Self-Assessment Questionnaire on Patient-Physician Concordance on Nevus Self-Count and Models Development to Predict High-Risk Phenotype >50 Nevi.
Image support
Melanoma
Secondary prevention
Self-assessment questionnaire
Skin self-examination
Journal
Dermatology (Basel, Switzerland)
ISSN: 1421-9832
Titre abrégé: Dermatology
Pays: Switzerland
ID NLM: 9203244
Informations de publication
Date de publication:
2022
2022
Historique:
received:
03
07
2021
accepted:
26
02
2022
pubmed:
25
4
2022
medline:
8
9
2022
entrez:
24
4
2022
Statut:
ppublish
Résumé
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. 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. 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. 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. 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.
Sections du résumé
BACKGROUND
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.
OBJECTIVES
OBJECTIVE
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.
METHODS
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.
RESULTS
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.
CONCLUSIONS
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.
Identifiants
pubmed: 35462375
pii: 000523953
doi: 10.1159/000523953
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
986-995Informations de copyright
© 2022 S. Karger AG, Basel.