Literature DB >> 12786829

Pattern analysis, not simplified algorithms, is the most reliable method for teaching dermoscopy for melanoma diagnosis to residents in dermatology.

P Carli1, E Quercioli, S Sestini, M Stante, L Ricci, G Brunasso, V De Giorgi.   

Abstract

BACKGROUND: Simplified algorithms for dermoscopy in melanoma diagnosis were developed in order to facilitate the use of this technique by non-experts. However, little is known about their reliability compared with classic pattern analysis when taught to untrained observers.
OBJECTIVES: To investigate the diagnostic performance of three different methods, i.e. classic pattern analysis and two of the most used algorithms (the ABCD rule of dermoscopy and the seven-point check-list) when used by newly trained residents in dermatology to diagnose melanocytic lesions. Methods Five residents in dermatology (University of Florence Medical School) were submitted to a teaching programme in dermoscopy based on both formal lessons and training and self-assessment using a newly developed, interactive CD-ROM on dermoscopy. The performance of the three diagnostic methods was analysed in a series of 200 clinically equivocal melanocytic lesions including 44 early melanomas (median thickness 0.30 mm; 25th-75th percentile 0.00-0.58 mm).
RESULTS: Pattern analysis yielded the best mean diagnostic accuracy (68.7%), followed by the ABCD rule (56.1%) and the seven-point check-list (53.4%, P = 0.06). The best sensitivity was associated with the use of the seven-point check-list (91.9%), which, however, provided the worst specificity (35.2%) of the methods tested. The interobserver reproducibility, as shown by kappa statistics, was low for all the methods (range 0.27-0.33) and did not show any statistical difference among them.
CONCLUSIONS: Pattern analysis, i.e. simultaneous assessment of the diagnostic value of all dermoscopy features shown by the lesion, proved to be the most reliable procedure for melanoma diagnosis to be taught to residents in dermatology.

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Year:  2003        PMID: 12786829     DOI: 10.1046/j.1365-2133.2003.05023.x

Source DB:  PubMed          Journal:  Br J Dermatol        ISSN: 0007-0963            Impact factor:   9.302


  12 in total

Review 1.  Strategies for early melanoma detection: Approaches to the patient with nevi.

Authors:  Agnessa Gadeliya Goodson; Douglas Grossman
Journal:  J Am Acad Dermatol       Date:  2009-05       Impact factor: 11.527

2.  Categorization of Common Pigmented Skin Lesions (CPSL) using Multi-Deep Features and Support Vector Machine.

Authors:  Prabira Kumar Sethy; Santi Kumari Behera; Nithiyanathan Kannan
Journal:  J Digit Imaging       Date:  2022-05-06       Impact factor: 4.903

3.  Cyclin D1 and D3 expression in melanocytic skin lesions.

Authors:  Ana Alekseenko; Anna Wojas-Pelc; Grzegorz J Lis; Alicja Furgał-Borzych; Grzegorz Surówka; Jan A Litwin
Journal:  Arch Dermatol Res       Date:  2010-05-23       Impact factor: 3.017

4.  Validity and Reliability of Dermoscopic Criteria Used to Differentiate Nevi From Melanoma: A Web-Based International Dermoscopy Society Study.

Authors:  Cristina Carrera; Michael A Marchetti; Stephen W Dusza; Giuseppe Argenziano; Ralph P Braun; Allan C Halpern; Natalia Jaimes; Harald J Kittler; Josep Malvehy; Scott W Menzies; Giovanni Pellacani; Susana Puig; Harold S Rabinovitz; Alon Scope; H Peter Soyer; Wilhelm Stolz; Rainer Hofmann-Wellenhof; Iris Zalaudek; Ashfaq A Marghoob
Journal:  JAMA Dermatol       Date:  2016-07-01       Impact factor: 10.282

5.  Detection of Malignant Melanoma Using Artificial Intelligence: An Observational Study of Diagnostic Accuracy.

Authors:  Michael Phillips; Jack Greenhalgh; Helen Marsden; Ioulios Palamaras
Journal:  Dermatol Pract Concept       Date:  2019-12-31

6.  Dermoscopy Training Effect on Diagnostic Accuracy of Skin Lesions in Canadian Family Medicine Physicians Using the Triage Amalgamated Dermoscopic Algorithm.

Authors:  Elizabeth A Sawyers; Donald T Wigle; Ashfaq A Marghoob; Andreas Blum
Journal:  Dermatol Pract Concept       Date:  2020-04-03

7.  Predicting the clinical management of skin lesions using deep learning.

Authors:  Kumar Abhishek; Jeremy Kawahara; Ghassan Hamarneh
Journal:  Sci Rep       Date:  2021-04-08       Impact factor: 4.379

8.  Visual inspection and dermoscopy, alone or in combination, for diagnosing keratinocyte skin cancers in adults.

Authors:  Jacqueline Dinnes; Jonathan J Deeks; Naomi Chuchu; Rubeta N Matin; Kai Yuen Wong; Roger Benjamin Aldridge; Alana Durack; Abha Gulati; Sue Ann Chan; Louise Johnston; Susan E Bayliss; Jo Leonardi-Bee; Yemisi Takwoingi; Clare Davenport; Colette O'Sullivan; Hamid Tehrani; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

9.  Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults.

Authors:  Jacqueline Dinnes; Jonathan J Deeks; Naomi Chuchu; Lavinia Ferrante di Ruffano; Rubeta N Matin; David R Thomson; Kai Yuen Wong; Roger Benjamin Aldridge; Rachel Abbott; Monica Fawzy; Susan E Bayliss; Matthew J Grainge; Yemisi Takwoingi; Clare Davenport; Kathie Godfrey; Fiona M Walter; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

10.  Strategies for early recognition of cutaneous melanoma-present and future.

Authors:  Franziska Brehmer; Martina Ulrich; Holger A Haenssle
Journal:  Dermatol Pract Concept       Date:  2012-07-31
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