Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma

Chuchu, Naomi, Takwoingi, Yemisi, Dinnes, Jacqueline, Matin, Rubeta N., Bassett, Oliver, Moreau, Jacqueline F., Bayliss, Susan E., Davenport, Clare, Godfrey, Kathie, Jain, Abhilash, Walter, Fiona M., Deeks, Jonathan J. and Williams, Hywel C. (2018) Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma. Cochrane Database of Systematic Reviews . ISSN 1469-493X (In Press)

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Background: Melanoma accounts for a small proportion of all skin cancer cases but is responsible for the majority of skin cancer-related deaths. Early detection and treatment can improve survival. Smartphone applications are readily accessible and potentially offer an instant risk assessment of the likelihood of malignancy, so that the right people seek further medical attention from a clinician for more detailed assessment of the lesion. There is, however, a risk that melanomas will be missed and treatment delayed if the application reassures the user that their lesion is low risk.

Objectives: To determine the diagnostic accuracy of smartphone applications to rule out cutaneous invasive melanoma and intraepidermal melanocytic variants in adults with concerns about suspicious skin lesions.

Search methods: We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles.

Selection criteria: Studies of any design evaluating smartphone applications intended for use by individuals in a community setting who have lesions that might be suspicious for melanoma or intraepidermal melanocytic variants compared with a reference standard of histological confirmation or clinical follow-up and expert opinion.

Data collection and analysis: Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). Due to scarcity of data and poor quality of studies, no meta-analysis was undertaken for this review. For illustrative purposes, estimates of sensitivity and specificity were plotted on coupled forest plots for each application under consideration.

Main results: This review reports on two cohorts of lesions published in two studies. Both studies were at high risk of bias from selective participant recruitment, and high rates of non-evaluable images. Concerns about applicability of findings were high due to inclusion only of lesions already selected for excision in a dermatology clinic setting, and image acquisition by clinicians rather than by smartphone app users. Data for five mobile phone applications were reported for 332 suspicious skin lesions with 86 melanomas across the two studies. Across the four artificial intelligence-based applications which classified lesion images (photographs) as melanomas (one application) or as high risk or ‘problematic’ lesions (three applications) using a pre-programmed algorithm, sensitivities ranged from 7% (95% CI: 2%, 16%) to 73% (95% CI: 52%, 88%) and specificities from 37% (95% CI: 29% to 46%) to 94% (95% CI: 87%, 97%). The single application using store-and-forward review of lesion images by a dermatologist had a sensitivity of 98% (95% CI: 90%, 100%) and specificity 30% (95% CI: 22%, 40%). The number of test failures (lesion images analysed by the applications but classed as ‘not evaluable’ and excluded by the study authors) ranged from 3 to 31 (or 2% to 18% of lesions analysed). The store-and-forward application had one of the highest rates of test failure (15%). At least one melanoma was classed as ‘not evaluable’ in three of the four application evaluations.

Authors' conclusions: Smartphone applications using artificial intelligence-based analysis have not yet demonstrated sufficient promise in terms of accuracy, and are associated with a high likelihood of missing melanomas. Applications based on store-and-forward images could have a potential role in the timely presentation of people with potentially malignant lesions by facilitating active self-management health practices and early engagement of those with suspicious skin lesions; however, they may incur a significant increase in resource and workload. Given the paucity of evidence and low methodological quality, no implications for practice can be drawn. Nevertheless, this is a rapidly advancing field and new and better applications with robust reporting of studies could change these conclusions substantially.

Item Type: Article
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Medicine
Depositing User: Eprints, Support
Date Deposited: 15 Jun 2018 12:37
Last Modified: 04 May 2020 19:40

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