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Developing diagnostic criteria for psoriasis in childre

Not Applicable
Completed
Conditions
Psoriasis in children and young people
Skin and Connective Tissue Diseases
Psoriasis
Registration Number
ISRCTN98851260
Lead Sponsor
niversity of Nottingham
Brief Summary

2019 Protocol article in https://pubmed.ncbi.nlm.nih.gov/31462472/ protocol (added 02/09/2020) 2021 Results article in https://pubmed.ncbi.nlm.nih.gov/34477218/ (added 30/12/2021)

Detailed Description

Not available

Recruitment & Eligibility

Status
Completed
Sex
All
Target Recruitment
348
Inclusion Criteria

Cases:
1. Children/young people (0 to <18 years of age)
2. Confirmed diagnosis of plaque psoriasis by a dermatologist
3. Active disease at the time of assessment
4. Able to consent

Controls:
1. Children/young people (0 to <18 years of age)
2. Confirmed diagnosis of a scaly inflammatory rash (excluding psoriasis and indeterminate psoriasis) by a dermatologist
3. Active disease at the time of assessment
4. Able to consent

Indeterminate psoriasis:
1. Children/young people (0 to <18 years of age)
2. Diagnosis of indeterminate or possible psoriasis by a dermatologist
3. Active disease at the time of assessment
4. Able to consent and willing to receive a follow-up questionnaire after 24 months

Exclusion Criteria

1. Children/young people with pustular psoriasis
2. Children/young people with erythrodermic psoriasis
3. Children/young people without a dermatologist’s diagnosis

Study & Design

Study Type
Observational
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Consensus agreed diagnostic criteria vs reference standard (dermatologist’s diagnosis). The presence or absence (binary) of each of the diagnostic criterion will be assessed by study investigators trained to undertake the diagnostic criteria assessment and blinded to the diagnosis of the participant. The threshold for diagnosis according to the consensus agreed diagnostic criteria has been determined through the consensus study. The diagnostic accuracy of the consensus agreed diagnostic criteria will be assessed using sensitivity and specificity. The best predictive diagnostic criteria will be developed using multivariate analysis and the decision to include individual criteria in the model will be based on the likelihood ratio.
Secondary Outcome Measures
NameTimeMethod
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