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
This special issue of Reproductive Sciences is focusing on ethnic health disparity and its impact on (fe)male reproduction. Indeed, studies regarding underlying mechanisms, interventions and... Show moreThis special issue of Reproductive Sciences is focusing on ethnic health disparity and its impact on (fe)male reproduction. Indeed, studies regarding underlying mechanisms, interventions and prognosis in reproduction are underexposed for the non-White male and female. Here, we call for documentation of race and ethnicity in the analysis and management of couples with recurrent pregnancy loss. Show less
Patients with diabetes mellitus have the highest mortality risk within the dialysis population. The presence of chronic kidney disease (CKD) in patients with diabetes is also strongly related to... Show morePatients with diabetes mellitus have the highest mortality risk within the dialysis population. The presence of chronic kidney disease (CKD) in patients with diabetes is also strongly related to impaired quality of life. Research is warranted to prevent progressive diabetic kidney disease, improve quality of life and reduce mortality in this vulnerable population. In order to improve survival, more knowledge about which patients have the highest mortality risk and which risk factors and co-morbid conditions contribute to this increased mortality risk is essential. In this thesis we focussed on clinical aspects of the relation between diabetes mellitus and kidney disease, from hyperfiltration to dialysis. In chapter 2 we assessed many different measures of glucose metabolism and their association with kidney function among Dutch middle-aged adults. In chapter three and four we compared survival of dialysis patients with diabetes mellitus as underlying cause of the renal failure versus dialysis patients with diabetes mellitus as a co-morbid condition only. In chapter five we aimed to develop a prediction model for 1-year mortality in diabetic dialysis patients. Furthermore in chapter six we compared survival after amputation in diabetic dialysis patients to non-diabetic dialysis patients. Show less
In this thesis, the transition from a population-based approach to individualized therapy for the prevention of VT following lower-leg cast immobilization and knee arthroscopy is discussed.
One of the main questions in Ewing sarcoma treatment is to identify low-risk patients that can be treated with less intensive treatment so that toxicity and the occurrence of long-term adverse... Show moreOne of the main questions in Ewing sarcoma treatment is to identify low-risk patients that can be treated with less intensive treatment so that toxicity and the occurrence of long-term adverse effects can be limited while still maintaining high cure rates or to identify those patients for whom treatment is expected to have limited benefit. Furthermore, to identify high-risk patients in which treatment needs to be intensified to improve outcome. Selection of risk groups and adjusted treatment allows for early decision making, will help to improve future outcomes and assists in clinical trial design. Additionally, treatment of Ewing sarcoma is multimodal and surgery, if feasible, is crucial for curative management. However, accurate detection and localization of tumor boundaries, especially in anatomical complex locations such as the pelvic is challenging. Inadequate surgical margins lead to a higher risk of local recurrence which has major impact on oncological outcome. Developments in intra-operative imaging, like CT-based navigation systems and near infrared (NIR)fluorescence guided surgery (FGS) make accurate defining and localization of surgical margins possible. They represent a whole new field of precision medicine and provide new treatment options for patients, thereby improving function outcome and healthcare quality. Show less
Postpartum haemorrhage, in this thesis defined as blood loss above 1000mL within the first 24 hours after birth, remains a major cause of maternal morbidity and mortality with an incidence that... Show morePostpartum haemorrhage, in this thesis defined as blood loss above 1000mL within the first 24 hours after birth, remains a major cause of maternal morbidity and mortality with an incidence that seems to be increasing over the last decade. In this thesis we focussed on improvement of prognostic and diagnostic strategies for major obstetric haemorrhage, which may subsequently lead to a reduction of severe maternal morbidity, mortality and need for surgical interventions. In pursuit of this aim, research questions were posed corresponding to all three phases leading up to adverse outcome due to postpartum haemorrhage: pregnancy (prior to childbirth), early postpartum haemorrhage and persistent postpartum haemorrhage. In the first part of this thesis we focused on prediction of postpartum haemorrhage.Bleeding assessment tools were found to have no predictive value for postpartum haemorrhage. The change of coagulation parameters during the course of postpartum haemorrhage was described, and fibrinogen was found to be an early predictor of a worse outcome of postpartum haemorrhage. The association between fibrinogen measured by the Clauss method and ROTEM Fibtem was described in this thesis. Show less
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
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
