Dermatology Unit, Department of Medical, Surgical and Neurosciences, University of Siena, Siena, Italy.
Department of Medical Biotechnologies, University of Siena, Siena, Italy.
J Eur Acad Dermatol Venereol. 2023 Nov;37(11):2301-2310. doi: 10.1111/jdv.19360. Epub 2023 Jul 26.
Due to progressive ageing of the population, the incidence of facial lentigo maligna (LM) of the face is increasing. Many benign simulators of LM and LMM, known as atypical pigmented facial lesions (aPFLs-pigmented actinic keratosis, solar lentigo, seborrheic keratosis, seborrheic-lichenoid keratosis, atypical nevus) may be found on photodamaged skin. This generates many diagnostic issues and increases the number of biopsies, with a subsequent impact on aesthetic outcome and health insurance costs.
Our aim was to develop a risk-scoring classifier-based algorithm to estimate the probability of an aPFL being malignant. A second aim was to compare its diagnostic accuracy with that of dermoscopists so as to define the advantages of using the model in patient management.
A total of 154 dermatologists analysed 1111 aPFLs and their management in a teledermatology setting: They performed pattern analysis, gave an intuitive clinical diagnosis and proposed lesion management options (follow-up/reflectance confocal microscopy/biopsy). Each case was composed of a dermoscopic and/or clinical picture plus metadata (histology, age, sex, location, diameter). The risk-scoring classifier was developed and tested on this dataset and then validated on 86 additional aPFLs.
The facial Integrated Dermoscopic Score (iDScore) model consisted of seven dermoscopic variables and three objective parameters (diameter ≥ 8 mm, age ≥ 70 years, male sex); the score ranged from 0 to 16. In the testing set, the facial iDScore-aided diagnosis was more accurate (AUC = 0.79 [IC 95% 0.757-0.843]) than the intuitive diagnosis proposed by dermatologists (average of 43.5%). In the management study, the score model reduced the number of benign lesions sent for biopsies by 41.5% and increased the number of LM/LMM cases sent for reflectance confocal microscopy or biopsy instead of follow-up by 66%.
The facial iDScore can be proposed as a feasible tool for managing patients with aPFLs.
由于人口老龄化的进展，面部恶性雀斑样痣（LM）的发病率正在增加。许多 LM 和 LM 恶性前体的良性模拟物，称为非典型色素性面部病变（aPFL-色素性光化性角化病、老年性黑子、脂溢性角化病、脂溢性苔藓样角化病、非典型痣），可能出现在光损伤皮肤上。这会产生许多诊断问题，并增加活检数量，从而对美容效果和健康保险费用产生后续影响。
我们旨在开发一种基于风险评分分类器的算法，以估计 aPFL 恶性的概率。第二个目的是比较其与皮肤科医生的诊断准确性，以确定在患者管理中使用该模型的优势。
共有 154 名皮肤科医生在远程皮肤科环境中分析了 1111 例 aPFL 及其处理情况：他们进行了模式分析，给出了直观的临床诊断，并提出了病变处理选择（随访/反射共聚焦显微镜/活检）。每个病例由一个皮肤镜和/或临床图片加上元数据（组织学、年龄、性别、位置、直径）组成。风险评分分类器在该数据集上进行了开发和测试，然后在另外 86 例 aPFL 上进行了验证。
面部综合皮肤镜评分（iDScore）模型由七个皮肤镜变量和三个客观参数（直径≥8mm、年龄≥70 岁、男性）组成；评分范围为 0 至 16。在测试集中，面部 iDScore 辅助诊断比皮肤科医生提出的直观诊断（平均 43.5%）更准确（AUC=0.79[95%CI 0.757-0.843]）。在管理研究中，该评分模型减少了 41.5%的良性病变进行活检的数量，并增加了 66%的 LM/LMM 病例进行反射共聚焦显微镜或活检而不是随访的数量。
面部 iDScore 可作为管理 aPFL 患者的一种可行工具。
