A Clinical Aid for Detecting Skin Cancer: The Triage Amalgamated Dermoscopic Algorithm (TADA)

Purpose: Family physicians (FPs) frequently evaluate skin lesions but may not have the necessary training to accurately and confidently identify lesions that require skin biopsy or specialist referral. We evaluated the diagnostic performance of a new, simplified dermoscopy algorithm for skin cancer detection. Methods: In this cross-sectional, observation study, attendees of a dermoscopy course evaluated 50 polarized dermoscopy images of skin lesions (27 malignant and 23 benign) using the Triage Amalgamated Dermoscopic Algorithm (TADA). The dermoscopic criteria of TADA include architectural disorder (ie, disorganized or asymmetric distribution of colors and/or structures), starburst pattern, blue-black or gray color, white structures, negative network, ulcer, and vessels. The study occurred after 1 day of basic dermoscopy training. Clinical information related to palpation (ie, firm, dimpling) was provided when relevant. Results: Of 200 course attendees, 120 (60%) participated in the study. Participants included 64 (53.3%) dermatologists and 41 (34.2%) primary care physicians, 19 (46.3%) of whom were FPs. Fifty-two (43%) individuals had no previous dermoscopy training. Overall, the sensitivity and specificity of TADA for malignant skin lesions was 94.8% and 72.3%, respectively. Previous dermoscopy training and years of dermoscopy experience were not associated with diagnostic sensitivity (P = .13 and P = .05, respectively) or specificity (P = .36 and P = .21, respectively). Specialty type was not associated with sensitivity (P = .37) but dermatologists had a higher specificity than nondermatologists (79% v. 72%, P = .008). Conclusions: After basic instruction, TADA may be a useful dermoscopy algorithm for FPs who examine skin lesions as it has a high sensitivity for detecting skin cancer.