Dr Emma Atakpa, MMath, PhD

Profile

I am a Postdoctoral Data Scientist in the Centre for Evaluation and Methods, working on a Breast Cancer Now-funded project titled "Models for risk of aggressive breast cancer and risk-stratified screening strategies". My research aims to adapt the Tyrer-Cuzick (IBIS) breast cancer risk model to predict risk by oestrogen-receptor status, develop a statistical model to estimate risk of node-positive breast cancer at detection, and evaluate the benefits and harms of risk-stratified breast cancer screening (personalising prevention and screening strategies according to individual risk) based on these models.

In 2013, I completed an integrated master's degree (MMath) in Mathematics with Economics at the University of Sussex, with a dissertation on mathematical modelling of virus-induced autoimmunity.

In 2015, I joined the former Wolfson Institute of Preventive Medicine (in the Centre for Cancer Prevention) to study for a PhD in Medical Statistics with Professor Jack Cuzick and Dr Adam Brentnall. My thesis, titled "Breast cancer risk associated with changes in mammographic density", focused on the use of repeated measures of mammographic density to estimate risk of breast cancer. After completing my PhD in 2019, I worked at the University of Western Australia, before returning to the Wolfson Institute in 2020 to begin my postdoctoral work.

Alongside my primary role, I also provide statistical support to the wider School of Medicine and Dentistry (UKCOGS, SIZOMUS, Barts Health NHS Trust COVID-19 ethnicity and equity data analysis), facilitate teaching (CANM937 Research Methods MSc module, Global Parkinson’s Genetics Program), co-organise the Wolfson Institute of Population Health Statisticians’ seminars, and participate in various public engagement, science communication, and Equality, Diversity and Inclusion activities.

Research

Research Interests:

• Medical statistics
• Mammographic density
• Longitudinal analysis of biomarkers
• Breast cancer prevention & screening
• Statistical models for breast cancer risk prediction

Publications

Outstanding publications

• Atakpa E, Thorat M A, Cuzick, J and Brentnall A. Mammographic density, endocrine therapy and breast cancer risk: a prognostic and predictive biomarker review. Cochrane Database Syst Rev. 2021 Oct 26;10(10): https://pubmed.ncbi.nlm.nih.gov/34697802/

• Atakpa A, Brentnall A, Astley S, Cuzick J et al. The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study. Cancers (Basel). 2021 Jun 29;13(13):3245: https://pubmed.ncbi.nlm.nih.gov/34209579/