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.
© 2020 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.