About
We are a multidisciplinary research & education group focused on epidemiology. This is the discipline that investigates the dissemination and determinants of disease and health in human populations. Epidemiology is indispensable in applied clinical and public health research.
Contact
Scope and scope of work
We seek to improve lifestyle, well-being and health of the (Dutch) population, specifically with respect to cancer-related and perinatal outcomes.
Read moreScope and scope of work
The mission of the Epidemiology R&D group is to improve lifestyle, well-being and health of the (Dutch) population, specifically with respect to cancer-related and perinatal outcomes, through high-quality and innovative epidemiological research and education.
Our research focuses on developing and improving strategies in etiology, prevention, early detection, prognosis, prediction and (quality of) care. We apply both observational and interventional methods. We work multidisciplinary where possible, increasing the chances of (clinical) embedding of the results after a research project.
Our ambition is to teach students, PhD students and other clinical and biomedical researchers state-of-the-art methods of applied medical scientific research and epidemiology. Through education and consultation, we enable students and researchers to conduct and evaluate applied scientific research in a sound manner. In doing so, we contribute to improving the scientific quality of research at Radboudumc and beyond.
Chairs/RGL's
- Cancer epidemiology - Bart Kiemeney
- View Radboudumc profile page and view research group
- Genetic epidemiology - Sita Vermeulen
- View Radboudumc profile page and view research group (link will follow)
- Personalized cancer screening - Mireille Broeders
- View Radboudumc profile page
Projects
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For etiological and prognostic research, we collect DNA and clinical information from children with congenital disorders and their parents. Mothers also complete a questionnaire about conditions during pregnancy.
More information on the projectwebsite.
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The ARM-Net Consortium is a group of professionals and patient representatives. The aim is to share data and knowledge for the purpose of research on congenital anorectal malformations and improvement of clinical care.
More information can be found at the projectwebsite.
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Using information and material from the AGORA databank and biobank, we are conducting research in a consortium with 4 other UMCs on the aetiology and prognosis of congenital kidney and urinary tract disorders.
More information can be found on the projectwebsite.
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Using information and material from the NBCS and UroLife biobank, among others, we investigate the genetic and molecular factors influencing the response to BCG immunotherapy in bladder cancer.
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In this project we aim to optimize follow-up for prostate cancer patients according to their individual risk of biochemical recurrence, late adverse effects of treatment and health-related quality of life.
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In collaboration with Aarhus University, we are developing a mixed model for application in genome-wide association studies (GWAS). This will be implemented in the LDAK software.
More information can be found on the projectwebsite.
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Within this project, we are looking for rare, inherited DNA variants that cause familial bladder cancer and bladder cancer at a very young age.
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Within the GWAS consortium for non-muscle-invasive bladder cancer, we use Mendelian Randomisation (MR) analyses to understand the relationship between body composition and outcomes in non-muscle-invasive bladder cancer.
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In this European project, we are analysing clinical and -omics data from many biobanks and conducting lab experiments to better understand relevant tumour-host interactions in melanoma, bladder and lung cancer.
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The NBS is a reference population for research on the role of genetic variation, lifestyle and environmental factors in health and disease. The NBS includes questionnaire data for ~9500 individuals and lab values for ~6500 individuals. In addition, there is genetic data from ~5500 individuals.
More information can be found at the projectwebsite.
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To investigate the role of lifestyle, clinical, and genetic and molecular factors in relation to bladder cancer risk and progression, this biobank with information and material from 2,500 bladder cancer patients was set up.
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In this multicenter randomized controlled trial, we investigate the additional beneficial value of FDG PET-CT in the follow-up of lung cancer patients.
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Personalized care in oncology: in this consortium, we develop the next generation of AI models for shared decision making in oncology.
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The aim of the PREFER study is to investigate whether we can make the population screening for cervical cancer more 'tailored' by including the risk of cervical cancer in which follow-up tests are carried out and how often they are done.
More information can be found at the projectwebsite.
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The PRIDE (PRegnancy and Infant DEvelopment) Study is a large survey of pregnant women in the Netherlands. These women and their children are followed for a longer period to discover factors that influence the health of mother and child.
