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Triage amalgamated dermoscopic algorithm (TADA) for skin cancer screening
IMPORTANCE: Dermoscopic triage algorithms have been shown to improve beginners’ abilities for identifying pigmented skin lesions requiring biopsy. OBJECTIVE: To estimate the diagnostic accuracy of the Triage Amalgamated Dermoscopic Algorithm (TADA) for pigmented and nonpigmented skin cancers. Second...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Derm101.com
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5424662/ https://www.ncbi.nlm.nih.gov/pubmed/28515993 http://dx.doi.org/10.5826/dpc.0702a09 |
Sumario: | IMPORTANCE: Dermoscopic triage algorithms have been shown to improve beginners’ abilities for identifying pigmented skin lesions requiring biopsy. OBJECTIVE: To estimate the diagnostic accuracy of the Triage Amalgamated Dermoscopic Algorithm (TADA) for pigmented and nonpigmented skin cancers. Secondarily, to compare TADAs performance to those of existing triage algorithms for the identification of pigmented skin cancers. DESIGN: Cross-sectional, observational, reader study that took place at a beginner and intermediate level dermoscopy course. PARTICIPANTS: Two hundred medical professionals of various specialties attended the course and 120 voluntarily joined the study (60% participation rate). EXPOSURES: After receiving basic dermoscopy training, participants evaluated 50 polarized, dermoscopic images of pigmented (22 benign, 18 malignant) and nonpigmented (1 benign, 9 malignant) skin lesions using TADA. Pigmented lesions were also evaluated using the Three-Point Checklist and AC Rule. With TADA, participants first determined if a lesion was an unequivocal angioma, dermatofibroma, or seborrheic keratosis, which would exclude it from further evaluation. All other lesions were assessed for architectural disorder, starburst pattern, blue-black or gray color, shiny white structures, negative network, ulcer/erosion, or vessels. Any one feature indicated suspicion for malignancy. RESULTS: Most participants were dermatologists (n=64, 53.3%) or primary care physicians (n=41, 34.2%), and many lacked previous dermoscopy training (n=52, 43.3%). TADA’s sensitivity and specificity for all skin cancers was 94.6% (95% CI=93.4–95.7%) and 72.5% (95% CI=70.1–74.7%), respectively. For pigmented skin cancers, the sensitivity and specificity were 94.0% (95% CI=92.9–95.0%) and 75.5% (95% CI=73.8–77.2%). This compared to 71.9% (95%CI=69.8–73.9%) and 81.4% (95%CI=79.7–83.0%) for the Three-Point Checklist and 88.6% (95%CI=87.1–89.9%) and 78.7% (95%CI=76.9–80.3%) for the AC Rule. CONCLUSIONS: These results suggest that TADA compares favorably to existing triage algorithms and might be a useful triage tool with high sensitivity and specificity for pigmented and nonpigmented skin cancers. Further studies are needed to validate these preliminary observations. |
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