Self-diagnosing melanoma and pigmented lesions: What works for novices?

We have a paper just out comparing different methods of allowing novices to diagnose pigmented lesions. Image training works as well as the hallowed ABCD method, and we wonder if it might work even better with a little more development. Perhaps.(open access via above link)

Image Training, Using Random Images of Melanoma, Performs as Well as the ABC(D) Criteria in Enabling Novices to Distinguish Between Melanoma and Mimics of Melanoma DOI: 10.2340/00015555-1733

Abstract:  Robust experimental evidence supporting many attempts to facilitate early melanoma diagnosis is lacking. In an experimental study using a browser interface we have examined diagnostic accuracy, sensitivity and specificity of novices in distinguishing between melanomas and mimics of melanoma. We show that rule-based ABC methods and image training, based on random images of melanoma, improve specificity to similar degrees, with-out effects on sensitivity, leading to small improvements in overall accuracy. There was a significant effect of age with older subjects performing better. Although both the ABC method and image training groups showed improved performance over the control group, overall performance was poor. For instance, for a task in which 1 in 4 test images was a melanoma, and 3 out of 4 benign, both interventions (ABC or image training) increased accuracy from the control value of 53% to around 61%. For reference, dermatology trainees performed at a much higher level of accuracy. Our study provides little support for the use of such methods in public education, but suggests ways in which performance might be improved.

 

Post by Jonathan Rees

Clinical academic and skin watcher at the University of Edinburgh

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