Mei Sum Chan
MMORSE, FIA, CStat
Mei is investigating biological ages as means of expressing the effects of modifiable biomarkers for chronic diseases. This involves the use of several statistical methods to characterise biological ageing pathways and biomarker associations across multiple organ systems, and is intended to aid in designing interventions for earlier disease diagnosis and targeted treatments. Her research is supported by a Nuffield Department of Population Health Scholarship.
She is a Fellow of the Institute and Faculty of Actuaries, a Chartered Statistician and holds a Masters in Mathematics, Operations Research, Statistics and Economics (MORSE) from the University of Warwick. Prior to joining the department, she worked as a Medical Statistician within an industry-academia collaboration based in University College London, investigating socioeconomic inequalities in life expectancy with and without multimorbidity.
Professor Sarah Parish, Dr Matthew Arnold (AstraZeneca) and Professor Rafael Perera (Nuffield Department of Primary Care Health Sciences)
Design, methods, and reporting of impact studies of cardiovascular clinical prediction rules are suboptimal: A systematic review.
Ban J-W. et al, (2021), J Clin Epidemiol
Biomarkers in the prediction of multimorbidity: scoping review
Spencer EA. et al, (2020)
Biological age in UK Biobank: biomarker composition and prediction of mortality, coronary heart disease and hospital admissions
Chan MS. et al, (2019)
Estimation of life expectancies using continuous-time multi-state models
van den Hout A. et al, (2019), Computer Methods and Programs in Biomedicine, 178, 11 - 18
Socio-economic inequalities in life expectancy of older adults with and without multimorbidity: a record linkage study of 1.1 million people in England.
Chan MS. et al, (2019), Int J Epidemiol