Impact of clinical and personal data in the dermoscopic differentiation between early melanoma and atypical nevi
Citation: Tognetti L, Cinotti E, Moscarella E, Farnetani F, Malvehy J, Lallas A, Pellacani G, Argenziano G, Cevenini G, Rubegni P. Impact of clinical and personal data in the dermoscopic differentiation between early melanoma and atypical nevi. Dermatol Pract Concept. 2018;8(4):324-327. DOI: https://doi.org/10.5826/dpc.0804a16
Received: march 26, 2018; Accepted: May 23, 2018; Published: October 31, 2018
Copyright: ©2018 Tognetti et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Competing interests: The authors have no conflicts of interest to disclose.
All authors have contributed significantly to this publication. LT and PR contributed equally to this study.
Corresponding author: Linda Tognetti, MD, Hospital S. Maria alle Scotte, Viale Bracci 16, 53100 Siena, Italy. Email: firstname.lastname@example.org
Background: Differential diagnosis of clinically atypical nevi (aN) and early melanomas (eMM) still represents a challenge even for experienced dermoscopists, as dermoscopy alone is not sufficient to adequately differentiate these equivocal melanocytic skin lesions (MSLs).
Objectives: The objectives of this study were to investigate what were the most relevant parameters for noninvasive differential diagnosis between eMM and aN among clinical, personal, and dermoscopic data and to evaluate their impact as risk factors for malignancy.
Methods: This was a retrospective study performed on 450 MSLs excised from 2014 to 2016 with a suspicion of malignancy. Dermoscopic standardized images of the 450 MSLs (300 aN and 150 eMM) were collected and evaluated. Patients’ personal data (ie, age, gender, body site, maximum diameter) were also recorded. Dermoscopic evaluations were performed by 5 different experts in dermoscopy blinded to histopathological diagnosis. Fleiss’ κ was calculated to measure concordance level between experts in the description of dermoscopic parameters for each MSLs. The power of the studied variables in discriminating malignant from benign lesions was also investigated through F-statistics.
Results: The variables age and maximum diameter supplied the highest discriminant power (F = 253 and 227, respectively). Atypical network, blue white veil and white shiny streaks were the most significant dermoscopic patterns suggestive of malignancy (F = 110, 104 and 99.5, respectively). Shiny white streaks was the only dermoscopic parameter to obtain satisfactory concordance value. Gender was not a discriminant factor. The specific statistical weight of clinical and personal data (ie, “patient’s age” and “lesion diameter”) surpassed those of atypical dermoscopic features.
Conclusions: The objective clinical and personal data collected here could supply a fundamental contribution in the correct diagnosis of equivocal MSLs and should be included in diagnostic algorithms along with significant dermoscopic features (ie, atypical network, blue-white veil, and shiny white streaks).