Comparison of melanoma diagnostic algorithms

on the 31 October 2014

The increase in the incidence of melanoma calls for accurate methods of early diagnosis and the use of dermoscopy has been shown to increase the diagnostic accuracy of dermatologists

Pattern analysis is known to be the most sensitive method of diagnosing melanoma, but it is difficult to use.
Researchers in Turkey have compared the sensitivity, specificity and diagnostic accuracy of four dermoscopic diagnostic algorithms that use calculation to provide a total score: the ABCD rule of dermoscopy, the seven-point checklist, the three-point checklist and the CASH algorithm.

In this study, three experienced dermoscopists examined 115 dermoscopic images of melanocytic lesions retrospectively and diagnosed each lesion as benign or malignant using each of the four diagnostic algorithms. Their results were then compared with histopathological diagnosis.

The sensitivity, specificity and diagnostic accuracy of the algorithms were as follows:

ABCD rule 91.6%, 60.4% and 66.9% respectively
Seven-point checklist 87.5%, 65.9% and 70.4%
Three-point checklist 79.1%, 62.6% and 66%
CASH algorithm 91.6%, 64.8% and 70.4%

The study found the ABCD rule and the CASH algorithm to be the most sensitive at diagnosing melanoma.
Unlu E, Akay BN, Erdem C. Comparison of dermatoscopic diagnostic algorithms based on calculation: the ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist and the CASH algorithm in dermatoscopic evaluation of melanocytic lesions.

J Dermatol 2014; 41: 598-603