toxicities or lack of therapeutic effect. Therefore, various approaches to individually tailor treatments and dosing regimens have been developed: a priori (based on genetic information, body size, drug elimination functions, etc.) and a posteriori (that is using information of measurements of drug exposure and/or effects). Mixed-effects modelling of pharmacokinetics and pharmacodynamics (PK-PD), combined with Bayesian maximum a posteriori probability estimation of individual effects, is the method of choice for a posteriori adjustments of dosing regimens. In this thesis, a novel approach to adjust the doses on the basis of predictions, given by a model for ordered categorical observations of toxicity, was developed and investigated by computer simulations. More technical aspects concerning the estimation of individual parameters were analysed to determine the factors of good performance of the method. These works were based on the example of capecitabine-induced hand-and-foot syndrome in the treatment of colorectal cancer. Moreover, a review of pharmacodynamic models for discrete data (categorical, count, time-to-event) was performed. Finally, PK-PD analyses of hydroxyurea in the treatment of sickle cell anemia were performed and used to compare different dosing regimens and determine the optimal measures for monitoring the treatment

Made available in DSpace on 2015-03-03T15:28:31Z (GMT). No. of bitstreams: 1 JoaoBC_DISSERT_partes_autorizadas.pdf: 252147 bytes, checksum: e830f27faffa86c9087da28e43e699fd (MD5) Previous issue date: 2010-05-28 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance. / Consideramos t?cnicas de predi??o baseadas em modelos de tempo de falha acelerado com efeito aleat?rio para dados de sobreviv?ncia correlacionados. Al?m do enfoque bayesiano atrav?s do Estimador de Bayes Emp?rico, tamb?m discutimos sobre o uso de um m?todo cl?ssico, o Melhor Preditor Linear N?o Viciado Emp?rico (EBLUP), nessa classe de modelos. Para ilustrar a utilidade desses m?todos, fazemos aplica??es a um conjunto de dados reais envolvendo tempos entre falhas de equipamentos de po?os de petr?leo da Bacia Potiguar. Neste contexto, o objetivo ? predizer os riscos/probabilidades de falha com a finalidade de subsidiar programas de manuten??o preventiva. Os resultados obtidos mostram que ambos os m?todos s?o adequados para prever falhas futuras, proporcionando boas decis?es em rela??o ao emprego e economia de recursos para manuten??o preventiva

Traffic safety has been considered one of the most important issues in the transportation field. Crashes have caused extensive human and economic losses. With the objective of reducing crash occurrence and alleviating crash injury severity, major efforts have been dedicated to reveal the hazardous factors that affect crash occurrence. With these consistent efforts, both fatalities and fatality rates from road traffic crashes in many countries have been steadily declining over the last ten years. Nevertheless, according to the World Health Organization, the world still lost 1.24 million lives from road traffic crashes in the year of 2013. And without action, traffic crashes on the roads network are predicted to result in deaths of around 1.9 million people, and up to 50 million more people suffer non-fatal injuries annually, with many incurring a disability as a result of their injury by the year 2020. To meet the transportation needs, the use of expressways (toll roads) has risen dramatically in many countries in the past decade. In fact, freeways and expressways are considered an important part of any successful transportation system. These facilities carry the majority of daily trips on the transportation network. Although expressways offer high level of service, and are considered the safest among other types of roads, traditional toll collection systems may have both safety and operational challenges. The traditional toll plazas still experience many crashes, many of which are severe. Therefore, it becomes more important to evaluate the traffic safety impacts of using different tolling systems. The main focus of the research in this dissertation is to provide an up-to-date safety impact of using different toll collection systems, as well as providing safety guidelines for these facilities to promote safety and enhance mobility on expressways. In this study, an extensive data collection was conducted that included one hundred mainline toll plazas located on approximately 750 miles of expressways in Florida. Multiple sources of data available online maintained by Florida Department of Transportation were utilized to identify traffic, geometric and geographic characteristics of the locations as well as investigating and determination of the most complete and accurate data. Different methods of observational before-after and Cross-Sectional techniques were used to evaluate the safety effectiveness of applying different treatments on expressways. The Before-After method includes Naive Before-After, Before-After with Comparison Group, and Before-After with Empirical Bayesian. A set of Safety Performance Functions (SPFs) which predict crash frequency as a function of explanatory variables were developed at the aggregate level using crash data and the corresponding exposure and risk factors. Results of the aggregate traffic safety analysis can be used to identify the hazardous locations (hot spots) such as traditional toll plazas, and also to predict crash frequency for untreated sites in the after period in the Before-After with EB method or derive Crash Modification Factors (CMF) for the treatment using the Cross-Sectional method. This type of analysis is usually used to improve geometric characteristics and mainly focus on discovering the risk factors that are related to the total crash frequency, specific crash type, and/or different crash severity levels. Both simple SPFs (with traffic volume only as an explanatory variable) and full SPFs (with traffic volume and additional explanatory variable(s)) were used to estimate the CMFs and only CMFs with lower standard error were recommended. The results of this study proved that safety effectiveness was significantly improved across all locations that were upgraded from Traditional Mainline Toll Plazas (TMTP) to the Hybrid Mainline Toll Plazas (HMTP) system. This treatment significantly reduced total, Fatal-and-Injury (F+I), and Rear-End crashes by 47, 46 and 65 percent, respectively. Moreover, this study examined the traffic safety impact of using different designs, and diverge-and-merge areas of the HMTP. This design combines either express Open Road Tolling (ORT) lanes on the mainline and separate traditional toll collection to the side (design-1), or traditional toll collection on the mainline and separate ORT lanes to the side (design-2). It was also proven that there is a significant difference between these designs, and there is an indication that design-1 is safer and the majority of crashes occurred at diverge-and-merge areas before and after these facilities. However, design-2 could be a good temporary design at locations that have low prepaid transponder (Electronic Toll Collection (ETC)) users. In other words, it is dependent upon the percentage of the ETC users. As this percentage increases, more traffic will need to diverge and merge; thus, this design becomes riskier. In addition, the results indicated significant relationships between the crash frequency and toll plaza types, annual average daily traffic, and drivers* age. The analysis showed that the conversion from TMTP to the All-Electronic Toll Collection (AETC) system resulted in an average reduction of 77, 76, and 67 percent for total, F+I, and Property Damage Only (PDO) crashes, respectively; for rear end and Lane Change Related (LCR) crashes the average reductions were 81 and 75 percent, respectively. The conversion from HMTP to AETC system enhanced traffic safety by reducing crashes by an average of 23, 29 and 19 percent for total, F+I, and PDO crashes; also, for rear end and LCR crashes, the average reductions were 15 and 21 percent, respectively. Based on these results, the use of AETC system changed toll plazas from the highest risk sections on Expressways to be similar to regular segments. Therefore, it can be concluded that the use of AETC system was proven to be an excellent solution to several traffic operations as well as environmental and economic problems. For those agencies that cannot adopt the HMTP and the AETC systems, improving traffic safety at traditional toll plazas should take a priority. This study also evaluates the safety effectiveness of the implementation of High-Occupancy Toll lanes (HOT Lanes) as well as adding roadway lighting to expressways. The results showed that there were no significant impact of the implementation of HOT lanes on the roadway segment as a whole (HOT and Regular Lanes combined). But there was a significant difference between the regular lanes and the HOT lanes at the same roadway segment; the crash count increased at the regular lanes and decreased at the HOT lanes. It was found that the total and F+I crashes were reduced at the HOT lanes by an average of 25 and 45 percent, respectively. This may be attributable to the fact that the HOT lanes became a highway within a highway. Moreover adding roadway lighting has significantly improved traffic safety on the expressways by reducing the night crashes by approximately 35 percent. Overall, the proposed analyses of the safety effectiveness of using different toll collection systems are useful in providing expressway authorities with detailed information on where countermeasures must be implemented. This study provided for the first time an up-to-date safety impact of using different toll collection systems, also developed safety guidelines for these systems which would be useful for practitioners and roadway users.