Document Detail


Diagnostic inaccuracy of smartphone applications for melanoma detection.
MedLine Citation:
PMID:  23325302     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVE: To measure the performance of smartphone applications that evaluate photographs of skin lesions and provide the user with feedback about the likelihood of malignancy.
DESIGN: Case-control diagnostic accuracy study.
SETTING: Academic dermatology department. PARTICIPANTS AND MATERIALS: Digital clinical images of pigmented cutaneous lesions (60 melanoma and 128 benign control lesions) with a histologic diagnosis rendered by a board-certified dermatopathologist, obtained before biopsy from patients undergoing lesion removal as a part of routine care.
MAIN OUTCOME MEASURES: Sensitivity, specificity, and positive and negative predictive values of 4 smartphone applications designed to aid nonclinician users in determining whether their skin lesion is benign or malignant.
RESULTS: Sensitivity of the 4 tested applications ranged from 6.8% to 98.1%; specificity, 30.4% to 93.7%; positive predictive value, 33.3% to 42.1%; and negative predictive value, 65.4% to 97.0%. The highest sensitivity for melanoma diagnosis was observed for an application that sends the image directly to a board-certified dermatologist for analysis; the lowest, for applications that use automated algorithms to analyze images.
CONCLUSIONS: The performance of smartphone applications in assessing melanoma risk is highly variable, and 3 of 4 smartphone applications incorrectly classified 30% or more of melanomas as unconcerning. Reliance on these applications, which are not subject to regulatory oversight, in lieu of medical consultation can delay the diagnosis of melanoma and harm users.
Authors:
Joel A Wolf; Jacqueline F Moreau; Oleg Akilov; Timothy Patton; Joseph C English; Jonhan Ho; Laura K Ferris
Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  JAMA dermatology     Volume:  149     ISSN:  2168-6084     ISO Abbreviation:  JAMA Dermatol     Publication Date:  2013 Apr 
Date Detail:
Created Date:  2013-06-11     Completed Date:  2013-07-30     Revised Date:  2013-12-13    
Medline Journal Info:
Nlm Unique ID:  101589530     Medline TA:  JAMA Dermatol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  422-6     Citation Subset:  AIM; IM    
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Cellular Phone*
Computers, Handheld*
Dermoscopy
Diagnosis, Differential
Diagnostic Errors*
Electronic Mail
Humans
Image Interpretation, Computer-Assisted / methods
Melanoma / diagnosis*
ROC Curve
Skin Neoplasms / diagnosis*
Software*
Telemedicine / instrumentation*
User-Computer Interface
Video Recording / methods
Grant Support
ID/Acronym/Agency:
UL1 RR024153/RR/NCRR NIH HHS; UL1RR024153/RR/NCRR NIH HHS; UL1TR000005/TR/NCATS NIH HHS
Comments/Corrections
Comment In:
JAMA Dermatol. 2013 Jul;149(7):885   [PMID:  23864095 ]
JAMA Dermatol. 2013 Jul;149(7):884   [PMID:  23864094 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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