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: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Mattioli1885
2012
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/81efa0e703f541ef900dc26b1fd16c37 |
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| Sumario: | 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.
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