Jahn Anna Sophie, Navarini Alexander Andreas, Cerminara Sara Elisa, Kostner Lisa, Huber Stephanie Marie, Kunz Michael, Maul Julia-Tatjana, Dummer Reinhard, Sommer Seraina, Neuner Anja Dominique, Levesque Mitchell Paul, Cheng Phil Fang, Maul Lara Valeska
Department of Dermatology, University Hospital of Basel, 4031 Basel, Switzerland.
Department of Dermatology, University Hospital of Zurich, 8091 Zurich, Switzerland.
Cancers (Basel). 2022 Aug 7;14(15):3829. doi: 10.3390/cancers14153829.
The exponential increase in algorithm-based mobile health (mHealth) applications (apps) for melanoma screening is a reaction to a growing market. However, the performance of available apps remains to be investigated. In this prospective study, we investigated the diagnostic accuracy of a class 1 CE-certified smartphone app in melanoma risk stratification and its patient and dermatologist satisfaction. Pigmented skin lesions ≥ 3 mm and any suspicious smaller lesions were assessed by the smartphone app SkinVision (SkinVision B.V., Amsterdam, the Netherlands, App-Version 6.8.1), 2D FotoFinder ATBM master (FotoFinder ATBM Systems GmbH, Bad Birnbach, Germany, Version 3.3.1.0), 3D Vectra WB360 (Canfield Scientific, Parsippany, NJ, USA, Version 4.7.1) total body photography (TBP) devices, and dermatologists. The high-risk score of the smartphone app was compared with the two gold standards: histological diagnosis, or if not available, the combination of dermatologists', 2D and 3D risk assessments. A total of 1204 lesions among 114 patients (mean age 59 years; 51% females (55 patients at high-risk for developing a melanoma, 59 melanoma patients)) were included. The smartphone app's sensitivity, specificity, and area under the receiver operating characteristics (AUROC) varied between 41.3-83.3%, 60.0-82.9%, and 0.62-0.72% according to two study-defined reference standards. Additionally, all patients and dermatologists completed a newly created questionnaire for preference and trust of screening type. The smartphone app was rated as trustworthy by 36% (20/55) of patients at high-risk for melanoma, 49% (29/59) of melanoma patients, and 8.8% (10/114) of dermatologists. Most of the patients rated the 2D TBP imaging (93% (51/55) resp. 88% (52/59)) and the 3D TBP imaging (91% (50/55) resp. 90% (53/59)) as trustworthy. A skin cancer screening by combination of dermatologist and smartphone app was favored by only 1.8% (1/55) resp. 3.4% (2/59) of the patients; no patient preferred an assessment by a smartphone app alone. The diagnostic accuracy in clinical practice was not as reliable as previously advertised and the satisfaction with smartphone apps for melanoma risk stratification was scarce. MHealth apps might be a potential medium to increase awareness for melanoma screening in the lay population, but healthcare professionals and users should be alerted to the potential harm of over-detection and poor performance. In conclusion, we suggest further robust evidence-based evaluation before including market-approved apps in self-examination for public health benefits.
基于算法的移动医疗(mHealth)应用程序(app)在黑色素瘤筛查方面呈指数级增长,这是对不断增长的市场的一种反应。然而,现有应用程序的性能仍有待研究。在这项前瞻性研究中,我们调查了一款获得1类CE认证的智能手机应用程序在黑色素瘤风险分层中的诊断准确性及其患者和皮肤科医生的满意度。皮肤色素沉着病变≥3毫米以及任何可疑的较小病变由智能手机应用程序SkinVision(荷兰阿姆斯特丹的SkinVision B.V.,应用程序版本6.8.1)、2D FotoFinder ATBM master(德国巴特比尔恩巴赫的FotoFinder ATBM Systems GmbH,版本3.3.1.0)、3D Vectra WB360(美国新泽西州帕西帕尼的Canfield Scientific,版本4.7.1)全身摄影(TBP)设备以及皮肤科医生进行评估。将智能手机应用程序的高风险评分与两个金标准进行比较:组织学诊断,或者如果没有组织学诊断,则将皮肤科医生的二维和三维风险评估相结合。共纳入114例患者(平均年龄59岁;51%为女性(55例有发展为黑色素瘤高风险的患者,59例黑色素瘤患者))的1204个病变。根据两项研究定义的参考标准,智能手机应用程序的敏感性、特异性和受试者工作特征曲线下面积(AUROC)在41.3 - 83.3%、60.0 - 82.9%和0.62 - 0.72%之间变化。此外,所有患者和皮肤科医生都完成了一份新创建的关于筛查类型偏好和信任度的问卷。黑色素瘤高风险患者中有36%(20/55)、黑色素瘤患者中有49%(29/59)以及皮肤科医生中有8.8%(10/114)将智能手机应用程序评为值得信赖。大多数患者将二维TBP成像(分别为93%(51/55)和88%(52/59))以及三维TBP成像(分别为91%(50/55)和90%(53/59))评为值得信赖。只有1.8%(1/55)的患者和3.4%(2/59)的患者赞成由皮肤科医生和智能手机应用程序联合进行皮肤癌筛查;没有患者仅偏好由智能手机应用程序进行评估。临床实践中的诊断准确性并不像之前宣传的那么可靠,对用于黑色素瘤风险分层的智能手机应用程序的满意度也很低。移动医疗应用程序可能是提高普通人群对黑色素瘤筛查认识的一种潜在媒介,但医疗保健专业人员和用户应警惕过度检测和性能不佳的潜在危害。总之,我们建议在将市场批准的应用程序纳入用于公共卫生益处的自我检查之前,进行进一步有力的基于证据的评估。