The main aim of this thesis is to explore risk factors associated to an increased risk of adverse outcomes for heart failure (HF) patients and improve the early re-admission or mortality prediction... Show moreThe main aim of this thesis is to explore risk factors associated to an increased risk of adverse outcomes for heart failure (HF) patients and improve the early re-admission or mortality prediction in HF. Data from two studies (OPERA-HF study in the UK and SAPHIRE study in US) has been used to explore a wide range of variables as potential risk factors. We found that depression is a significant and independent predictor of all-cause mortality among HF patients. Depression was also significantly associated with recurrent events: unplanned readmission or mortality. Other psychosocial or non-clinical variables independently associated with increasing risk of recurrent events in the year following discharge after a HF hospital admission were: presence of frailty, moderate-to-severe anxiety, living alone and the presence of cognitive impairment. We then used data from the OPERA-HF study to develop a 30-day composite outcome model and to explore the added predictive value of non-clinical predictors to early outcomes: 30-day unplanned readmission or mortality. The performance of the model improved by including physical frailty and social support next to clinical variables. The transportability of the model to a different geography was proved in the external validation of the model on the SAPHIRE study data. Show less
The major challenge in analysing omic datasets is the strong dependencies which are present between samples and features. Taking into account and modelling the different dependency structures can... Show moreThe major challenge in analysing omic datasets is the strong dependencies which are present between samples and features. Taking into account and modelling the different dependency structures can lead to further improvements of our knowledge of the biological mechanisms. Therefore, improving our ability to predict diseases. This dissertation focuses on the development of new statistical methods designed to take into account the existing structures inside omic datasets by using mixed models, Gaussian graphical models, and machine learning approaches. Show less
The scope of this thesis spanned several issues in the measurement and evaluation of OD. The screening, assessment, and treatment effect for OD have been covered,with a special emphasis on... Show moreThe scope of this thesis spanned several issues in the measurement and evaluation of OD. The screening, assessment, and treatment effect for OD have been covered,with a special emphasis on patient self-evaluation. Show less
SDHD-related head and neck paragangliomas are, hereditary and generally benign, neuroendocrine tumors that arise from paraganglionic tissue associated with the parasympathetic nervous system.... Show moreSDHD-related head and neck paragangliomas are, hereditary and generally benign, neuroendocrine tumors that arise from paraganglionic tissue associated with the parasympathetic nervous system. The primary aim of this thesis was to gain more insight in the natural course of SDHD-related head and neck paragangliomas and ultimately improve surveillance and treatment strategies, as well as counseling of both patients and their family members. The risk of occult and metachronous paragangliomas, tumor growth, clinical progression and survival of SDHD germline mutation carriers were addressed. Show less
The work presented in this thesis focuses on methods for the construction of diagnostic rules based on clinical mass spectrometry proteomic data. Mass spectrometry has become one of the key... Show moreThe work presented in this thesis focuses on methods for the construction of diagnostic rules based on clinical mass spectrometry proteomic data. Mass spectrometry has become one of the key technologies for jointly measuring the expression of thousands of proteins in biological samples. However, the development of MS instrumentation gave rise to new statistical challenges in the processing and analysis of the acquired data. This is due to the complex nature of the spectral proteomic signal which is measured, as it consists of high-dimensional functions representing the within-patient proteome expression. This work considers new methods to respond to these challenges. Our main interest focuses on the comparison of mass spectral proteomic profiles collected from healthy individuals and cancer patients in the context of distinct case-control studies. A key objective in such studies is the construction of discriminant rules for distinguishing between individuals as to the presence or absence of the disease as well as for predicting the health status of future patients. We present a series of data analyses for distinct case-control cancer studies where we address these questions through the use of methodology specific for the type of data considered in each of the studies. Show less
We propose a novel classification method that integrates into existing agile software development practices by collecting data records generated by software and tools used in the development... Show moreWe propose a novel classification method that integrates into existing agile software development practices by collecting data records generated by software and tools used in the development process. We extract features from the collected data and create visualizations that provide insights, and feed the data into a prediction framework consisting of a deep neural network. The features and results are validated against conceptual frameworks that model the development methodologies as similar processes in other contexts. Initial results show that the visualization and prediction techniques provide promising outcomes that may help development teams and management gain better understanding of past events and future risks. Show less
The field of rheumatoid arthritis (RA) is moving into identification of patients as early as possible and the ultimate aim is to prevent RA becoming a chronic disease. To this end, we studied the... Show moreThe field of rheumatoid arthritis (RA) is moving into identification of patients as early as possible and the ultimate aim is to prevent RA becoming a chronic disease. To this end, we studied the phase of Clinically Suspect Arthralgia (CSA). Patients with arthralgia that were considered by the rheumatologist to have an increased risk to progress to RA (CSA) had indeed an increased risk of RA. In addition, subclinical MRI-inflammation preceded clinical arthritis with a few months. Future research will shed more light on processes underlying progression from CSA to RA and effectiveness of treatment initiation in the CSA phase. The severity of the course of RA is variable between patients and this cannot be yet accurately predicted. In this thesis, we performed studies that contributed to the understanding of these differences in severity. Three genetic risk factors for more severe joint damage progression (two non-HLA and one HLA variation) and one for arthritis persistence were identified. Further research on functional implications of the identified variants and whether they might be useful as biomarkers to guide treatment decisions is needed. Show less
Secondary prevention of recurrent venous can be achieved in two ways, either by elimination of modifiable risk factors or by extending the anticoagulant treatment period in patients at high risk... Show moreSecondary prevention of recurrent venous can be achieved in two ways, either by elimination of modifiable risk factors or by extending the anticoagulant treatment period in patients at high risk of recurrence. The aim of this thesis was to identify modifiable risk factors for as well as factors that might be able to predict recurrent venous thrombotic events. This thesis reports on an increased risk of recurrences in women who continue or start using hormonal contraceptives after a first venous thrombotic event, suggesting that refraining from this modifiable risk factor decreases the risk of recurrence. Furthermore, this thesis describes several factors, male sex, unprovoked first event, levels of coagulation factor VIII and antibiotic use to be associated with recurrent venous thrombosis. These factors should eventually be taken together and used to build a prognostic model, which will be able to predict recurrences at a refined and individual level. Show less
