Department of Dermatology, Georg August University Göttingen, Göttingen, Germany.
J Am Acad Dermatol. 2012 Jan;66(1):27-36. doi: 10.1016/j.jaad.2010.09.731. Epub 2011 Jun 11.
Sequential digital dermatoscopy identifies dynamic changes in melanocytic lesions. However, no algorithm exists that systematically weights dynamic changes regarding their association with melanoma.
We sought to identify relevant dynamic changes and to integrate these into a novel diagnostic algorithm.
During follow-up (mean 44.28 months) of 688 patients at high risk, 675 pigmented lesions with prospectively documented dynamic changes were excised. The association between specific changes and melanoma was assessed.
We detected 61 melanomas (38 invasive, median thickness 0.42 mm) with dynamic changes. Multivariate logistic regression analyses revealed a significant association between the diagnosis of melanoma and 5 dynamic criteria. According to the observed odds ratios we defined two dynamic major criteria (2 points each: asymmetric-multifocal enlargement and architectural change) and 3 dynamic minor criteria (1 point each: focal increase in pigmentation, focal decrease in pigmentation, and overall decrease in pigmentation when not accompanied by a lighter pigmentation of the adjacent skin). The DynaMel score was generated by addition of dynamic and 7-point checklist scores with a threshold for excision of 3 or more points. Including information about dynamic changes increased the sensitivity of the 7-point checklist from 47.5% (29 of 61 melanomas detected) to 77.1% (47 of 61 melanomas detected). The specificity slightly decreased from 99.0% to 98.1%.
Before broad application the DynaMel algorithm needs to be validated using data from a different prospective study.
The DynaMel algorithm integrates a scoring system for dynamic dermatoscopic changes into the 7-point checklist for dermatoscopy and thereby increased the sensitivity of melanoma detection.
连续数码皮肤镜可识别黑素细胞病变的动态变化。然而，目前尚不存在一种算法能够系统地对与黑色素瘤相关的动态变化进行加权。
我们旨在确定相关的动态变化，并将其整合到一种新的诊断算法中。
在对 688 名高危患者进行的随访（平均随访时间为 44.28 个月）中，前瞻性记录了 675 个有动态变化的色素性病变，并对其进行了切除。评估了特定变化与黑色素瘤之间的关联。
我们共发现 61 例黑色素瘤（38 例侵袭性，中位厚度为 0.42mm）存在动态变化。多变量逻辑回归分析显示，诊断为黑色素瘤与 5 项动态标准显著相关。根据观察到的比值比，我们定义了两个动态主要标准（各 2 分：不对称多灶性增大和结构改变）和 3 个动态次要标准（各 1 分：色素沉着局灶性增加、色素沉着局灶性减少以及当相邻皮肤未出现更浅色色素沉着时色素沉着总体减少）。通过添加动态和 7 点检查表评分来生成 DynaMel 评分，切除阈值为 3 分或以上。包括动态变化信息后，7 点检查表的敏感性从 47.5%（61 例黑色素瘤中发现 29 例）提高到 77.1%（61 例黑色素瘤中发现 47 例）。特异性从 99.0%略有下降至 98.1%。
在广泛应用之前，DynaMel 算法需要使用来自另一项前瞻性研究的数据进行验证。
DynaMel 算法将动态皮肤镜变化的评分系统整合到 7 点皮肤镜检查表中，从而提高了黑色素瘤的检测敏感性。
