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Castle Biosciences Presents Data Reinforcing the Clinical Utility of Its DecisionDx® Dermatologic Portfolio
Presented at American Society for Dermatologic Surgery (ASDS) 2021 Annual Meeting FRIENDSWOOD, Texas--(BUSINESS WIRE)-- Castle Biosciences, Inc. (Nasdaq:
About this update from Castle Biosciences, Inc.
[{"type":"text","content":"\nPresented at American Society for Dermatologic Surgery (ASDS) 2021 Annual Meeting\n\n FRIENDSWOOD, Texas--(BUSINESS WIRE)--\nCastle Biosciences, Inc. (Nasdaq: CSTL), a company applying innovative diagnostics to inform disease management decisions and improve patient outcomes, today announced oral presentations on its DecisionDx® gene expression profile (GEP) tests for skin cancer at the American Society for Dermatologic Surgery (ASDS) 2021 Annual Meeting, held Nov. 19-21, 2021.\n\n“We are excited to share data further reinforcing the clinical utility of our GEP tests with leading experts and health care professionals,” said Derek Maetzold, president and chief executive officer of Castle Biosciences. “We believe our DecisionDx tests complement dermatology clinicians’ arsenal of tools and help ensure the best possible outcomes for their patients. The clinically actionable information that our tests provide can help clinicians make informed and personalized treatment decisions for each patient based on their unique biology.”\n\nDecisionDx®-Melanoma:\n\nDecisionDx-Melanoma is Castle’s risk-stratification GEP test that is designed to predict 5-year risk of metastasis, as well as metastasis to the sentinel lymph node (SLN), independent of traditional staging factors. The test’s Integrated Test Result (ITR) includes the traditional class designation of lowest risk (Class 1A), increased risk (Class 1B/2A) or highest risk (Class 2B), as well as a more precise risk prediction for both SLN positivity and risk of recurrence, distant metastasis and melanoma survival in patients with stage I, II or III melanoma through the i31- GEP algorithms (i31-SLNB and i31-Risk of Recurrence (ROR)). The i31-SLNB and i31-ROR are distinct, independently validated algorithms that integrate clinicopathologic features with the DecisionDx-Melanoma score.\n\nNicholas Taylor, M.D., Ph.D. presented data on DecisionDx-Melanoma through an oral presentation titled “Integrated clinicopathologic data and gene expression profile predict sentinel lymph node positivity and recurrence-free and distant metastasis-free survival in cutaneous melanoma.”\n\nStudy background and findings:\n\n\nThe study's objective was to understand how integrating gene expression profiling with clinical and pathologic features can improve personalized medicine.\n\n\nDecisionDx-Melanoma’s cont...