BM BCh MA (Oxon) MSc DPhil FRCPath
Consultant Pathologist and Honorary Visiting Research Fellow
Dr Kezia Gaitskell joined the Cancer Epidemiology Unit in 2013, and studied for a DPhil as part of the Cancer Research UK Oxford Centre’s Clinical Research Training Fellowship programme. Prior to coming to the Unit, she studied medicine at Oxford, trained as a histopathology registrar in London, and completed an MSc in Epidemiology at the London School of Hygiene and Tropical Medicine. In 2018 she took up a post as an NIHR-funded Academic Clinical Lecturer in Histopathology in the Nuffield Division of Clinical Laboratory Sciences.
Her main research interest is in the interface between histopathology and epidemiology. For her DPhil, she explored epidemiological risk factors for ovarian cancer in the Million Women Study cohort, and how this varies by histological subtype. For her postdoctoral research, she continues to investigate variation in risk factors for different histological types of cancer.
Since completing her clinical training in 2022, she has continued with research and teaching alongside working as a Locum Consultant in Histopathology at Oxford University Hospitals.
The clinicopathological characteristics and survival outcomes of primary expansile vs. infiltrative mucinous ovarian adenocarcinoma: a retrospective study sharing the experience of a tertiary centre.
Nistor S. et al, (2023), Transl Cancer Res, 12, 2682 - 2692
Angiogenesis inhibitors for the treatment of epithelial ovarian cancer
Gaitskell K. et al, (2023), Cochrane Database of Systematic Reviews, 2023
Predicting Molecular Traits from Tissue Morphology Through Self-interactive Multi-instance Learning
Hu Y. et al, (2022), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13432 LNCS, 130 - 139
Ovarian cancer survival by stage, histotype, and pre-diagnostic lifestyle factors, in the prospective UK Million Women Study.
Gaitskell K. et al, (2021), Cancer Epidemiol, 76
Characterisation and clustering of diseases by their association with well-known risk factors
Webster A. et al, (2021), INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 50