Systematic curation and analysis of ovarian cancer data across multiple electronic record systems held within the UK National Health Service: a tertiary referral centre experience
Automated curation and analysis of RWD is possible at scale, in real time. Analysis yielded clinical findings consistent with the prevalent literature and showed evolution of treatment practice. While not all unstructured data could be explored, we demonstrate that automated curation of clinically important real-world variables is feasible and can yield robust data for both research and operational purposes.
Authors
- Erik Mayer (ORCID: https://orcid.org/0000-0002-5509-4580)
- J. Krell
- Ben Glampson (ORCID: https://orcid.org/0000-0002-5601-5581)
- Laura A. Tookman (ORCID: https://orcid.org/0000-0003-0752-3974)
- C Fotopoulou
- Louis G. Mercuri (ORCID: https://orcid.org/0000-0002-5061-4129)
- I. McNeish
- D. Lyons (ORCID: https://orcid.org/0000-0002-3623-1316)
- Sadaf Ghaem‐Maghami (ORCID: https://orcid.org/0000-0002-7369-5080)
- Rong Jiang (ORCID: https://orcid.org/0000-0002-2138-167X)
- E. Xing
- Yashna Nadkarni
- Ankit Chadha (ORCID: https://orcid.org/0000-0002-5089-3877)
- Gaia Giannone (ORCID: https://orcid.org/0000-0003-1991-039X)
- Amit Samani (ORCID: https://orcid.org/0000-0001-6570-4912)
- D. Papadimitriou
Institutions
- Imperial College Healthcare NHS Trust (GB)
- NIHR Imperial Biomedical Research Centre (GB)
- Imperial College London (GB)
Publication Details
- Journal
- ESMO Real World Data and Digital Oncology
- Published
- 2025-06-19
- DOI
- https://doi.org/10.1016/j.esmorw.2025.100150
- Primary Topic
- Ovarian cancer diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Imperial Health Charity
- National Institute for Health and Care Research
- Imperial College Healthcare NHS Trust
- NIHR Imperial Biomedical Research Centre