International Journal of Population Data Science (Sep 2024)

Socio-demographic variations in prostate cancer diagnosis recording: Primary care compared to the Cancer Registry in England

  • Gayasha Somathilake,
  • Elizabeth Ford,
  • Jo Armes,
  • Sotiris Moschoyiannis,
  • Sophie Otter,
  • Agnieszka Lemanska

DOI
https://doi.org/10.23889/ijpds.v9i5.2589
Journal volume & issue
Vol. 9, no. 5

Abstract

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Introduction In the UK, primary care data are often used for cancer-related research, but the accuracy of cancer information is uncertain. Objective We investigated socio-demographic variation based on the recording date of prostate cancer diagnosis between primary care and the National Cancer Registry (CR). Approach We utilised a data extract of 1,600,000 patients over 65 years from Clinical Practice Research Datalink (CPRD). We extracted prostate cancer diagnoses using Read and SNOMED-CT codes from primary care, and ICD-10 from CR. Initial code entry determined diagnosis dates. We categorised recording timing differences as earlier, same-day or later in primary care than CR and used the chi-squared test and logistic regression (adjusted for recording year) to compare these discrepancies across age, deprivation, and ethnicity. Results We included 26,875 men with prostate cancer diagnoses commonly recorded in both sources during 2000-2016 (1,030 excluded with missing ethnicity). Compared to CR, 1,747 (7%) had diagnoses recorded on the same day in primary care, while 20,615 (77%) had later recordings with a median delay of 21 days (IQR: 13-38). Age at diagnosis was associated with recording discrepancies (p<0.001); older men were more likely to have earlier/same-day recordings. Adjusted ORs for age groups were 1.4 (95%CI: 1.3-1.5) for 60-69, 1.3 (1.2-1.5) for 70-79, and 0.9 (0.8-1.0) for ≥80 compared to <60. No associations were found between deprivation (p=0.096) or ethnicity (p=0.067) and recording differences. Conclusion/ Implications The discrepancy in prostate cancer information between primary care and CR underscores potential biases in studies relying solely on one data source.