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Self-Assessment Questionnaire on Patient-Physician Concordance on Nevus Self-Count and Models Development to Predict High-Risk Phenotype >50 Nevi.
- Source :
-
Dermatology (Basel, Switzerland) [Dermatology] 2022; Vol. 238 (5), pp. 986-995. Date of Electronic Publication: 2022 Apr 22. - Publication Year :
- 2022
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Abstract
- Background: Cutaneous melanoma accounts for the majority of skin cancer-related deaths. Readily identifiable phenotypic characteristics and total body nevus count (TBNC) >50 are among the most important risk factors for cutaneous melanoma. Implementation of nevus self-count procedures and self-assessment of phenotypic traits as part of skin self-examination could be an excellent screening tool for identifying an at-risk target population.<br />Objectives: Objectives of the study were to assess the skills of a central Italian and eastern Spanish population sample to recognize their skin lesions via the submission of a self-assessment questionnaire and to explore which self-assessment questionnaire item combination best predicts the high-risk condition of TBNC >50.<br />Methods: Patients aged ≥18 years filled a self-assessment questionnaire, autonomously and prior to the dermatological visit. Subsequently, dermatologists performed total body skin examination and reported patients' skin lesions on a separate questionnaire.<br />Results: We reported fair to moderate patient-dermatologist agreement for skin lesion self-assessment. The item number of nevi on the back was the single questionnaire item most accurately predicting TBNC >50. The high-sensitivity and high-specificity classification and regression tree models for the prediction of TBNC >50 displayed different items combinations; the item nevus on the back was always the first and most important predictor in both our models.<br />Conclusions: Patients were partially able to provide correct estimation of their whole-body nevus self-count. The item nevi on the back seems to be the first and most important predictor of TBNC >50 across our models. Delivery of high-sensitivity and high-specificity prediction models based on our questionnaire item combination may help defining a high-risk target population.<br /> (© 2022 S. Karger AG, Basel.)
Details
- Language :
- English
- ISSN :
- 1421-9832
- Volume :
- 238
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Dermatology (Basel, Switzerland)
- Publication Type :
- Academic Journal
- Accession number :
- 35462375
- Full Text :
- https://doi.org/10.1159/000523953