PhD, MSc, MA (Cantab)
Senior Epidemiologist/Medical Statistician
I’ve recently been working on an HTA project on optimal strategies for monitoring lipid levels in patients at risk or with cardiovascular disease. Monitoring cholesterol levels is a common clinical activity, but the best lipid measure to use and the best interval for monitoring are not known, and practice varies. A high proportion of cholesterol measurements reflect only measurement error instead of true changes from baseline, thus modifications in treatments based on these readings could be unnecessary and potentially negative to the individual. My main role in the project has focused on creating statistical models to help understand the implications of different monitoring schedules.
I’m also involved in a project examining the quality and outcomes of care for chronic conditions in older patients diagnosed with breast, colorectal or prostate cancer; a project examining current practice and optimal strategies for monitoring kidney function in primary care; and an NSPCR project that aims to validate the performance of a series of risk prediction scores developed in the QResearch database using CPRD data.
I help co-ordinate and teach on the Introduction to Study Design and Research Methods module for the MSc in Evidence Based Health Care, and am part of the statistics teaching group for pre-clinical students in Oxford's Medical Sciences Division. I also supervise a DPhil student studying survival models for competing risks.
My previous research focussed on socioeconomic inequalities in health in the EPIC-Norfolk cohort, and night shift work, light at night and the risk of breast cancer in the Breakthrough Generations Study.
Timing of pubertal stages and breast cancer risk: The Breakthrough Generations Study
Bodicoat DH. et al, (2014), Breast Cancer Research, 16
Body mass index, exercise, and other lifestyle factors in relation to age at natural menopause: analyses from the breakthrough generations study.
Morris DH. et al, (2012), Am J Epidemiol, 175, 998 - 1005
Self-rated health does not explain the socioeconomic differential in mortality: a prospective study in the EPIC-Norfolk cohort.
McFadden E. et al, (2009), J Epidemiol Community Health, 63, 329 - 331
Social class, risk factors, and stroke incidence in men and women: a prospective study in the European prospective investigation into cancer in Norfolk cohort.
McFadden E. et al, (2009), Stroke, 40, 1070 - 1077
Does the association between self-rated health and mortality vary by social class?
McFadden E. et al, (2009), Soc Sci Med, 68, 275 - 280