Differences in recording of cancer diagnosis between datasets in England: A population-based study of linked cancer registration, hospital, and primary care data
Year: 2024
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Differences in the recording of cancer case status and diagnosis date have been observed between cancer registry (CR) - the reference standard - and electronic health records (EHRs); such differences may affect estimates of cancer risk or misclassify diagnostic pathways. This study aims to quantify differences in recording of case status and date of cancer diagnosis between cancer registry and EHRs. METHODS: Linked primary care (Clinical Practice Research Datalink (CPRD)), secondary care (Hospital Episode Statistics (HES)) and national Cancer Registry (CR) data, were used to identify 14,301 patients with a recorded diagnosis of brain, colon, lung, ovarian, or pancreatic cancer between 1999 and 2018. Agreement in case status between datasets, differences in recorded diagnosis dates, and change in agreement over time were investigated for each cancer site. RESULTS: Between 84 % (ovary) to 92 % (colon) of diagnoses in cancer registry were also recorded in combined CPRD-HES data. Agreement with cancer registry was slightly lower in HES (78 % (ovary) to 86 % (colon)) and CPRD (61 % (ovary, pancreas) to 72 % (brain)). The proportion of CPRD-HES diagnoses confirmed in CR varied by cancer site (50 % (brain) to 86 % (lung)). Agreement between CR and HES was relatively stable within cancer sites over time. Concordance between CR and CPRD was more heterogeneous between cancer sites and over time. Best agreement in diagnosis date was observed between CR and HES (median difference 0 or 1 days, all cancer sites). CONCLUSION: Agreement between CR and EHR data is heterogeneous across cancer sites. Concordance does not appear to have improved over time. Combined data from primary and secondary care may be sufficient to approximate case status in CR in some circumstances, but the date we consider to represent the diagnosis may impact study outcomes.
Source: Cancer Epidemiology
Authors: Emma Whitfield, Becky White, Matthew E. Barclay, Meena Rafiq, Cristina Renzi, Brian Rous, Spiros Denaxas, Georgios Lyratzopoulos
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,350
Funders: Wellcome Trust, UK Research and Innovation, Cancer Research UK, National Institute for Health and Care Research, British Heart Foundation, University of Cambridge, University College London, University of Manchester, Public Health Agency, Knight Cancer Institute, Oregon Health and Science University, Medical Research Council, Economic and Social Research Council, Health and Social Care Research and Development Division, UCLH Biomedical Research Centre
OpenAlex ID: W4404857091