I am a statistician (MSc and PhD) with a strong interest in epidemiology and health related topics. I am particularly interested in contributing to building bridges between epidemiological research and statistical methods, and in encouraging researchers to use non-traditional approaches in analysing data.
The main area of interest of my thesis was the nested case-control design. My thesis aimed to refine and extend the scope of the weighted likelihood approach in nested case-control data analysis by investigating the advantages of this method as an alternative to the traditional conditional logistic regression. The weighted likelihood approach showed several advantages compared to the traditional conditional logistic regression in nested case-control data analysis, which reinforced, refined and extended what had been previously shown in the literature.
I am currently working as a statistician in the Unit of Clinical Epidemiology at the Department of Medecine of the Karolinska Institute. I am involved in studies related to chronic inflammatory diseases.
- 2017, PhD (Medicine). Title of my thesis : Efficient Design and Analysis of Extended Case-Control Studies.
- 2005, certificate of pedagogic ability at higher level education (CAPAES), Université Libre de Bruxelles, Belgium.
- 1998, complementary Master in Statistics (2 years), Université Libre de Bruxelles, Belgium.
- 1991, complementary Master in Hospital Physics (2 years), Université Catholique de Louvain, Belgium.
- 1989, MSc (Physics), Université Catholique de Louvain, Belgium.
The title of my thesis is "Efficient design and analysis of extended case-control studies". Using weighted partial likelihood methods in the analysis of nested case-control data, I addressed the following topics:
- Reusing data from nested case-control design to address a new research question.
- Estimating baseline hazard and absolute risk from nested case-control data.
- Mitigating a problem of overmatching and handling clustered data in nested case-control design
- Performing valid subgroups analysis in nested case-control studies
- Delcoigne B, Colzani E, Prochazka M, Gagliardi G, Hall P, Abrahamowicz M, Czene K, Reilly M. Breaking the matching in nested case-control data offered several advantages for risk estimation. J Clin Epidemiol. 2017;82:79-86.https://www.ncbi.nlm.nih.gov/pubmed/27923734
- Salim A, Delcoigne B, Villaflores K, Koh WP, Yuan JM, van Dam RM, Reilly M. Comparisons of risk prediction methods using nested case-control data. Stat Med. 2017;36(3):455-465. https://www.ncbi.nlm.nih.gov/pubmed/27734520
- Delcoigne B, Hagenbuch N, Schelin ME, Salim A, Lindström LS, Bergh J, Czene K, Reilly M. Feasibility of reusing time-matched controls in an overlapping cohort. Stat Methods Med Res. 2016 Sep. pii: 0962280216669744. https://www.ncbi.nlm.nih.gov/pubmed/27659169
I have a considerable experience in teaching statistics to undergraduate students at both University (Faculty of Medecine) and University College levels (Department of Paramedical Studies) in my home country (Belgium) for 15 years.
I have been involved in the following teaching activities at graduate and undergraduate levels since 2013 at KI and other Universities:
- Basic courses in statistics at KI (biostat I and VetU)
- Logistic regression at KI (biostat II)
- Survival analysis at KI (biostat III)
- Extensions to the design and analysis of case-control studies at University of Milano-Bicocca