Dr. Tsilidis is a Senior Lecturer in Cancer Epidemiology in the Department of Epidemiology and Biostatistics of Imperial College. Since January 2020, he is the co-PI of the World Cancer Research Fund Continuous Update Project at Imperial College, which performs evidence syntheses of the diet, adiposity and physical activity associations with risk of cancer development and survival. He also holds an Associate Professor position in Epidemiology at the University of Ioannina School of Medicine in Greece.
He was trained at the University of Athens, where he received a Bachelor's in Nursing and a Master's in Public Health, and at the School of Public Health of the Johns Hopkins University in Baltimore, USA, where he received a Master of Health Science in Biostatistics and PhD in Epidemiology. He performed his post-doctoral training in cancer epidemiology at the University of Oxford in the UK.
He is a molecular epidemiologist with a strong focus on cancer aetiology and prevention. His research focuses on the role of genetic, dietary, metabolic and hormonal pathways in cancer development, prognosis and survival. He is further interested in evidence synthesis methods and applications, Mendelian randomization, pharmaco-epidemiology, and the methodological assessment and correction (via causal inference methods) of systematic errors in the biomedical literature.
et al., 2016, Burden of Cancer in a Large Consortium of Prospective Cohorts in Europe, Journal of the National Cancer Institute, Vol:108, ISSN:0027-8874
et al., 2015, A Genome-wide Pleiotropy Scan for Prostate Cancer Risk, European Urology, Vol:67, ISSN:0302-2838, Pages:649-657
et al., 2015, Type 2 diabetes and cancer: umbrella review of meta-analyses of observational studies, British Medical Journal, Vol:350, ISSN:0959-535X
et al., 2014, Metformin does not affect cancer risk: a cohort study in the UK clinical practice research datalink analyzed like an intention-to-treat trial, Diabetes Care, Vol:37, ISSN:0149-5992, Pages:2522-2532
et al., 2012, Evaluation of Excess Statistical Significance in Meta-analyses of 98 Biomarker Associations with Cancer Risk, Journal of the National Cancer Institute, Vol:104, ISSN:0027-8874, Pages:1867-1878