BACKGROUND: There is a need for better standardization of the dermoscopic terminology in assessing pigmented skin lesions. OBJECTIVE: The virtual Consensus Net Meeting on Dermoscopy was organized to investigate reproducibility and validity of the various features and diagnostic algorithms. METHODS: Dermoscopic images of 108 lesions were evaluated via the Internet by 40 experienced dermoscopists using a 2-step diagnostic procedure. The first-step algorithm distinguished melanocytic versus nonmelanocytic lesions. The second step in the diagnostic procedure used 4 algorithms (pattern analysis, ABCD rule, Menzies method, and 7-point checklist) to distinguish melanoma versus benign melanocytic lesions. kappa Values, log odds ratios, sensitivity, specificity, and positive likelihood ratios were estimated for all diagnostic algorithms and dermoscopic features. RESULTS: Interobserver agreement was fair to good for all diagnostic methods, but it was poor for the majority of dermoscopic criteria. Intraobserver agreement was good to excellent for all algorithms and features considered. Pattern analysis allowed the best diagnostic performance (positive likelihood ratio: 5.1), whereas alternative algorithms revealed comparable sensitivity but less specificity. Interobserver agreement on management decisions made by dermoscopy was fairly good (mean kappa value: 0.53). CONCLUSION: The virtual Consensus Net Meeting on Dermoscopy represents a valid tool for better standardization of the dermoscopic terminology and, moreover, opens up a new territory for diagnosing and managing pigmented skin lesions.
BACKGROUND: There is a need for better standardization of the dermoscopic terminology in assessing pigmented skin lesions. OBJECTIVE: The virtual Consensus Net Meeting on Dermoscopy was organized to investigate reproducibility and validity of the various features and diagnostic algorithms. METHODS: Dermoscopic images of 108 lesions were evaluated via the Internet by 40 experienced dermoscopists using a 2-step diagnostic procedure. The first-step algorithm distinguished melanocytic versus nonmelanocytic lesions. The second step in the diagnostic procedure used 4 algorithms (pattern analysis, ABCD rule, Menzies method, and 7-point checklist) to distinguish melanoma versus benign melanocytic lesions. kappa Values, log odds ratios, sensitivity, specificity, and positive likelihood ratios were estimated for all diagnostic algorithms and dermoscopic features. RESULTS: Interobserver agreement was fair to good for all diagnostic methods, but it was poor for the majority of dermoscopic criteria. Intraobserver agreement was good to excellent for all algorithms and features considered. Pattern analysis allowed the best diagnostic performance (positive likelihood ratio: 5.1), whereas alternative algorithms revealed comparable sensitivity but less specificity. Interobserver agreement on management decisions made by dermoscopy was fairly good (mean kappa value: 0.53). CONCLUSION: The virtual Consensus Net Meeting on Dermoscopy represents a valid tool for better standardization of the dermoscopic terminology and, moreover, opens up a new territory for diagnosing and managing pigmented skin lesions.
Authors: Ankur Dalal; Randy H Moss; R Joe Stanley; William V Stoecker; Kapil Gupta; David A Calcara; Jin Xu; Bijaya Shrestha; Rhett Drugge; Joseph M Malters; Lindall A Perry Journal: Comput Med Imaging Graph Date: 2010-11-12 Impact factor: 4.790
Authors: William V Stoecker; Mark Wronkiewiecz; Raeed Chowdhury; R Joe Stanley; Jin Xu; Austin Bangert; Bijaya Shrestha; David A Calcara; Harold S Rabinovitz; Margaret Oliviero; Fatimah Ahmed; Lindall A Perry; Rhett Drugge Journal: Comput Med Imaging Graph Date: 2010-10-30 Impact factor: 4.790
Authors: M Emre Celebi; Hitoshi Iyatomi; William V Stoecker; Randy H Moss; Harold S Rabinovitz; Giuseppe Argenziano; H Peter Soyer Journal: Comput Med Imaging Graph Date: 2008-09-19 Impact factor: 4.790
Authors: A Blum; J Kreusch; W Stolz; H Haenssle; R Braun; R Hofmann-Wellenhof; P Tschandl; I Zalaudek; H Kittler Journal: Hautarzt Date: 2017-08 Impact factor: 0.751
Authors: M C Fargnoli; F Sera; M Suppa; D Piccolo; M T Landi; A Chiarugi; C Pellegrini; S Seidenari; K Peris Journal: J Eur Acad Dermatol Venereol Date: 2014-03-04 Impact factor: 6.166