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
Seeters, T. van; Biessels, G.J.; Kappelle, L.J.; Schaaf, I.C. van der; Dankbaar, J.W.; Horsch, A.D.; ... ; Dutch Acute Stroke Study DUST Inve 2016
Chronic pain is a significant health problem that greatly impacts the quality of life of individual patients and imparts high costs to society. Despite intense research effort and progress in our... Show moreChronic pain is a significant health problem that greatly impacts the quality of life of individual patients and imparts high costs to society. Despite intense research effort and progress in our understanding of the mechanistic and molecular basis of pain, chronic pain remains a significant clinical problem that has few effective therapies Throughout the various chapters we have highlighted some important conceptual and experimental flaws in the way that pain signalling and pharmacological activity are characterised and translated across species and disease conditions. The common denominator of the work presented here is the requirement for accurate characterisation of exposure-response relationships, without which the dose rationale for the progression of a molecule cannot justified, whether drugs are aimed at symptomatic relief, disease modification or prophylaxis. In addition to a comprehensive review of the mechanisms underlying pain signalling and symptoms, the work developed here focuses on three different aspects of research underpinning the use of pharmacokinetic-pharmacodynamic relationships. First, we have explored the requirements for the characterisation of behavioural measures of pain during the early screening of candidate molecules, shedding light onto the shortcomings of experimental protocols commonly used in preclinical research. Then we introduced the prerequisites for the parameterisation of pain behaviour to ensure accurate translation of the pharmacological properties across species as well as for bridging across different phases of development. Lastly, an attempt was made to model clinical response in chronic inflammatory pain and to establish correlations between symptom improvement and the underlying pharmacological effects using biomarkers. In addition our work showed how clinical trial simulations can be used as a design tool, enabling the evaluation of a variety of scenarios that disentangle the contribution of pharmacology from the confounding effects of placebo and disease dynamics. Show less