Veerle Coupé (Chair)
Veerle Coupé is astronomer by training with a MSc degree in Clinical Epidemiology and a PhD degree in Medical Decision Sciences. Her research concerns mathematical modeling of the development and progression of cancer, in order to predict clinical and economic outcomes of prevention, diagnostics, and treatment. She built micro-simulation models for the evaluation of screening for colorectal cancer and cervical cancer and for the evaluation of treatments in melanoma and lung cancer. She currently supervises PhD students who are modelling diagnosis and treatment of lung cancer, melanoma and colorectal cancer. Furthermore, Veerle Coupé teaches in the area of statistical methodology, mathematical modeling and cost-effectiveness.
Hans Berkhof (Co-chair)
Hans Berkhof is chair of the department of Epidemiology and Biostatistics at the VU University Medical Center and is a researcher in the field of disease modeling and statistics. His research focuses on the development of mathematical decision models and integration of evidence from multiple sources. He has developed HPV disease and transmission models and has advised national health decision makers on HPV screening and vaccination issues. He also teaches in the area of modeling, screening and prevention.
Tim van de Brug
Tim van de Brug focuses his research on statistical methodology for neuroimaging and high-dimensional data analysis. He also does statistical consultancy for various departments within VUmc. Before, he has worked as an Assistant Professor at the Department of Mathematics of VU University. He did research on probability theory and statistical physics and has been a speaker at conferences in Vancouver, Abu Dhabi, India, Brazil, Buenos Aires and Europe. At VU, he lectured several courses in statistics and data analysis. Earlier, he has worked a couple of years at ABN AMRO Asset Management. There he built simulation models for forecasting and optimizing the performance of quantitative investment strategies, and decision support software for the portfolio management processes. Tim holds a PhD in Mathematics from VU.
Birgit Lissenberg-Witte studied Mathematics with a major in Statistics at the VU University Amsterdam and obtained her PhD degree in Mathematical Statistics at the Delft University of Technology. During her PhD research, she developed nonparametric methods to estimate the cumulative incidence of asymptomatic diseases, in particular the incidence of viral infections (HIV and Hepatitis A), and focussed on mathematical properties of these estimation methods. Her current research aims at more applied methodology in health science. She developed algorithms for more accurate estimation of cumulative incidence by correcting for misclassification of events due to limited accuracy of screening tests. Furthermore, she is involved in clinical decision research as a statistical consultant. Birgit teaches in the area of statistical methodology.
Peter van de Ven
Peter van de Ven holds MSc degrees in Engineering Mathematics (Eindhoven University of Technology) and Health Psychology (Tilburg University) and a PhD degree in the area of statistics (Eindhoven University of Technology). After holding postdoctoral positions at the University of Southampton and TNO Quality of Life, he joined the department of Epidemiology and Biostatistics of VU University Medical Center in 2009. His current research focusses on efficient study designs for comparison of the performance of diagnostics and screening instruments and the design of Bayesian adaptive clinical trials for targeted treatment. Furthermore, he acts as a statistical consultant and is a member of the hospital’s ethical review board.
Janneke Wilschut studied econometrics at VU University Amsterdam and obtained a PhD degree in health economics in 2012. She did her PhD research at the department of Public Health of Erasmus University Medical Center Rotterdam, where she used a micro-simulation model to estimate costs and effects of colorectal cancer screening. After her PhD she applied productivity analysis to answer policy questions related to the efficiency of the public sector. Her current research focuses on the modeling of disease in order to optimize the allocation of medical resources. She is also a statistical / methodological consultant and teaches in the area of statistics.
Marjolein Greuter has a MSc degree in Research in Health Sciences from VU University Amsterdam, with a focus on health economic modeling. She is also a registered Epidemiologist. She completed her PhD on the ASCCA project (VU University Medical Center), which aimed to use micro-simulation to predict health effects and costs of population-based screening strategies for colorectal cancer (CRC). She has constructed a disease model that describes the natural history of CRC and used this model to predict the long-term health effects of the recently implemented Dutch colorectal cancer screening programme. Her current research focuses on the potential of biomarkers in CRC screening and surveillance. Besides her research, she teaches in the area of health economics and basic statistics.
Thomas Klausch is a post-doctoral researcher in biostatistics specializing in the fields of predictive modeling (statistical learning) and causal inference. Before joining VUmc, Thomas was a post-doc at the Department of Methodology and Statistics at Utrecht University, where he also received his PhD degree. His PhD thesis focused on methods for estimating and adjusting errors in survey statistics. In this time, he was additionally a fellow at the methodology section of Statistics Netherlands (Centraal Bureau voor de Statistiek). In his current research, he focusses on methods for estimating optimal treatment strategies using patient registry data. He is involved in EU project BD2Decide where he collaborates in an international network on a clinical support system for treatment decision making. Furthermore, he acts as statistical consultant to researchers at VUmc.
