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An integrated clinical‐dermoscopic risk scoring system for the differentiation between early melanoma and atypical nevi: the iDScore
Author(s) -
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.
Publication year - 2018
Publication title -
journal of the european academy of dermatology and venereology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.655
H-Index - 107
eISSN - 1468-3083
pISSN - 0926-9959
DOI - 10.1111/jdv.15106
Subject(s) - medicine , concordance , receiver operating characteristic , melanoma , lesion , scoring system , malignancy , nevus , radiology , dermatology , pathology , surgery , cancer research
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 ( iDS core ). 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 iDS core ‐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 iDS core 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.