Literature DB >> 2142028

A study of the value of the seven-point checklist in distinguishing benign pigmented lesions from melanoma.

M Keefe1, D C Dick, R A Wakeel.   

Abstract

A seven-point scoring system has been adopted by the Cancer Research Campaign to help non-dermatologists recognize melanoma (MM). Its value is reviewed in the light of increasing referrals of pigmented lesions. One-hundred and ninety-five patients (M:F, 43:152; mean age = 43 years, s.d. = 19) were asked whether their lesions possessed the seven points before diagnosis. The dermatologist assessed the signs. Six patients were unable to comply and some had multiple lesions; thus, 216 lesions were fully assessed by patient and dermatologist, and six by the dermatologist alone. Histology was obtained where appropriate. There were eight MMs, 95 naevi, 80 seborrhoeic warts, three dysplastic naevi, and 36 other lesions. Seven of the eight MMs were diagnosed clinically; the other was biopsied because of suspicious features and was a nodular MM. Four lesions suspected to be MMs proved benign. The predictive value (PV) of a clinical diagnosis of MM was 64% and of non-MM was 99%. Using accepted cutpoints for the seven-point system (refer if score greater than or equal to 3) patients' scores gave a PV for MM of 7% and for non-MM of 99%. Two MMs scored less than three. Dermatologists' scores gave a PV for MM of 8% and for non-MM of 99%. One MM scored less than 3. Univariate analyses showed that enlargement (P less than 0.05), dermatologists' assessments of an irregular margin (P less than 0.001), size (P less than 0.05) and pigmentary irregularity (P less than 0.05), and patients' assessments of size (P less than 0.05) were statistically significant.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1990        PMID: 2142028     DOI: 10.1111/j.1365-2230.1990.tb02064.x

Source DB:  PubMed          Journal:  Clin Exp Dermatol        ISSN: 0307-6938            Impact factor:   3.470


  13 in total

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5.  Using the 7-point checklist as a diagnostic aid for pigmented skin lesions in general practice: a diagnostic validation study.

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

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Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

8.  Teledermatology for diagnosing skin cancer in adults.

Authors:  Naomi Chuchu; Jacqueline Dinnes; Yemisi Takwoingi; Rubeta N Matin; Susan E Bayliss; Clare Davenport; Jacqueline F Moreau; Oliver Bassett; Kathie Godfrey; Colette O'Sullivan; Fiona M Walter; Richard Motley; Jonathan J Deeks; Hywel C Williams
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9.  Visual inspection for diagnosing cutaneous melanoma in adults.

Authors:  Jacqueline Dinnes; Jonathan J Deeks; Matthew J Grainge; 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; Yemisi Takwoingi; Clare Davenport; Kathie Godfrey; Fiona M Walter; Hywel C Williams
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Review 10.  Computer aided diagnostic support system for skin cancer: a review of techniques and algorithms.

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