Literature DB >> 9146533

Who removes pigmented skin lesions?

R Marks1, D Jolley, C McCormack, A P Dorevitch.   

Abstract

BACKGROUND: Increasing numbers of pigmented skin lesions are being removed because of concern about possible malignancy.
OBJECTIVE: Our purpose was to determine the ratio of benign to malignant pigmented tumors removed by different categories of physician and to verify whether any improvement had occurred after 5 years of educational programs.
METHODS: All pigmented lesions submitted to a major histopathology service in the years 1989 and 1994 were assessed as to the category of physician who removed the lesion, tumor type, and age and sex of the patient.
RESULTS: Dermatologists had the lowest benign/malignant ratio and general practitioners had the highest. General practitioners appeared to have difficulty differentiating both seborrheic keratoses and melanocytic nevi from malignant lesions; the frequency of these benign lesions was highly dependent on the age of the patient. During the 5-year period we observed an improvement among general practitioners in the benign/malignant ratio for melanocytic nevi, but not for seborrheic keratoses.
CONCLUSION: There is room for improvement by physicians in differentiating both melanocytic nevi and seborrheic keratoses from melanomas. This is especially true for general practitioners, from whom the public in Australia and in other countries is encouraged to first seek advice about a suspect pigmented lesion.

Entities:  

Mesh:

Year:  1997        PMID: 9146533     DOI: 10.1016/s0190-9622(97)80324-6

Source DB:  PubMed          Journal:  J Am Acad Dermatol        ISSN: 0190-9622            Impact factor:   11.527


  18 in total

1.  A Randomized Trial on the Efficacy of Mastery Learning for Primary Care Provider Melanoma Opportunistic Screening Skills and Practice.

Authors:  June K Robinson; Namita Jain; Ashfaq A Marghoob; William McGaghie; Michael MacLean; Pedram Gerami; Brittney Hultgren; Rob Turrisi; Kimberly Mallett; Gary J Martin
Journal:  J Gen Intern Med       Date:  2018-02-05       Impact factor: 5.128

2.  Novice identification of melanoma: not quite as straightforward as the ABCDs.

Authors:  R Benjamin Aldridge; Matteo Zanotto; Lucia Ballerini; Robert B Fisher; Jonathan L Rees
Journal:  Acta Derm Venereol       Date:  2011-03       Impact factor: 4.437

3.  A systematic heuristic approach for feature selection for melanoma discrimination using clinical images.

Authors:  Ying Chang; R Joe Stanley; Randy H Moss; William Van Stoecker
Journal:  Skin Res Technol       Date:  2005-08       Impact factor: 2.365

4.  Meta-analysis of number needed to treat for diagnosis of melanoma by clinical setting.

Authors:  Amy J Petty; Bradley Ackerson; Reed Garza; Michael Peterson; Beiyu Liu; Cynthia Green; Michelle Pavlis
Journal:  J Am Acad Dermatol       Date:  2020-01-11       Impact factor: 11.527

5.  Cost-effectiveness of Skin Cancer Referral and Consultation Using Teledermoscopy in Australia.

Authors:  Centaine L Snoswell; Liam J Caffery; Jennifer A Whitty; H Peter Soyer; Louisa G Gordon
Journal:  JAMA Dermatol       Date:  2018-06-01       Impact factor: 10.282

6.  Evaluation of aid to diagnosis of pigmented skin lesions in general practice: controlled trial randomised by practice.

Authors:  Dallas R English; Robert C Burton; Chris B del Mar; Robert J Donovan; Paul D Ireland; Geoff Emery
Journal:  BMJ       Date:  2003-08-16

7.  A basis function feature-based approach for skin lesion discrimination in dermatology dermoscopy images.

Authors:  R Joe Stanley; William V Stoecker; Randy H Moss; Harold S Rabinovitz; Armand B Cognetta; Giuseppe Argenziano; H Peter Soyer
Journal:  Skin Res Technol       Date:  2008-11       Impact factor: 2.365

8.  UV biomarker genes for classification and risk stratification of cutaneous actinic keratoses and squamous cell carcinoma subtypes.

Authors:  Dawn Queen; Yao Shen; Megan H Trager; Adriana T Lopez; Faramarz H Samie; Jesse M Lewin; George W Niedt; Larisa J Geskin; Liang Liu
Journal:  FASEB J       Date:  2020-08-10       Impact factor: 5.191

9.  [Pre-malignant and malignant lesions in minor surgery at a health centre. Appearances can't be trusted].

Authors:  C González Anguren; R Osés Primo; R Molinero Pinilla; A Parra Osés; S de la Red Arroyo
Journal:  Aten Primaria       Date:  2003-12       Impact factor: 1.137

10.  A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images.

Authors:  R Joe Stanley; Randy Hays Moss; William Van Stoecker; Chetna Aggarwal
Journal:  Comput Med Imaging Graph       Date:  2003 Sep-Oct       Impact factor: 4.790

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