Dermoscopy in general dermatology (non-neoplastic dermatoses) in skin of colour: a comparative retrospective study by the International Dermoscopy Society

Background Dermoscopy has been shown to be a useful supportive tool to assist the diagnosis of several non-neoplastic dermatoses (i.e. inflammatory, infiltrative and infectious skin diseases), yet data on skin of colour is still limited. Objectives To characterize dermoscopic features of non-neoplastic dermatoses in dark-skinned patients in order to identify possible clues that may facilitate the differential diagnosis of clinically similar conditions. Materials & methods Members of the International Dermoscopy Society were invited to submit cases of any non-neoplastic dermatosis developing in patients with Fitzpatrick phototypes V-VI whose diagnosis had been confirmed by the corresponding gold standard diagnostic test. A standardized assessment of the dermoscopic images and a comparative analysis according to clinical presentation were performed. Seven clinical categories were identified: (I) papulosquamous dermatoses; (II) facial hyperpigmented dermatoses; (III) extra-facial hyperpigmented dermatoses; (IV) hypopigmented dermatoses; (V) granulomatous dermatoses; (VI) sclerotic dermatoses; and (VII) facial inflammatory dermatoses. Results A total of 653 patients (541 and 112 with Phototype V and VI, respectively) were recruited for the analysis. Thirty-six statistically significant dermoscopic features were identified for papulosquamous dermatoses, 24 for facial hyperpigmented disorders, 12 for extra-facial hyperpigmented disorders, 17 for hypopigmented disorders, eight for granulomatous dermatoses, four for sclerotic dermatoses and 17 for facial inflammatory diseases. Conclusions Our findings suggest that dermoscopy might be a useful tool in assisting the diagnosis of clinically similar non-neoplastic dermatoses in dark phototypes by revealing characteristic clues. Study limitations include the retrospective design, the lack of a direct dermoscopic-histological correlation analysis and the small sample size for less common diseases.