The research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency,... Show moreThe research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency, which is evaluated based on donors' hemoglobin and ferritin levels. If either of these levels are inadequate, donors are deferred from donation. Deferral due to low hemoglobin levels occurs on-site, meaning that donors have already traveled to the blood bank and then have to return home without donating, which is demotivating for the donor and inefficient for the blood bank. A large part of this dissertation therefore has the objective to develop a prediction model for donors' hemoglobin levels, based on historical measurements and donor characteristics.The prediction model that was developed reduces the deferral rate by approximately 60\% (from 3\% to 1\% for women, and from 1\% to 0.4\% for men), showing the potential of using data to enhance blood bank policy efficiency. Additionally, the model predictions were made explainable, providing the blood bank with insights into why specific predictions are made. These insights increase our understanding of the relationships between donor characteristics and hemoglobin levels. If this prediction model would be implemented in practice, the explanations could also be shared with the donor to help them understand why they are (not) invited to donate, which could also contribute to donor satisfaction and retention.In a collaborative effort with blood banks in Australia, Belgium, Finland and South Africa, the same prediction model was applied on data from each blood bank. Despite differences in blood bank policies and donor demographics, the models found similar associations with the predictor variables in all countries. Differences in performance could mostly be attributed to differences in deferral rates, with blood banks with higher deferral rates obtaining higher model accuracy.Beyond hemoglobin prediction models, additional research questions are explored. One study aims to identify determinants of ferritin levels in donors through repeated measurements, and linking these to environmental variables. Another study involves modeling the pharmacokinetics of antibodies in COVID-19 recovered donors, and finding relationships between patient characteristics, symptoms, and antibody levels over time.In summary, the research in this dissertation shows the potential within the wealth of data collected by blood banks. The proposed data-driven donation strategies not only decrease deferral rates but also increase donor retention and understanding. This comprehensive approach allows Sanquin to provide more personalised feedback to donors regarding their iron status, ultimately optimising the blood donation process and contributing to the overall efficacy of blood banking systems. 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
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
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
H2: Hensgens MP, Goorhuis A, Notermans DW, van Benthem BH, Kuijper EJ. Decrease of hypervirulent Clostridium difficile PCR ribotype 027 in the Netherlands. Euro Surveill. 2009 H3: Hensgens MP,... Show moreH2: Hensgens MP, Goorhuis A, Notermans DW, van Benthem BH, Kuijper EJ. Decrease of hypervirulent Clostridium difficile PCR ribotype 027 in the Netherlands. Euro Surveill. 2009 H3: Hensgens MP, Keessen EC, Squire M, Riley TV, Koene MG, de Boer E, Lipman LJ, Kuijper EJ. Clostridium difficile infection in the community: a zoonotic disease? Clin Microbiol Infect. 2012 H4: Hensgens MP / Goorhuis A, van Kinschot CM, Crobach MJ, Harmanus C, Kuijper EJ. Clostridium difficile infection in an endemic setting in the Netherlands. Eur J Clin Microbiol Infect Dis. 2011 H5: Hensgens MP, Goorhuis A, Dekkers OM, Kuijper EJ. Time-interval of increased risk for Clostridium difficile infection after exposure to antibiotics. J Antimicrob Chemother. 2012 H7: Hensgens MP, Goorhuis A, Dekkers OM, van Benthem BH, Kuijper EJ. Outcome of nosocomial Clostridium difficile infections; results of a multicenter cohort study. Clin Infect Dis. 2013 H8: Hensgens MP / Bauer MP, Miller M, Gerding DN, Wilcox MH, Dale AP, Fawley WN, Kuijper EJ, Gorbach SL. Renal failure and leukocytosis are predictors of a complicated course of Clostridium difficile infection (CDI) if measured on day of diagnosis. Clin Infect Dis. 2012 H9: Hensgens MP, Kuijper EJ. Clostridium difficile infection due to binary toxin positive strains. Emerg Infect Dis. 2013 H10: Hensgens MP, Dekkers OM, Goorhuis A, Le Cessie S, Kuijper EJ. Predicting a severe course of Clostridium difficile infection at the bedside. Clin Microbiol Infect. 2012 Show less
Major advances have been made in the treatment of rheumatoid arthritis, a potentially chronic disabling disease which poses a large burden on both patients and society. By early start of disease... Show moreMajor advances have been made in the treatment of rheumatoid arthritis, a potentially chronic disabling disease which poses a large burden on both patients and society. By early start of disease-modifying antirheumatic drugs, including methotrexate as a prominent drug, the use of combination therapies including prednisone or biologicals, and tight control of disease activity, many patients are able to reach a state of clinical remission and some can even taper and stop antirheumatic therapy. Challenges lie in correctly identifying the earliest manifestations of the disease, starting the right treatment sufficiently early, tailored to the individual patient, and setting the optimal treatment goal at which to steer therapy adjustments. This thesis has made a start towards tackling several of these challenges and discusses further necessary steps that may lead to a fundamental change in the outlook of patients with rheumatoid arthritis. Show less