More information can be found at the projectwebsite.
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In this study, we collected data on risk factors for breast cancer. By modelling, we look at the effect of offering the high-risk group a more extensive and the low-risk group a less extensive population screening.
More information can be found at the projectwebsite.
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In this project we identified a subset of the Patient Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) for standardized symptom monitoring in rectal cancer.
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ReLife is a multicentre prospective cohort study of 368 people with localised kidney cancer on the relationship lifestyle, clinical outcomes and quality of life.
More information can be found at the projectwebsite.
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This cohort study in the Dutch population-based breast cancer screening aims to determine the short- to long-term effect of tomosynthesis, replacing digital mammography, in population-based breast cancer screening.
More information can be found at the projectwebsite.
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In this project, we develop a risk-stratified follow-up care model for lung cancer patients.
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UroLife is a multicentre prospective cohort study of over 1,500 people with non-muscle-invasive bladder cancer on the relationship lifestyle, clinical outcomes and quality of life.
More information can be found at the projectwebsite.
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In this project, we develop a group-based multitrajectory model to identify clusters of patients with distinct symptom development over time.
Initial education
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This course focuses on understanding and applying advanced methods of causal inference in observational research.
The basic concepts in causal inference, including causal identification criteria, will be discussed. You will gain hands-on experience with creating your own causal models using the Directed Acyclic Graph (DAG) frameworks.More information can be found here.
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BMS17 is focused on big, population-based genome association studies. Do you want to understand the design, analysis, and results of these studies? And do you want to be able to perform a genome data association analysis and identify disease-related DNA variants yourself? Then this is the right course for you.
More information can be found here.
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The main objective of this course is to gain a clear understanding in methods of biological sample collection for the use of biomarkers in health-related research questions, taking into account validity, reproducibility, feasibility, and efficiency. Students will also gain practical experience by designing the preanalytical phase of a population-based study.
More information can be found here.
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Prediction models are the cornerstone of personalized medicine. During this course students will learn the concepts of traditional epidemiological prediction models and learn how to build one themselves. From there they learn the ‘machine learning language’ and how the methods compare to traditional epidemiological prediction models. Next, they will learn to create and evaluate a prediction model using advanced statistical techniques and machine learning algorithms (e.g. random forest, support vector machines).
More information can be found here.
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In this course multivariable linear and logistic regression models are considered for association and prediction studies. It is explained how to build models, estimate the parameters and how to interpret the results of the analyses. The package R is used.
More information can be found here.
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This course encompasses the fields of reproductive epidemiology and toxicology, covering the entire spectrum from fertility and subfertility through pregnancy complications to adverse perinatal outcomes (e.g. preterm birth and low birth weight) and birth defects in offspring, as a result of exposure to non-genetic risk factors and gene-environment interaction.
More information can be found here.
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This course focuses on innovative research approaches within the theme urological cancers, with special attention to translational relevance, i.e. the implementation of new diagnostic and therapeutic interventions in an academic clinical setting.
More information can be found here.
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This course focuses on providing the students with a clinical view on women’s cancers, i.e. gynecological cancer and breast cancer. It will also challenge the students to formulate existing clinical questions in a research project. By doing so we aim to show the relevance of collaborating with people in the medical field, gathering the necessary information, clarifying the problem and developing an appropriate research proposal.
More information can be found here.
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In this course you will learn how to design an applied medical research study in a valid and efficient manner. The basic knowledge of observational study designs and intervention studies will be rehearsed, deepened and broadened. In addition, you will learn about alternative study designs like nested case-control, case-cohort studies and stepped wedge trials. The course also focusses on concepts as bias, validity, and causality.
More information can be found here.
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The quality and results of most studies depend heavily on the quality of the data. This course addresses both theory and practice of modern data collection methods for quantitative health-related research, which will enable the students to properly design their own data collection and assess the quality of data collected by others.
More information can be found here.
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The overall aim of the course ‘Applied medical research and society’ is to bridge the gap between medical research and society and provide you with the tools to succeed in this. You will learn to choose which epidemiological impact measures to use in certain situations to give a balanced view and provide the most appropriate information for the general public, (health) professionals, or policy makers.
