Abstract and Introduction
Abstract
Background: In children, psoriasis can be challenging to diagnose. Difficulties arise from differences in the clinical presentation compared with adults.
Objectives: To test the diagnostic accuracy of previously agreed consensus criteria and to develop a shortlist of the best predictive diagnostic criteria for childhood psoriasis.
Methods: A case–control diagnostic accuracy study in 12 UK dermatology departments (2017–2019) assessed 18 clinical criteria using blinded trained investigators. Children (< 18 years) with dermatologist-diagnosed psoriasis (cases, N = 170) or a different scaly inflammatory rash (controls, N = 160) were recruited. The best predictive criteria were identified using backward logistic regression, and internal validation was conducted using bootstrapping.
Results: The sensitivity of the consensus-agreed criteria and consensus scoring algorithm was 84·6%, the specificity was 65·1% and the area under the curve (AUC) was 0·75. The seven diagnostic criteria that performed best were: (i) scale and erythema in the scalp involving the hairline, (ii) scaly erythema inside the external auditory meatus, (iii) persistent well-demarcated erythematous rash anywhere on the body, (iv) persistent erythema in the umbilicus, (v) scaly erythematous plaques on the extensor surfaces of the elbows and/or knees, (vi) well-demarcated erythematous rash in the napkin area involving the crural fold and (vii) family history of psoriasis. The sensitivity of the best predictive model was 76·8%, with specificity 72·7% and AUC 0·84. The c-statistic optimism-adjusted shrinkage factor was 0·012.
Conclusions: This study provides examination- and history-based data on the clinical features of psoriasis in children and proposes seven diagnostic criteria with good discriminatory ability in secondary-care patients. External validation is now needed.
Introduction
Psoriasis is a chronic immune-mediated inflammatory skin disease affecting the skin and joints. The World Health Organization (WHO) has identified psoriasis as a serious noncommunicable disease and an area of unmet health need.[1] Ensuring prompt diagnosis and identifying other priority areas for research are highlighted by both the WHO and the Psoriasis Priority Setting Partnership.[2,3]
Making the diagnosis of psoriasis in children and young people can be more challenging than in adults. The presentation of psoriasis in children is often more subtle, with thinner, less hyperkeratotic plaques. The distribution often involves the flexures, face and skin covered by clothing and hair, which can be easily missed if these areas are not specifically asked about and examined.[4,5] Psoriasis in children is also under-recognized in primary and secondary care. Reasons for this may include a lack of awareness that psoriasis can develop from infancy onwards, and psoriasis being misdiagnosed as other common childhood rashes such as atopic dermatitis/eczema, skin infections and exanthems.[6,7] The evidence to guide treatment and monitoring in childhood psoriasis is limited. For many children psoriasis can persist into adulthood and there is the potential for a cumulative negative effect over many years.[8–11]
Currently, diagnosis is based on the recognition of clinical signs and symptoms. There are no diagnostic criteria in routine use in clinical practice or research.[12] The lack of a standardized disease definition and case ascertainment impacts on the validity and generalizability of the evidence, and is a limitation of many existing studies.[13–16] Also, timely recognition of psoriasis is important for referral to a specialist, access to effective treatment and identification of juvenile psoriatic arthritis.[8]
To address this an eDelphi consensus study was completed with the International Psoriasis Council to agree a list of criteria important for the diagnosis of psoriasis in children and to propose a scoring algorithm for diagnosis.[17] The aim of this study (DIPSOC) was to test the diagnostic accuracy of the consensus-agreed criteria and to refine the criteria using multivariate analysis. Through refinement the aim was to identify a shortlist of the best predictive criteria.
The British Journal of Dermatology. 2022;186(2):341-351. © 2022 Blackwell Publishing
