Self-Assessment Questionnaire on Patient-Physician Concordance on Nevus Self-Count and Models Development to Predict High-Risk Phenotype >50 Nevi

Maria Mannino, Pietro Sollena, Maria Esposito, Maria Concetta Fargnoli, Ketty Peris, Eduardo Nagore

Risultato della ricerca: Contributo in rivistaArticolo in rivista


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: 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: 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: 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: 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.
Lingua originaleEnglish
pagine (da-a)986-995
Numero di pagine10
Stato di pubblicazionePubblicato - 2022


  • Image support
  • Melanoma
  • Skin self-examination
  • Self-assessment questionnaire
  • Secondary prevention


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