More information can be found here.
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In this course we will discuss advanced statistical methods that are used to address biomedical and epidemiological research questions that require the collection and analysis of clustered data. In this course, multilevel analyses, longitudinal data analyses, and multilevel survival analyses will be taught. The computer package R will be used for the analysis of data from a range of research contexts in order to obtain practical experience.
More information can be found here.
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The course comprises an interactive mix of learning and teaching. The learning aids for making your Plan of Work, which is your end product of CKO9, are presented on Brightspace. You are in control of your own project and are given assistance with defining the topics of your research by your peers through peer review. We designed seminars to stimulate this peer review process. Through interaction with fellow students, the teacher and, later on, your supervisor, the process of critical reflection on your own study will be reinforced.
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In (bio)medical research we collect and use information from and about humans. You will be introduced to various methods for data collection in humans, for example by physical examination. You will perform some anthropometric measurements yourself.
More information can be found here.
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This course deals with etiological research designs and measures of association and impact, all applied to research on pregnancy outcomes or fertility.
More information can be found here.
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In this CSI module, you will learn the basics of intervention research along with the basic concepts of research design, research ethics and data analysis. You will learn this by setting up your own RCT (in theory) on the effect of an intervention with caffeine and then by processing data collected in previous years from such an intervention.
More information can be found here.
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Good research requires you to be critical of how you design and conduct research and how you interpret and present your results. Does my work meet all research methodological and research ethical standards and values? Am I critical of mistakes I may make in the process?
More information can be found here.
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In this module you will study theory about associations, causal relations, validity and bias and convert this theory into practice.
You will also perform descriptive and association analyses in your own data, which were collected by you and other BMS students during Q1 – Q3. All these data are merged into a student research database.More information can be found here.
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Diagnosis is central to medical practice. It refers to knowing about the health status of a person. In this module you will learn about diagnosis of cancer: which tests are available, and how do they perform in clinical practice? You will learn about measures to describe the performance of a diagnostic test, such as sensitivity, specificity and diagnostic value. Furthermore, we will discuss screening programs for cancer.
More information can be found here.
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In this module for students in BMS, three computer assignments deal with the methodology of etiological and prognostic research. Students also learn how to report their findings through a scientific abstract.
More information can be found here.
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In the Netherlands almost 1 out of 20 persons will be diagnosed with colorectal cancer in their lifetime. Since 2014 the Netherlands has implemented a population-based screening programme for colorectal cancer. This module takes this screening programme as an example to elaborate on the possibilities and pitfalls of early diagnostics.
More information can be found here.
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The minor Biomedical Research Methods is specifically designed for premaster students of Biomedical Sciences. In this minor students will learn most of the research content that regular BMS bachelor students learned during their first 1,5 years of study. It is about human-based research in populations.
More information can be found here.
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This minor focuses on the application of genetic, epidemiological, and bioinformatic tools in (bio)medicine. In other words: To use the information contained within the genome of patients to understand and diagnose diseases, and (when possible) define strategies for prevention, treatment and/or curing these diseases.
More information can be found here.
Post-initial education
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This course focusses on the design of scientific research. Topics include choosing appropriate designs for a research question, advanced designs for randomized, non-randomized trials and observational studies, selecting study population and applying sampling methods, different types of biases and models for causality.
More information can be found here.
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Three-day course developed for PhD students in the Department of Genetics (and SD Medical BioSciences), focusing on basic statistical concepts and analyses, working in Linux, and when and how to seek help for epidemiological and statistical questions.
Consultancy/services
If you are interested in consultations or services from a R&E group, please fill in our application form: aanvraagformulier
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Radboudumc researchers can consult epidemiologists on research design and conduct, study designs, data collection, data management, analysis, and interpretation and implementation.
Registration Epidemiologist A and B
National registration as Epidemiologist A or B is possible for scientifically trained and practice-trained epidemiologists who are able to function in epidemiological research and education, in counselling or in policy preparation concerning (public) health problems. Discuss training and registration opportunities with accredited Epidemiology trainer Dr Femmie de Vegt (e-mail).
See also: