Pattern analysis, not simplified algorithms, is the most reliable method for teaching dermoscopy for melanoma diagnosis to residents in dermatology.
BACKGROUND: Simplified algorithms for dermoscopy in melanoma diagnosis were developed in order to facilitate the use of this technique by non-experts. However, little is known about their reliability compared with classic pattern analysis when taught to untrained observers. OBJECTIVES: To investigate the diagnostic performance of three different methods, i.e. classic pattern analysis and two of the most used algorithms (the ABCD rule of dermoscopy and the seven-point check-list) when used by newly trained residents in dermatology to diagnose melanocytic lesions. Methods Five residents in dermatology (University of Florence Medical School) were submitted to a teaching programme in dermoscopy based on both formal lessons and training and self-assessment using a newly developed, interactive CD-ROM on dermoscopy. The performance of the three diagnostic methods was analysed in a series of 200 clinically equivocal melanocytic lesions including 44 early melanomas (median thickness 0.30 mm; 25th-75th percentile 0.00-0.58 mm). RESULTS: Pattern analysis yielded the best mean diagnostic accuracy (68.7%), followed by the ABCD rule (56.1%) and the seven-point check-list (53.4%, P = 0.06). The best sensitivity was associated with the use of the seven-point check-list (91.9%), which, however, provided the worst specificity (35.2%) of the methods tested. The interobserver reproducibility, as shown by kappa statistics, was low for all the methods (range 0.27-0.33) and did not show any statistical difference among them. CONCLUSIONS: Pattern analysis, i.e. simultaneous assessment of the diagnostic value of all dermoscopy features shown by the lesion, proved to be the most reliable procedure for melanoma diagnosis to be taught to residents in dermatology.