Ngoo Alexander, Finnane Anna, McMeniman Erin, Tan Jean-Marie, Janda Monika, Soyer H Peter
Dermatology Research Centre, School of Medicine, University of Queensland, Brisbane, Queensland, Australia.
Department of Dermatology, Princess Alexandra Hospital, Brisbane, Queensland, Australia.
Australas J Dermatol. 2018 Aug;59(3):e175-e182. doi: 10.1111/ajd.12599. Epub 2017 Feb 27.
BACKGROUND/OBJECTIVES: Melanoma apps are smartphone applications that assess risk of pigmented lesions using a smartphone camera and underlying algorithm. We aimed to assess the capability of melanoma smartphone applications (apps) in making clinical decisions about risk, compared with lesion assessment by specialist trained dermatologists.
A prospective study of 3 melanoma apps was conducted between 2015 and 2016, recruiting 30 patients with 57 pigmented lesions. Risk categories assigned by the apps were compared with the clinical decisions of two consultant dermatologists classifying lesions as 'suspicious' or 'benign'.
Of the 42 lesions deemed clinically suspicious to a dermatologist, from 9 to 26 were classified as suspicious by the apps; of the 15 clinically benign lesions 3 to 15 were correctly classified as benign by the apps. The apps' sensitivity and specificity ranged from 21 to 72% and 27 to 100.0%, respectively, when compared with the specialists' decisions. Two apps were unable to analyse 14 and 18% of lesions submitted, respectively. Interrater agreement between dermatologists and apps was poor (κ = -0.01 SE = 0.16; P = 0.97) to slight (κ = 0.16 SE = 0.09; P = 0.12).
None of the melanoma apps tested had high enough agreement with the dermatologist's clinical opinion to be considered to provide additional benefit to patients in assessing their skin for high-risk pigmented lesions. The low sensitivity in detecting lesions that are suspicious to a trained specialist may mean false reassurance is being given to patients. Development of highly sensitive and specific melanoma apps remains a work in progress.
背景/目的:黑色素瘤应用程序是利用智能手机摄像头和底层算法评估色素沉着病变风险的智能手机应用。我们旨在评估黑色素瘤智能手机应用在做出风险临床决策方面的能力,并与经过专业培训的皮肤科医生进行的病变评估作比较。
2015年至2016年对3款黑色素瘤应用程序进行了一项前瞻性研究,招募了30名患有57处色素沉着病变的患者。将应用程序指定的风险类别与两位皮肤科顾问医生将病变分类为“可疑”或“良性”的临床决策进行比较。
在皮肤科医生认为临床上可疑的42处病变中,应用程序将9至26处分类为可疑;在15处临床良性病变中,应用程序将3至15处正确分类为良性。与专家的决策相比,应用程序的敏感性和特异性分别为21%至72%和27%至100.0%。两款应用程序分别无法分析提交病变的14%和18%。皮肤科医生与应用程序之间的评分者间一致性较差(κ=-0.01,标准误=0.16;P=0.97)至轻微(κ=0.16,标准误=0.09;P=0.12)。
所测试的黑色素瘤应用程序中,没有一款与皮肤科医生的临床意见有足够高的一致性,从而在评估患者皮肤的高风险色素沉着病变时被认为能为患者带来额外益处。检测对训练有素的专家可疑的病变时敏感性较低,这可能意味着在向患者提供错误的安心保证。高敏感性和特异性的黑色素瘤应用程序的开发仍在进行中。