BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings

Background: Deciding whether a skin lesion requires biopsy to exclude skin cancer is often challenging for primary care clinicians in Australia. There are several published algorithms designed to assist with the diagnosis of skin cancer but apart from the clinical ABCD rule, these algorithms only e...

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Autores principales:	Peter Bourne, Cliff Rosendahl, Jeff Keir, Alan Cameron
Formato:	article
Lenguaje:	EN
Publicado:	Mattioli1885 2012
Materias:	melanoma skin cancer diagnostic algorithm BLINCK primary care Dermatology RL1-803
Acceso en línea:	https://doaj.org/article/81efa0e703f541ef900dc26b1fd16c37
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spelling	oai:doaj.org-article:81efa0e703f541ef900dc26b1fd16c372021-11-17T08:33:09ZBLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings10.5826/dpc.0202a122160-9381https://doaj.org/article/81efa0e703f541ef900dc26b1fd16c372012-04-01T00:00:00Zhttp://dpcj.org/index.php/dpc/article/view/1173https://doaj.org/toc/2160-9381 Background: Deciding whether a skin lesion requires biopsy to exclude skin cancer is often challenging for primary care clinicians in Australia. There are several published algorithms designed to assist with the diagnosis of skin cancer but apart from the clinical ABCD rule, these algorithms only evaluate the dermatoscopic features of a lesion. Objectives: The BLINCK algorithm explores the effect of combining clinical history and examination with fundamental dermatoscopic assessment in primary care skin cancer practice. Patients/Methods: Clinical and dermatoscopic images of 50 skin lesions were collected and shown to four primary care practitioners. The cases were assessed by each participant and lesions requiring biopsy were determined on separate occasions using the 3-Point Checklist, the Menzies method, clinical assessment alone and the BLINCK algorithm. Results: The BLINCK algorithm had the highest sensitivity and found more melanomas than any of the other methods. However, BLINCK required more biopsies than the other methods. When comparing diagnostic accuracy, there was no difference between BLINCK, Menzies method and clinical assessment but all were better than the 3-Point checklist. Conclusions: These results suggest that the BLINK algorithm may be a useful skin cancer screening tool for Australian primary care practice. Peter BourneCliff RosendahlJeff KeirAlan CameronMattioli1885articlemelanomaskin cancerdiagnostic algorithmBLINCKprimary careDermatologyRL1-803ENDermatology Practical & Conceptual (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	melanoma skin cancer diagnostic algorithm BLINCK primary care Dermatology RL1-803
spellingShingle	melanoma skin cancer diagnostic algorithm BLINCK primary care Dermatology RL1-803 Peter Bourne Cliff Rosendahl Jeff Keir Alan Cameron BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings
description	Background: Deciding whether a skin lesion requires biopsy to exclude skin cancer is often challenging for primary care clinicians in Australia. There are several published algorithms designed to assist with the diagnosis of skin cancer but apart from the clinical ABCD rule, these algorithms only evaluate the dermatoscopic features of a lesion. Objectives: The BLINCK algorithm explores the effect of combining clinical history and examination with fundamental dermatoscopic assessment in primary care skin cancer practice. Patients/Methods: Clinical and dermatoscopic images of 50 skin lesions were collected and shown to four primary care practitioners. The cases were assessed by each participant and lesions requiring biopsy were determined on separate occasions using the 3-Point Checklist, the Menzies method, clinical assessment alone and the BLINCK algorithm. Results: The BLINCK algorithm had the highest sensitivity and found more melanomas than any of the other methods. However, BLINCK required more biopsies than the other methods. When comparing diagnostic accuracy, there was no difference between BLINCK, Menzies method and clinical assessment but all were better than the 3-Point checklist. Conclusions: These results suggest that the BLINK algorithm may be a useful skin cancer screening tool for Australian primary care practice.
format	article
author	Peter Bourne Cliff Rosendahl Jeff Keir Alan Cameron
author_facet	Peter Bourne Cliff Rosendahl Jeff Keir Alan Cameron
author_sort	Peter Bourne
title	BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings
title_short	BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings
title_full	BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings
title_fullStr	BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings
title_full_unstemmed	BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings
title_sort	blinck—a diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings
publisher	Mattioli1885
publishDate	2012
url	https://doaj.org/article/81efa0e703f541ef900dc26b1fd16c37
work_keys_str_mv	AT peterbourne blinckadiagnosticalgorithmforskincancerdiagnosiscombiningclinicalfeatureswithdermatoscopyfindings AT cliffrosendahl blinckadiagnosticalgorithmforskincancerdiagnosiscombiningclinicalfeatureswithdermatoscopyfindings AT jeffkeir blinckadiagnosticalgorithmforskincancerdiagnosiscombiningclinicalfeatureswithdermatoscopyfindings AT alancameron blinckadiagnosticalgorithmforskincancerdiagnosiscombiningclinicalfeatureswithdermatoscopyfindings
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BLINCK—A diagnostic algorithm for skin cancer diagnosis combining clinical features with dermatoscopy findings

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