An integrated clinical‐dermoscopic risk scoring system for the differentiation between early melanoma and atypical nevi: the iDScore. (28th June 2018)

• Record Type: Journal Article
• Authors: Tognetti, L.; Cevenini, G.; Moscarella, E.; Cinotti, E.; Farnetani, F.; Mahlvey, J.; Perrot, J.L.; Longo, C.; Pellacani, G.; Argenziano, G.; Fimiani, M.; Rubegni, P.
• Is Part Of: Journal of the European Academy of Dermatology and Venereology. Volume 32:Number 12(2018)
• Page Start: 2162
• Page End: 2170
• Publication Date: 2018-06-28
• Subjects: Dermatology -- Periodicals; Sexually transmitted diseases -- Periodicals; 616.5
• DOI: 10.1111/jdv.15106
• Languages: English
• ISSNs: 0926-9959

Abstract

Abstract: Background: Dermoscopy revealed to be extremely useful in the diagnosis of early melanoma, the most important limitation being its subjectivity in giving a final diagnosis. To overcome this problem, several algorithms and checklists have been proposed. However, they generally demonstrated modest level of diagnostic accuracy, unsatisfactory concordance between dermoscopists and/or poor specificity. Objective: To test a new methodological approach for the differentiation between early melanoma and atypical nevi, based on an integrated clinical‐anamnestic dermoscopic risk scoring system ( iDScore ). Methods: We selected a total of 435 standardized dermoscopic images of clinically atypical melanocytic skin lesion (MSL) excised in the suspect of malignancy (i.e. 134 early melanomas – MM – and 301 atypical nevi). Data concerning patient age and sex and lesion dimension and site were collected. A scoring classifier was designed based on this data set integrated with the dermoscopic evaluations performed by three experts blinded to histological diagnosis. Results: A total of seven dermoscopic structures, three age groups (30–40 years, 41–60 years and >60 years), two maximum diameter categories (5–10 mm and >10 mm) and three body areas (i.e. frequently, chronically and seldom photoexposed sites) were selected by the scoring classifier as interdependently significant variables. The total risk score ( S ) of a lesion resulted from the simple sum of partial scores assigned to each selected variable. The iDScore ‐aided diagnosis showed an high accuracy (receiver operating characteristic‐area under the curve = 0.903; IC: 95% = 0.887–0.918). A risk‐based criticality scale corresponding to different S ranges was proposed. Conclusion: The iDScore checklist is proposed as a feasible and efficient tool to support dermatologists in non‐invasive differentiation between atypical nevi and early MM on the basis of few selected clinical‐anamnestic data and standardized dermoscopic features.