Ewout W. Steyerberg
Ewout W. Steyerberg
|Born||July 26, 1967|
|Alma mater||Leiden University|
|Institutions||Leiden University Medical Center, Erasmus MC|
Ewout W. Steyerberg (born July 26, 1967) is a Professor of Clinical Biostatistics and Medical Decision Making at Leiden University Medical Center and a Professor of Medical Decision Making at Erasmus MC. He has been chair of the department of Biomedical Data Sciences at Leiden University Medical Center since 2017. He has interest in a wide range of statistical methods for medical research, but is mainly known for his seminal work on prediction modelling, which was stimulated by various research grants including a fellowship from the Royal Netherlands Academy of Arts and Sciences (KNAW). Steyerberg is one of the most cited researchers in the Netherlands. He has published over 1000 peer-reviewed articles, many in collaboration with clinical researchers, both in methodological and medical journals. In January 2020, his h-index was 104 according to Web of Science, and 139 according to Google Scholar
Steyerberg started his education in medicine at the Medical Faculty of Leiden University in 1986. After obtaining his propedeuse, he initiated his education in Biomedical Sciences at the same university. In 1991, he received his MSc (cum laude). He started working towards his PhD at the Department of Public Health at Erasmus MC. His thesis, titled ‘Prognostic Modeling for Clinical Decision Making: Theory and Applications’, was completed in 1996. Subsequently, Steyerberg held a position at Erasmus Medical Centre. He spent sabbaticals at Duke University (Durham, NC: 1996) and Harvard University (Boston, MA: 2003 and 2005). In 2006, he was appointed professor at Erasmus MC, where he has been the chair of the Medical Decision Making group till the end of 2016. In 2017, Steyerberg was appointed as Chair of the Department of Biomedical Data Sciences at Leiden University Medical Center.
Steyerberg’s methodological research is mainly focussed on clinical prediction modeling. He has developed and applied advanced regression modeling and related statistical techniques for prediction in many medical domains. Other areas of interest include design and analysis of randomized clinical trials, cost-effectiveness, decision analysis, and quality of care research, all with the aim to make better decisions in health care. Contemporary research themes have his attention, including Comparative effectiveness research, Big data, Machine learning, Value-based Healthcare and Precision medicine.
Medical fields of application include oncology (e.g. testicular, bladder, prostate, esophageal, colorectal, lymphomas, and hereditary cancers); cardiovascular disease (e.g. acute myocardial infarction, heart valve replacement, limb ischemia, primary and secondary prevention of CVD); internal medicine (e.g. renovascular hypertension, osteoporosis); pediatrics (e.g. triage systems); infectious diseases (e.g. leprosy, chlamydia trachomatis screening); neurology (Guillain Barré syndrome, stroke); and traumatic brain injury (prognosis and efficiency of trial design, comparative effectiveness research, new biomarkers).
Steyerberg is known for his tremendous contribution to the field of statistical methods for prediction research. Among his most-cited articles are several methodological papers on the development and validation of clinical prediction models. In 2009, he published his book ‘Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating’. The book provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. It has become both a practical guide and reference work for anyone involved in prediction research in medicine. A second edition was published in 2019.
Steyerberg received a fellowship from the Royal Netherlands Academy of Arts and Sciences and the John M. Eisenberg Award for Practical Application of Medical Decision Making Research by the Society for Medical Decision Making in 2016. In 2019 Steyerberg was elected as member of the Royal Netherlands Academy of Arts and Sciences.
Steyerberg currently lives in Rotterdam, in the neighborhood Hillegersberg, with his wife, Aleida Steyerberg-Sluijk, a manager, and their three children Matthijs, Laurens, and Suzanne. The Steyerberg family owns a Labrador, named Bas. As an amateur runner, Steyerberg finished three marathons. His personal best, 3:51, was set at the Rotterdam Marathon in 2010. Together with his sons he is interested in cryptocurrency.
- "Ewout Steyerberg". Leiden University. Retrieved March 22, 2018.
- "Ewout Steyerberg". Erasmus MC. Retrieved March 22, 2018.
- "Citation report". Web of Science. Retrieved January 9, 2020.
- Steyerberg, Ewout W. "Prognostic Modeling for Clinical Decision Making: Theory and Applications" (PDF). Retrieved March 22, 2018.
- Steyerberg, Ewout W.; Vickers, Andrew J.; Cook, Nancy R. (2010). "Assessing the Performance of Prediction Models A Framework for Traditional and Novel Measures". Epidemiology. 21 (1): 128–138. doi:10.1097/EDE.0b013e3181c30fb2. PMC 3575184. PMID 20010215.
- Steyerberg, Ewout W.; Harrell, Frank E.; Borsboom, G.J.J.M. (2001). "Internal validation of predictive models: Efficiency of some procedures for logistic regression analysis". Journal of Clinical Epidemiology. 54 (8): 774–781. doi:10.1016/S0895-4356(01)00341-9. PMID 11470385.
- Steyerberg, Ewout W.; Eijkemans, M.J.C.; Harrell, Frank E. (2000). "Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets". Statistics in Medicine. 19 (8): 1059–1079. doi:10.1002/(SICI)1097-0258(20000430)19:8<1059::AID-SIM412>3.3.CO;2-S. PMID 10790680.
- Steyerberg, Ewout W. (2009). Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating. Springer.
- "Clinical Prediction Models". Ewout W. Steyerberg. Retrieved March 22, 2018.
- "Ewout Steyerberg". Royal Netherlands Academy of Arts and Sciences. Archived from the original on 11 April 2020.