Phenotypes and rates of cancer-relevant symptoms and tests in the year before cancer diagnosis in UK Biobank and CPRD Gold.


Journal

PLOS digital health
ISSN: 2767-3170
Titre abrégé: PLOS Digit Health
Pays: United States
ID NLM: 9918335064206676

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 29 03 2023
accepted: 05 10 2023
medline: 15 12 2023
pubmed: 15 12 2023
entrez: 15 12 2023
Statut: epublish

Résumé

Early diagnosis of cancer relies on accurate assessment of cancer risk in patients presenting with symptoms, when screening is not appropriate. But recorded symptoms in cancer patients pre-diagnosis may vary between different sources of electronic health records (EHRs), either genuinely or due to differential completeness of symptom recording. To assess possible differences, we analysed primary care EHRs in the year pre-diagnosis of cancer in UK Biobank and Clinical Practice Research Datalink (CPRD) populations linked to cancer registry data. We developed harmonised phenotypes in Read v2 and CTV3 coding systems for 21 symptoms and eight blood tests relevant to cancer diagnosis. Among 22,601 CPRD and 11,594 UK Biobank cancer patients, 54% and 36%, respectively, had at least one consultation for possible cancer symptoms recorded in the year before their diagnosis. Adjusted comparisons between datasets were made using multivariable Poisson models, comparing rates of symptoms/tests in CPRD against expected rates if cancer site-age-sex-deprivation associations were the same as in UK Biobank. UK Biobank cancer patients compared with those in CPRD had lower rates of consultation for possible cancer symptoms [RR: 0.61 (0.59-0.63)], and lower rates for any primary care consultation [RR: 0.86 (95%CI 0.85-0.87)]. Differences were larger for 'non-alarm' symptoms [RR: 0.54 (0.52-0.56)], and smaller for 'alarm' symptoms [RR: 0.80 (0.76-0.84)] and blood tests [RR: 0.93 (0.90-0.95)]. In the CPRD cohort, approximately representative of the UK population, half of cancer patients had recorded symptoms in the year before diagnosis. The frequency of non-specific presenting symptoms recorded in the year pre-diagnosis of cancer was substantially lower among UK Biobank participants. The degree to which results based on highly selected biobank cohorts are generalisable needs to be examined in disease-specific contexts.

Identifiants

pubmed: 38100737
doi: 10.1371/journal.pdig.0000383
pii: PDIG-D-23-00086
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e0000383

Informations de copyright

Copyright: © 2023 Barclay et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

MB reports personal fees from Grail Inc for membership of an Independent Data Monitoring Committee, outside the submitted work. No other disclosures were reported.

Auteurs

Matthew Barclay (M)

Department of Behavioural Science and Health, Institute of Epidemiology and Healthcare, University College London, London, United Kingdom.

Cristina Renzi (C)

Department of Behavioural Science and Health, Institute of Epidemiology and Healthcare, University College London, London, United Kingdom.
Faculty of Medicine, University Vita-Salute San Raffaele, Milan, Italy.

Antonis Antoniou (A)

Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.

Spiros Denaxas (S)

Institute of Health Informatics, University College London, London, United Kingdom.

Hannah Harrison (H)

Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.

Samantha Ip (S)

Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom.

Nora Pashayan (N)

Department of Applied Health Research, Institute of Epidemiology and Healthcare, University College London, London, United Kingdom.

Ana Torralbo (A)

Institute of Health Informatics, University College London, London, United Kingdom.

Juliet Usher-Smith (J)

Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.

Angela Wood (A)

Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom.
British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, United Kingdom.
National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, United Kingdom.
Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, United Kingdom.
Cambridge Centre for Artificial Intelligence in Medicine, University of Cambridge, Cambridge, United Kingdom.

Georgios Lyratzopoulos (G)

Department of Behavioural Science and Health, Institute of Epidemiology and Healthcare, University College London, London, United Kingdom.

Classifications MeSH