Simone Rauh has a MSc degree in Research in Health Sciences from VU University Amsterdam, with a focus on clinical prediction modeling. Her PhD research (VU University Medical Center) focuses on the application of clinical prediction models and the identification of potential risk factors in observational cohort studies, including the development, internal and external validation and updating of prediction models. Her current research focusses on the development of decision support tools in non-small cell lung cancer and on the comparison of individualized care versus a population-based approach. Furthermore, Simone teaches in the area of statistical methodology and clinical prediction modeling.
Andrea Bassi holds a MSc in Engineering Mathematics (Polytechnic University of Milan), with a focus on Applied Statistics. After having worked in Italy as a statistical consultant, he started his PhD training at the VU University Medical Center, on the BIOMARKER project. The goal of this project is to make all the necessary preparations for running and analyzing a Bayesian adaptive clinical trial to decide on the optimal targeted treatment strategy for patients with diffuse large B-cell lymphoma (DLBCL), a very heterogeneous disease. Due to their flexibility, Bayesian-adaptive trials are more suitable than standard randomized clinical trials for finding optimal targeted treatment strategies for diseases where patients with different characteristics may benefit from different treatments.
Federica Inturrisi studied Biology at the University of Catania and received her MSc degree in Molecular Biosciences, major Cancer Biology, from the University of Heidelberg and DKFZ. She also holds a MSc degree in Epidemiology and Biostatistics. After having worked on STI-related projects and in particular in the field of infection and cancer, she started her PhD at the VU University Medical Center in Amsterdam. The aim of the project is to evaluate benefits, harms and cost-effectiveness of the risk-stratification strategy as foreseen in the new Dutch HPV-based cervical cancer screening program implemented in 2017.
Gabrielle Jongeneel studied health sciences at the VU University Amsterdam and received her MSc degree in health policy. During her master degree she developed a special interest in health economic modeling. She recently started her PhD at the VU University Medical Center in Amsterdam on the PATTERN project. The aim of the project is to evaluate the selection of stage II colon cancer patients for adjuvant treatment to improve the long-term health benefits and effectiveness of new molecular selection strategies by using a decision model. Besides her project, Gabrielle teaches in basic statistics and methodology.
Natalia R Kunst
Natalia R Kunst holds two MSc degrees, one in European Studies with a major in Economics and EU Finance (Gdansk University of Technology) and another in Management with a major in Accounting and Finance (Gdynia University). She has been working as a health economic consultant performing model-based evaluations for HTA purposes and developing decision-analytic models in many therapeutic areas such as oncology, neurology and immunology. Currently, she is pursuing a PhD at the University of Oslo in collaboration with the VU University Medical Center in Amsterdam. Her PhD focuses on the inclusion of real-world data in decision-analytic modeling using the case of metastatic colorectal cancer. In the project, she utilizes extensive data coupled from several Norwegian registries. Building a disease simulation model, investigating the disease patterns and performing cost-effectiveness analyses for treatment and diagnostics, are three of the main tasks of the project.
Ingrid van Maurik
Ingrid van Maurik studied Health and Life Sciences at the VU University Amsterdam and received her MSc degree in Clinical Neuropsychology at Leiden University. She is currently doing a PhD at the VUmc Alzheimercenter on the ABIDE project, in collaboration with the department of epidemiology and biostatistics. The general aim of ABIDE is to enable the (cost)effective application of MRI, CSF, and PET diagnostic tests for Alzheimer’s Disease (AD) and its predecessor Mild Cognitive Impairment (MCI) in clinical practice (in secondary and tertiary care). In addition, ABIDE aims to develop individual risk estimates in MCI patients for (time to) progression to dementia.
Venetia Qendri studied Mathematics at the National and Kapodistrian University of Athens and received her MSc degree in Health Economics from the Erasmus School of Economics. At present, she is working as a PhD student in biostatistics at the VU University Medical Center, involved in the EU funded project CoheaHr. The aim is to compare health interventions for the prevention of
HPV-related cancer and to identify optimal strategies for the integration of the HPV-vaccination and screening on the basis of HPV transmission and cancer progression models.
Harold Wolff studied Bio-Medical sciences, with extra-curricular courses in medicine, computer sciences, chemistry and physics, and obtained his MSc degree in Systems Biology at the VU University Amsterdam. After his MSc, he worked as a research assistant at the University of Pittsburgh and as a pre-doc at the Centrum Wiskunde & Informatica (CWI) on a bio-physical tissue simulation model. He is currently doing a PhD at the VU University Medical Center on a micro-simulation model of non-small cell lung carcinoma (NSCLC). This model aims to predict long-term health-effects and cost-effectiveness of diagnostics and treatments in NSCLC.
Carolien Ruijgrok has a MSc degree in Health Sciences from the VU University Amsterdam, with a focus on policy and organization of health care and economic evaluations. At present, she is working on an embedded PhD project at the VU University Medical Center in Amsterdam and Unilever R&D in Vlaardingen. The aim of this project is to develop a health impact model of the relationship of two dietary approaches with diabetes risk factors and diabetes incidence for the prevention of type 2 diabetes mellitus. The model outcomes can be used for guidance for public health policies. Moreover, she teaches in courses in basic statistics and methodology.