Factors Affecting Dermatologists’ Use of a 31-Gene Expression Profiling Test as an Adjunct for Predicting Metastatic Risk in Cutaneous Melanoma openaccess articles

May 2018 | Volume 17 | Issue 5 | Original Article | 544 | Copyright © 2018

Ryan M. Svoboda MD MS,a Alex M. Glazer MD,b Aaron S. Farberg MD,c and Darrell S. Rigel MD MSd

aNational Society for Cutaneous Medicine, New York, NY bUniversity of Arizona, Tucson, AZ cIcahn School of Medicine at Mount Sinai, New York, NY dNYU School of Medicine, New York, NY

Abstract

Importance: A 31-gene expression profile (31-GEP) test to predict metastatic risk in patients with cutaneous malignant melanoma has previously been validated and is available for clinical use. The impact of the availability of such a test on clinical decision-making has previously been studied. However, little is known about which factors play a role in clinicians’ decision to utilize the test. Objective: To determine factors affecting clinicians’ decisions to utilize the 31-GEP test for metastatic risk stratification in patients with cutaneous malignant melanoma. Design, Setting, and Participants: Dermatologists attending a national conference completed a series of questions based around four clinical vignettes using an audience response system. The vignettes and associated questions were designed to determine the impact of three factors—Breslow thickness, ulceration, and sentinel lymph node biopsy status—on the decision to order the 31-GEP test. Main Outcomes and Measures: The percentage of respondents who would order the 31-GEP test in the various clinical scenarios was quantified. Differences between groups were assessed using the chi-squared test. Results: A total of 181/187 individuals completed the survey (96.8% response rate). For tumors with a Breslow thickness ≥0.5 mm, a majority of respondents reported that they would recommend the 31-GEP test. Ulceration was associated with a statistically significant increase in the percentage of clinicians who would recommend the assay for all but the thickest (2.1 mm) tumors. A negative SLN was only associated with a statistically significant increase in the percentage of clinicians who would recommend the test for the thinnest (0.26 mm) tumors (22% to 34%, P=0.033). Conclusions and Relevance: Ulceration appears to be the most important factor impacting clinicians when deciding to order the 31-GEP test to assess risk for melanoma metastasis. J Drugs Dermatol. 2018;17(5):544-547.

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BACKGROUND

Cutaneous malignant melanoma (CMM) provides a significant challenge in terms of prognostication and post-diagnosis management. This is largely due to the inability of traditional staging systems to provide enough granularity to distinguish groups of patients with significantly different outcomes.1,2 The clinical features that form the cornerstone of traditional American Joint Committee on Cancer (AJCC) staging systems are not as accurate in stratifying patients based on prognosis as they are in other malignancies. This is demonstrated by the fact that approximately two-thirds of melanoma-related deaths occur in sentinel-lymph node negative patients who are initially diagnosed with Stage I and II disease.3 This apparent paradox may lead to a false sense of security on the part of the patient and the clinician, with lower-intensity follow-up plans for patients in remission—a detail underscored by the fact that the majority of recurrences are detected by patients themselves.3,4These concerns highlight the need for new methods to more accurately group melanoma patients into prognostic categories. As such, there has been increasing interest in the use of molecular diagnostics and other “personalized medicine” techniques to better classify melanoma patients in terms of metastatic risk.2,5,6One such technology is the 31-gene expression profile (31-GEP) test (DecisionDx-Melanoma, Castle Biosciences Inc., Friendswood, TX). This gene profiling system, which classifies patients as low-risk (Class 1) versus high-risk (Class 2) for metastasis based on differential gene expression, has previously been validated and has been shown to have additionally significantly improved predictive accuracy when combined with AJCC staging methods and guideline recommendations.6 Despite the availability of this tool, relatively little is known about how dermatologists use the test clinically, particularly in terms of what factors clinicians consider when deciding whether to order the test. The purpose of this 

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