Argenziano Giuseppe, Soyer H Peter, Chimenti Sergio, Talamini Renato, Corona Rosamaria, Sera Francesco, Binder Michael, Cerroni Lorenzo, De Rosa Gaetano, Ferrara Gerardo, Hofmann-Wellenhof Rainer, Landthaler Michael, Menzies Scott W, Pehamberger Hubert, Piccolo Domenico, Rabinovitz Harold S, Schiffner Roman, Staibano Stefania, Stolz Wilhelm, Bartenjev Igor, Blum Andreas, Braun Ralph, Cabo Horacio, Carli Paolo, De Giorgi Vincenzo, Fleming Matthew G, Grichnik James M, Grin Caron M, Halpern Allan C, Johr Robert, Katz Brian, Kenet Robert O, Kittler Harald, Kreusch Jürgen, Malvehy Josep, Mazzocchetti Giampiero, Oliviero Margaret, Ozdemir Fezal, Peris Ketty, Perotti Roberto, Perusquia Ana, Pizzichetta Maria Antonietta, Puig Susana, Rao Babar, Rubegni Pietro, Saida Toshiaki, Scalvenzi Massimiliano, Seidenari Stefania, Stanganelli Ignazio, Tanaka Masaru, Westerhoff Karin, Wolf Ingrid H, Braun-Falco Otto, Kerl Helmut, Nishikawa Takeji, Wolff Klaus, Kopf Alfred W
Department of Dermatology, Second University of Naples, Italy.
J Am Acad Dermatol. 2003 May;48(5):679-93. doi: 10.1067/mjd.2003.281.
There is a need for better standardization of the dermoscopic terminology in assessing pigmented skin lesions.
The virtual Consensus Net Meeting on Dermoscopy was organized to investigate reproducibility and validity of the various features and diagnostic algorithms.
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.
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).
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.
在评估色素性皮肤病变时，需要更好地规范皮肤镜术语。
组织皮肤镜虚拟共识网络会议，以研究各种特征和诊断算法的可重复性和有效性。
40名经验丰富的皮肤镜医师通过互联网，采用两步诊断程序对108个病变的皮肤镜图像进行评估。第一步算法区分黑素细胞性病变与非黑素细胞性病变。诊断程序的第二步使用4种算法（模式分析、ABCD规则、孟席斯方法和7分检查表）区分黑色素瘤与良性黑素细胞性病变。对所有诊断算法和皮肤镜特征估计kappa值、对数优势比、敏感性、特异性和阳性似然比。
所有诊断方法的观察者间一致性为中等至良好，但大多数皮肤镜标准的一致性较差。对于所有考虑的算法和特征，观察者内一致性为良好至优秀。模式分析具有最佳的诊断性能（阳性似然比：5.1），而其他算法显示出相当的敏感性，但特异性较低。皮肤镜检查做出的管理决策的观察者间一致性相当好（平均kappa值：0.53）。
皮肤镜虚拟共识网络会议是更好地规范皮肤镜术语的有效工具，而且为色素性皮肤病变的诊断和管理开辟了新领域。