Text-mining is a challenging field of research initially meant for reading large text collections with a computer. Text-mining is useful in summarizing text, searching for the informative documents... Show moreText-mining is a challenging field of research initially meant for reading large text collections with a computer. Text-mining is useful in summarizing text, searching for the informative documents, and most important to do knowledge discovery. Knowledge discovery is the main subject of this thesis. The hypothesis that knowledge discovery is possible started with the work done by Swanson. He made, as a first finding, links between Raynaud__s disease and fish oil using intermediate medical terms to relate them to each other. This principle was formalized in the AB- C concept. A and C are not directly related to each other but via an intermediate concept B that needs to be discovered. Tex data can be extended by adding other non textual data such as microarray experiments. Then we are in the field of data-mining. The final goal is to do all kinds of discoveries with computer (in silico) using data sources in order to assist biology research to save time and discover more. Show less
As the de facto industry standard for software modeling, the Unified Modeling Language (UML) is used widely across various IT domains. UML__s wide acceptance is partly because the language offers... Show moreAs the de facto industry standard for software modeling, the Unified Modeling Language (UML) is used widely across various IT domains. UML__s wide acceptance is partly because the language offers flexibility and freedom in modeling software systems: 1) UML provides an extensive set of modeling notations that can be used to model various concepts; 2) UML can be used both in a casual and formal manners. In the context of model-driven software development, the degree of freedom in which UML is used raises an important issue related to model quality. Different styles and rigors in using UML affect the quality of the resulting models. It is then logical to think that the level of quality of the UML model may affect the quality of the resulting software. This thesis reports on a series of empirical studies performed to address a pivotal question concerning the benefits of UML modeling in software development, particularly from a quality perspective. The results of these empirical studies show that the use of UML provides benefits in terms of increased quality and productivity in software development. The availability of UML models also allows early prediction of defects in software systems. Such prediction is potentially useful for identifying and fixing defects early during software development, and for prioritizing testing. Show less
This thesis investigated the association between several genetic factors and autoantibodies and the development of undifferentiated arthritis (UA) and rheumatoid arthritits (RA). Second, this... Show moreThis thesis investigated the association between several genetic factors and autoantibodies and the development of undifferentiated arthritis (UA) and rheumatoid arthritits (RA). Second, this thesis described a prediction model that estimates the chance to progress from UA to RA. The most important genetic risk factor for RA are the HLA-Class II alleles that encode for a common amino acid sequence, called the ‘Shared Epitope’. Investigating the progression to RA from UA revealed that the HLA-Shared Epitope alleles are not primarily a risk factor for RA but for the presence of anti-CCP antibodies, that are known to be specific for RA. Smoking in the presence of HLA-Shared Epitope alleles particularly increased the risk on anti-CCP-positive RA.. The HLA-DR3 alleles were associated with anti-CCP-negative RA. The presence of HLA-alleles encoding for D70ERAA correlated with a lower risk on RA and a less severe disease course. The presence of the PTPTN22 T-allele conferred an increased risk for both UA and RA. The knowledge on risk factors for RA-development was translated in a model that estimates the chance to progress to RA in patients that present with UA by using 9 clinical variables. The discriminative ability was high and this model allows individualized treatment decisions in UA. Show less
In this thesis novel statistical methods are developed for the analysis of high dimensional microarray data. In short: Chapter 1 gives an overview of the most important research methods developed... Show moreIn this thesis novel statistical methods are developed for the analysis of high dimensional microarray data. In short: Chapter 1 gives an overview of the most important research methods developed so far. Chapter 2 describes a method for testing association of the expression of gene sets (pathways) with a patient level response variable, which can be continuous or two-valued. Chapter 3 extends the methodology of chapter 2 to survival as a response variable. Chapter 4 presents a goodness-of-fit test for the multinomial regression model, which can be used to extend the methodology of chapter 2 to multi-valued outcomes. Chapter 5 presents a general theoretical framework in for the tests of chapters 2-4 and derives optimality properties for these tests. Chapter 6 presents a method for predicting a response variable from high dimensional data, based on latent variables. Chapter 7 presents a visualization tool for improved presentation of scatterplots with many thousands of dots. Show less
