The proposed study will examine comorbidity patterns in people with psoriasis, estimating the prevalence of diseases, identifying clusters of similar conditions and subgroups of people with similar disease profiles.
Data will be obtained from CPRD GOLD and CPRD Aurum with linkage to hospital (Hospital Episodes Statistics), mortality (Office for National Statistics) and deprivation (Index of Multiple Deprivation) data. A common protocol will be applied across the databases for cohort construction and analysis. The study populations will comprise of adult patients with psoriasis, as identified from Read codes, between 1 January 1998 and 31 December 2020 who have been registered with a contributing practice for at least one year. The primary outcome will be comorbidities known to be associated with psoriasis. Crude and age-standardised prevalence rates will be calculated for each condition. Agglomerative hierarchical clustering will be used to identify comorbidity clusters. Latent class analysis will be used to identify distinct profiles of multiple disease among patients with psoriasis with multivariable regression analysis to predict latent class membership. Progression or changes in disease patterns will be examined by performing cluster and latent class analyses throughout follow-up.
Morbidity prevalence - individual conditions, comorbidity and multimorbidity
(conditions selected based on clinical association with psoriasis, core conditions, diseases in the quality and outcomes framework and long-term conditions as defined by the NHS);
patterns of disease clusters; determinants of disease clusters
Darren Ashcroft - Chief Investigator - University of Manchester
Alison Wright - Corresponding Applicant - University of Manchester
Christopher Griffiths - Collaborator - University of Manchester
Evangelos Kontopantelis - Collaborator - University of Manchester
Martin Rutter - Collaborator - University of Manchester
Richard Emsley - Collaborator - King's College London (KCL)