Profile
I am a Senior Lecturer in Biostatistics in the Centre for Evaluation and Methods, and fellow of the Digital Environment Research Institute (DERI). I work closely with colleagues in the Centre for Prevention, Detection and Diagnosis. I co-lead a research methods module for MSc programmes at Barts Cancer Institute. I have previously worked on problems in operational research, including in retail finance and aircraft scheduling.
I am currently serving as member of a NICE committee for Ovarian cancer guidelines development on identifying and managing familial and genetic risk. I support several clinical trial steering and data safety monitoring committees as statistician. I am standing member Cancer Research UK's Expert Review Panel on Early Detection & Diagnosis Trials, Behavioural, Health Systems and Health Economics Research.
Research
Research Interests:
My work mainly focuses on cancer prevention and early detection, particularly risk stratification. This includes in the design and analysis of epidemiological, clinical trials and laboratory studies, and in developing statistical methodology driven by these studies. I also collaborate in other healthcare and biomedical science areas, such as in helping to design and analyse research studies. I enjoy learning about new areas and working in multidisciplinary teams.
Publications
Please click through to see a complete list of Adam’s publications
Outstanding publications
- Brentnall AR, Cuzick J. Risk Models for Breast Cancer and Their Validation. Stat Sci. 2020;35(1):14-30. doi:10.1214/19-STS729
- Sasieni P, Brentnall AR. On standardized relative survival. Biometrics. 2017 Jun;73(2):473-482. Epub 2016 Aug 23. PMID: 27554303; PMCID: PMC5507182. doi: 10.1111/biom.12578.
- Brentnall AR, Cuzick J, Buist DSM, Bowles EJA. Long-term Accuracy of Breast Cancer Risk Assessment Combining Classic Risk Factors and Breast Density. JAMA Oncol. 2018;4(9):e180174. doi:10.1001/jamaoncol.2018.0174.
- Brentnall AR, Cuzick J. Use of the concordance index for predictors of censored survival data. Statistical Methods in Medical Research. 2018;27(8):2359-2373. doi.org/10.1177/0962280216680245.
- Brentnall, A.R., Harkness, E.F., Astley, S.M. et al. Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort. Breast Cancer Res 17, 147 (2015). doi.org/10.1186/s13058-015-0653-5.
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