Literature DB >> 23325302

Diagnostic inaccuracy of smartphone applications for melanoma detection.

Joel A Wolf1, Jacqueline F Moreau, Oleg Akilov, Timothy Patton, Joseph C English, Jonhan Ho, Laura K Ferris.   

Abstract

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.

Entities:  

Mesh:

Year:  2013        PMID: 23325302      PMCID: PMC4019431          DOI: 10.1001/jamadermatol.2013.2382

Source DB:  PubMed          Journal:  JAMA Dermatol        ISSN: 2168-6068            Impact factor:   10.282


  8 in total

1.  Smart phones: new clinical tools in oncology?

Authors:  Kathryn Senior
Journal:  Lancet Oncol       Date:  2011-05       Impact factor: 41.316

2.  A randomised control trial to determine if use of the iResus© application on a smart phone improves the performance of an advanced life support provider in a simulated medical emergency.

Authors:  D Low; N Clark; J Soar; A Padkin; A Stoneham; G D Perkins; J Nolan
Journal:  Anaesthesia       Date:  2011-04       Impact factor: 6.955

3.  Supporting autobiographical memory in patients with Alzheimer's disease using smart phones.

Authors:  Gianluca De Leo; Eleonora Brivio; Scott W Sautter
Journal:  Appl Neuropsychol       Date:  2011-01

4.  Patterns of detection in patients with cutaneous melanoma.

Authors:  M S Brady; S A Oliveria; P J Christos; M Berwick; D G Coit; J Katz; A C Halpern
Journal:  Cancer       Date:  2000-07-15       Impact factor: 6.860

5.  Surveillance of patients for early detection of melanoma: patterns in dermatologist vs patient discovery.

Authors:  Sean T McGuire; Aaron M Secrest; Ryan Andrulonis; Laura K Ferris
Journal:  Arch Dermatol       Date:  2011-06

6.  Is physician detection associated with thinner melanomas?

Authors:  D S Epstein; J R Lange; S B Gruber; M Mofid; S E Koch
Journal:  JAMA       Date:  1999-02-17       Impact factor: 56.272

7.  An analysis of data management tools for diabetes self-management: can smart phone technology keep up?

Authors:  Elizabeth Ciemins; Patricia Coon; Christopher Sorli
Journal:  J Diabetes Sci Technol       Date:  2010-07-01

8.  Routine dermatologist-performed full-body skin examination and early melanoma detection.

Authors:  Jonathan Kantor; Deborah E Kantor
Journal:  Arch Dermatol       Date:  2009-08
  8 in total
  80 in total

1.  The use of a mobile app to motivate evidence-based oral hygiene behaviour.

Authors:  B Underwood; J Birdsall; E Kay
Journal:  Br Dent J       Date:  2015-08-28       Impact factor: 1.626

Review 2.  Optimizing cancer care through mobile health.

Authors:  Bassel Odeh; Reem Kayyali; Shereen Nabhani-Gebara; Nada Philip
Journal:  Support Care Cancer       Date:  2015-02-04       Impact factor: 3.603

3.  [Telematics services and telemedicine under ophthalmological legal aspects].

Authors:  F Tost; G Freißler
Journal:  Ophthalmologe       Date:  2018-07       Impact factor: 1.059

4.  Characteristics and quality of genetics and genomics mobile apps: a systematic review.

Authors:  Divya Talwar; Yu-Lyu Yeh; Wei-Ju Chen; Lei-Shih Chen
Journal:  Eur J Hum Genet       Date:  2019-02-26       Impact factor: 4.246

5.  Accuracy and stability testing of a 'smart dresser' for persons with dementia.

Authors:  D F Mahoney; W Burleson; J Rowe; E L Mahoney
Journal:  Gerontechnology       Date:  2016

6.  A Cross-Sectional Study of Prominent US Mobile Health Applications: Evaluating the Current Landscape.

Authors:  Pierre-Antoine Fougerouse; Mobin Yasini; Guillaume Marchand; Oliver O Aalami
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

7.  [Image-based computer diagnosis of melanoma].

Authors:  V Dick; P Tschandl; C Sinz; A Blum; H Kittler
Journal:  Hautarzt       Date:  2018-07       Impact factor: 0.751

8.  Impact of a smartphone application on skin self-examination rates in patients who are new to total body photography: A randomized controlled trial.

Authors:  Andrew J Marek; Emily Y Chu; Michael E Ming; Zeeshan A Khan; Carrie L Kovarik
Journal:  J Am Acad Dermatol       Date:  2018-02-10       Impact factor: 11.527

Review 9.  The promise and peril of mobile health applications for diabetes and endocrinology.

Authors:  Donna S Eng; Joyce M Lee
Journal:  Pediatr Diabetes       Date:  2013-04-30       Impact factor: 4.866

Review 10.  The digital age of melanoma management: detection and diagnostics.

Authors:  Alexander L Fogel; Kavita Sarin
Journal:  Melanoma Manag       Date:  2015-11-26
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