Concordance And Timing In Recording Cancer Events In Primary Care, Hospital And Mortality Records For Patients With And Without Psoriasis: A Population-Based Cohort Study

Background The association between psoriasis and the risk of cancer has been investigated in numerous studies utilising electronic health records (EHRs), with conflicting results in the extent of the association. Objectives To assess concordance and timing of cancer recording between primary care, hospital and death registration data for people with and without psoriasis. Methods Cohort studies delineated using primary care EHRs from the Clinical Practice Research Datalink (CPRD) GOLD and Aurum databases, with linkage to hospital episode statistics (HES), Office for National Statistics (ONS) mortality data and indices of multiple deprivation (IMD). People with psoriasis were matched to those without psoriasis by age, sex and general practice. Cancer recording between databases was investigated by proportion concordant, that being the presence of cancer record in both source and comparator datasets. Delay in recording cancer diagnoses between CPRD and HES records and predictors of discordance were also assessed. Results 58,904 people with psoriasis and 350,592 comparison patients were included using CPRD GOLD; whereas 213,400 people with psoriasis and 1,268,998 comparison patients were included in CPRD Aurum. For all cancer records (excluding keratinocyte), concordance between CPRD and HES was greater than 80%. Concordance for same-site cancer records was markedly lower (<68% GOLD-linked data; <72% Aurum-linked data). Concordance of non-Hodgkin lymphoma and liver cancer recording between CPRD and HES was lower for people with psoriasis compared to those without. Conclusions Concordance between CPRD and HES is poor when restricted to cancers of the same site, with greater discordance in people with psoriasis for some cancers of specific sites. The use of linked patient-level data is an important step in reducing misclassification of cancer outcomes in epidemiological studies using routinely collected electronic health records.