GENERAL DERMATOLOGY BJD British Journal of Dermatology In vivo dermoscopic and confocal microscopy multistep algorithm to detect in situ melanomas* S. Borsari, 1 R. Pampena iD , 1 E. Benati iD , 1 C. Bombonato iD , 1 A. Kyrgidis iD , 1 E. Moscarella iD , 1 A. Lallas iD , 2 G. Argenziano, 3 G. Pellacani 4 and C. Longo iD 1,4 1 Centro Oncologico ad Alta Tecnologia Diagnostica, Azienda Unita ` Sanitaria Locale - IRCCS, Reggio Emilia, Italy 2 First Department of Dermatology, Aristotle University of Thessaloniki, Thessaloniki, Greece 3 Dermatology Unit, Second University of Naples, Naples, Italy 4 Department of Dermatology, University of Modena and Reggio Emilia, Modena, Italy Linked Comment: Bahadoran.Br J Dermatol 2018; 179:12–13. Correspondence Caterina Longo. E-mail: longo.caterina@gmail.com Accepted for publication 5 January 2018 Funding sources Italian Ministry of Health, Ricerca Finalizzata (NET-2011-02347213). Conflicts of interest None to declare. *Plain language summary available online DOI 10.1111/bjd.16364 Summary Background Although several dermoscopic features of in situ melanoma have been identified, data on confocal features of in situ melanoma are still lacking. Objectives To identify reflectance confocal microscopy (RCM) features of in situ melanoma and to develop a diagnostic score combining dermoscopy and RCM. Methods In total, 120 in situ melanoma and 213 nevi (test set) were retrospectively analysed to assess the presence of dermoscopic and RCM criteria. Facial and acral lesions were excluded. Spearman’s correlation, univariate and multivariate regres- sion models were used to identify features significantly correlated with in situ melanoma diagnosis. Multivariate results on the test set allowed the development of a multistep algorithm, that was tested on a validation set of 100 lesions. Results The dermoscopic findings of an atypical network and regression were independent predicting factors for in situ melanoma diagnosis [odds ratio (OR) 3Á44, 95% CI (confidence interval) 1Á70–6Á97 and OR 4Á17, 95% CI 1Á93–9Á00, respectively]. Significant confocal predictors for malignancy were epidermal pagetoid spread (OR 2Á83, 95% CI 1Á32–6Á04) and junctional cytological atypia (OR 3Á39, 95% CI 1Á38–8Á30 if focal, OR 8Á44, 95% CI 3Á21–22Á16 if wide- spread). A multistep diagnostic algorithm able to predict in situ melanoma with a sensitivity of 92Á5% and a specificity of 61% was developed. The validation set confirmed the high diagnostic value (sensitivity 92%, specificity 58%). Conclusions An easy and reproducible multistep algorithm for in situ melanoma detection is suggested, that can be routinely used in tertiary centres. What’s already known about this topic? • Data on reflectance confocal microscopy (RCM) diagnostic features for in situ mela- noma are still lacking. What does this study add? • Findings of an atypical network and regression from dermoscopy, and epidermal pagetoid spreading and junctional cytological atypia from RCM are positive predic- tors for in situ melanoma diagnosis. • This multistep algorithm can be used routinely in tertiary centres to improve the accuracy of diagnosing in situ melanoma. The combined incidence of in situ melanoma and invasive mel- anoma has been increasing by 2Á6% annually over the past decade, with intraepidermal tumours constituting the majority of the burden. 1,2 In situ melanoma is a melanoma that is lim- ited to the epidermis and as such has no associated direct mortality. However, there is an association with an increased © 2018 British Association of Dermatologists British Journal of Dermatology (2018) 179, pp163–172 163