Psoriasis is a complex, chronic skin condition characterised by red, itchy scaly patches of skin that can appear on any part of the body but most commonly on the scalp, elbows, torso, lower back and knees. Psoriasis effects the quality of life of people with the condition but it is also associated with a number of other health problems including; arthritis, heart disease, diabetes, liver, kidney and bowel disorders, mental health conditions, cancer and sleep disorders. The impact of these conditions along with psoriasis pose an even greater burden on patients, potentially requiring the use of multiple medications and creating a further source of significant physical, emotional, and social stress and premature death.
The specific combinations of conditions occurring together will dictate the needs for people with psoriasis and the treatment strategies. Some of the medications used to treat psoriasis may aggravate certain health conditions and, in turn, drugs used to treat these co-existing conditions may affect psoriasis. Understanding the patterns of medical conditions in people with psoriasis may prompt earlier and more targeted screening of specific conditions and appropriate management and treatment to help delay or prevent the onset of these conditions and improve quality of life.
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
Charlotte Morris - Collaborator - 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)
HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation