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Identifying the best predictive diagnostic criteria for psoriasis in children (< 18 years): a UK multicentre
E Burden-Teh1,2, R Murphy1,3, S Gran1
1Centre of Evidence Based Dermatology, School of Medicine, University of Nottingham, Nottingham, UK.
Insights
Diagnosing childhood psoriasis is challenging due to differing presentations. This study identified seven key clinical criteria to improve diagnostic accuracy for pediatric psoriasis.
Area of Science:
- Dermatology
- Pediatric Medicine
- Diagnostic Accuracy Studies
Background:
- Psoriasis diagnosis in children presents unique challenges compared to adults.
- Clinical presentation of pediatric psoriasis often differs significantly from adult forms.
- Accurate diagnosis is crucial for timely and appropriate management of childhood psoriasis.
Purpose of the Study:
- To evaluate the diagnostic accuracy of established consensus criteria for childhood psoriasis.
- To develop and validate a refined set of predictive diagnostic criteria for pediatric psoriasis.
- To improve the identification of psoriasis in pediatric patients presenting with scaly rashes.
Main Methods:
- A case-control diagnostic accuracy study was conducted across 12 UK dermatology centers.
- 18 clinical criteria were assessed by blinded investigators in children with psoriasis (cases) and other scaly rashes (controls).
- Backward logistic regression and bootstrapping were used to identify and validate the best predictive diagnostic criteria.
Main Results:
- The initial consensus criteria showed 84.6% sensitivity and 65.1% specificity (AUC 0.75).
- Seven key criteria demonstrated superior predictive ability: scalp hairline involvement, external auditory meatus scales, persistent body rash, umbilical erythema, extensor plaque, napkin area rash with fold involvement, and family history.
- The optimized model achieved 76.8% sensitivity, 72.7% specificity, and an AUC of 0.84.
Conclusions:
- Seven specific clinical and historical criteria show strong discriminatory ability for diagnosing psoriasis in children.
- These criteria offer improved diagnostic accuracy for pediatric psoriasis in secondary care settings.
- External validation of these proposed diagnostic criteria is recommended for broader applicability.
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.
