Differentiation of combined nevi and melanomas: Case‐control study with comparative analysis of dermoscopic features. (17th January 2020)

• Record Type: Journal Article
• Authors: Schweizer, Anissa; Fink, Christine; Bertlich, Ines; Toberer, Ferdinand; Mitteldorf, Christina; Stolz, Wilhelm; Enk, Alexander; Kilian, Samuel; Haenssle, Holger A.
• Is Part Of: Journal der Deutschen Dermatologischen Gesellschaft. Volume 18:Number 2(2020)
• Page Start: 111
• Page End: 118
• Publication Date: 2020-01-17
• Subjects: Skin -- Diseases -- Periodicals; Dermatology -- Periodicals; 616.5005
• DOI: 10.1111/ddg.14019
• Languages: English
• ISSNs: 1610-0379

Abstract

Summary: Background and objectives: Combined nevi (CN) show two or more components of major nevus subtypes and simulate melanomas. We investigated a panel of dermoscopic features and three dermoscopic algorithms for differentiating CN from melanomas. Patients and methods: Retrospective, blinded case‐control study using dermoscopic images of 36 CN and 36 melanoma controls. Twenty‐one dermoscopic features validated for the diagnosis of melanocytic lesions, the number of colors, and three dermoscopic algorithms were investigated (ABCD rule of dermoscopy, Menzies scoring method, 7‐point checklist). Results: Five of seven features indicative of nevi were observed significantly more frequently in CN than in melanomas (all p < 0.05) and two were exclusively found in CN. Eleven out of 14 features indicative of melanomas were observed significantly more frequently in melanomas than in CN (all p < 0.03) and five were exclusively found in melanomas. The mean (± SD) number of colors in CN was lower than in melanomas (2.1 ± 0.6 versus 3.4 ± 0.7; p < 0.001). Among tested algorithms the ABCD rule of dermoscopy performed best (sensitivity 91.7 %, specificity 77.8 %). Conclusions: The ABCD rule of dermoscopy differentiated CN from melanomas most efficiently. Additional knowledge of dermoscopic features to be expected exclusively in either CN or melanomas should help dermatologists to make a correct clinical diagnosis.