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

Peter Bourne; Cliff Rosendahl; Jeff Keir; Alan Cameron

doi:10.5826/dpc.0202a12

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

Authors

Peter Bourne School of Medicine, University of Queensland, Brisbane, Australia
Cliff Rosendahl School of Medicine, University of Queensland, Brisbane, Australia
Jeff Keir Department of Dermatology, School of Medicine, Cardiff University, Wales & Northern Rivers Skin Cancer Clinic, Ballina, NSW, Australia
Alan Cameron School of Medicine, University of Queensland, Brisbane, Australia

Keywords:

melanoma, skin cancer, diagnostic algorithm, BLINCK, primary care

Abstract

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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