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

T. Rogers, MFA; M. L. Marino, MD; S. W. Dusza, DrPH; S. Bajaj, MD; R. P. Usatine, MD; M. A. Marchetti, MD; A. A. Marghoob, MD

Disclosures

J Am Board Fam Med. 2016;29(6):694-701. 

In This Article

Abstract and Introduction

Abstract

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.

Introduction

It has been proposed that the worldwide epidemic of skin cancer[1,2] be addressed by all physicians involved in the ongoing primary care of patients.[3] The current shortage of US dermatologists[4,5] has heightened the need to involve other medical professionals in skin cancer management. Primary care physicians (PCPs), including family physicians (FPs), regularly see patients with skin concerns who are not being followed by or do not have access to dermatologists. Each of these patient encounters, regardless of its primary purpose, is an opportunity to detect skin cancer. In primary care settings, the clinical assessment of concerning lesions requires the ability to determine whether a biopsy or further evaluation by a specialist is warranted. However, PCPs often lack confidence in their abilities to recognize skin cancer.[6] The dearth of dermatologic education in medical school curricula and family medicine residencies[7,8] underscores the need for providing PCPs with better tools and training for the management of cutaneous lesions.[9]

Dermoscopy is a noninvasive diagnostic technique that has been shown to enhance the detection of skin cancer compared with naked-eye examination.[10–12] Although the use of dermoscopy has been gaining popularity among PCPs,[13] training is required for it to become a beneficial tool.[14–17] To facilitate the use of dermoscopy among nonexperts, several simplified dermoscopic algorithms have been validated.[18,19] However, these algorithms were designed to detect specific subsets of pigmented skin cancers, primarily pigmented melanoma. This restricts their overall utility given that many basal cell carcinomas, squamous cell carcinomas, and even melanomas are not pigmented. To our knowledge, there are no proven clinical tools available to PCPs for evaluating nonpigmented skin lesions.[20]

The triage amalgamated dermoscopic algorithm (TADA) (Figure 1) was designed for the identification of both pigmented and nonpigmented skin cancers. In our experience, it can be difficult and time consuming to teach beginners the multitude of dermoscopic structures specific to a given malignancy. This is in part due to the poor interobserver concordance for most of these structures.[21] However, the subjective interpretation of architectural disorder (ie, disorganized or asymmetric distribution of colors and/or structures) has been shown to have high interobserver agreement and discriminatory power for malignancy.[21,22] TADA harnesses these attributes by prompting users to assess a lesion for architectural disorder, which if present, would suggest the need for a biopsy or specialist referral. However, given that several subtypes of skin cancer, such as nodular, spitzoid, and amelanotic melanoma, can appear as organized and symmetric lesions, TADA includes 6 additional, previously validated, dermoscopic patterns and features (starburst, blue-black or gray color, polarizing white structures, negative network, ulcer, vessels) to help identify these skin cancers.[23–30] The presence of any 1 of the 6 additional criteria would also suggest the need for a biopsy or specialist referral.

Figure 1.

The Triage Amalgamated Dermoscopic Algorithm (TADA).

One major difference between TADA and the other simplified screening algorithms is that TADA requires that commonly encountered and diagnostically unequivocal benign lesions, namely, angioma, dermatofibroma, and seborrheic keratosis, be excluded from the algorithm. In other words, before assessing for the algorithm's malignant criteria, one should first determine whether a lesion is a classic example of 1 of these 3 benign neoplasms. Although in many instances, these lesions can have dermoscopic structures that overlap with malignant lesions,[31,32] they can, nonetheless, be differentiated based on their overall clinical and dermoscopic patterns. TADA thus asks observers to learn the salient dermoscopic patterns associated with these benign lesions, which, in our personal experience, are easy to teach and learn. In addition, the frequency with which these lesions are encountered in clinical practice allows one to rapidly gain experience in their identification.

The aim of this observational study was to determine the diagnostic accuracy of TADA for common malignant skin lesions (melanoma, basal cell carcinoma, squamous cell carcinoma) when used by individuals with 1 day of dermoscopy training versus those with more extensive training or experience.

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