Dutch Society of Dermatology and Venereology, Utrecht, The Netherlands.
Dermapark, Uden, The Netherlands.
J Eur Acad Dermatol Venereol. 2020 Feb;34(2):274-278. doi: 10.1111/jdv.15873. Epub 2019 Sep 12.
Several smartphone applications (app) with an automated risk assessment claim to be able to detect skin cancer at an early stage. Various studies that have evaluated these apps showed mainly poor performance. However, all studies were done in patients and lesions were mainly selected by a specialist.
To investigate the performance of the automated risk assessment of an app by comparing its assessment to that of a dermatologist in lesions selected by the participants.
Participants of a National Skin Cancer Day were enrolled in a multicentre study. Skin lesions indicated by the participants were analysed by the automated risk assessment of the app prior to blinded rating by the dermatologist. The ratings of the automated risk assessment were compared to the assessment and diagnosis of the dermatologist. Due to the setting of the Skin Cancer Day, lesions were not verified by histopathology.
We included 125 participants (199 lesions). The app was not able to analyse 90 cases (45%) of which nine BCC, four atypical naevi and one lentigo maligna. Thirty lesions (67%) with a high and 21 with a medium risk (70%) rating by the app were diagnosed as benign naevi or seborrhoeic keratoses. The interobserver agreement between the ratings of the automated risk assessment and the dermatologist was poor (weighted kappa = 0.02; 95% CI -0.08-0.12; P = 0.74).
The rating of the automated risk assessment was poor. Further investigations about the diagnostic accuracy in real-life situations are needed to provide consumers with reliable information about this healthcare application.
有几款具有自动风险评估功能的智能手机应用声称能够早期发现皮肤癌。评估这些应用的各种研究表明，它们的性能主要较差。然而，所有的研究都是在患者中进行的，病变主要由专家选择。
通过比较应用程序的自动风险评估与参与者选择的皮肤科医生的评估，来研究应用程序的自动风险评估的性能。
在国家皮肤癌日，招募了多名参与者参加一项多中心研究。在由皮肤科医生进行盲法评估之前，参与者指示的皮肤病变由应用程序的自动风险评估进行分析。将自动风险评估的评分与皮肤科医生的评估和诊断进行比较。由于皮肤癌日的设置，病变未经组织病理学验证。
我们纳入了 125 名参与者（199 个病变）。应用程序无法分析 90 例（45%）病变，其中 9 例为基底细胞癌、4 例为不典型痣和 1 例恶性雀斑样痣。应用程序评分高风险（67%）和中风险（70%）的 30 个病变被诊断为良性痣或脂溢性角化病。自动风险评估评分和皮肤科医生之间的观察者间一致性较差（加权 κ=0.02；95%CI-0.08-0.12；P=0.74）。
自动风险评估的评分较差。需要进一步研究其在实际情况下的诊断准确性，以便为消费者提供有关这种医疗保健应用的可靠信息。
