Efficacy of smartphone applications in high-risk pigmented lesions
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.
© 2017 The Australasian College of Dermatologists
Ngoo A , McMeniman E, Tan JM, Soyer HP (Dermatology Research Centre, School of Medicine, University of Queensland, Brisbane, Queensland, Australia)
Finnane A,McMeniman E, Soyer HP (Department of Dermatology, Princess Alexandra Hospital, Brisbane, Queensland, Australia)
Janda M (School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia)