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Castle Biosciences Presents New Data on DecisionDx®-Melanoma and DecisionDx®-SCC at the 2021 American Academy of Dermatology (AAD) Summer Meeting
FRIENDSWOOD, Texas--(BUSINESS WIRE)-- Castle Biosciences, Inc. (Nasdaq: CSTL), a dermatologic diagnostics company providing personalized genomic information
About this update from Castle Biosciences, Inc.
[{"type":"text","content":" FRIENDSWOOD, Texas--(BUSINESS WIRE)--\nCastle Biosciences, Inc. (Nasdaq: CSTL), a dermatologic diagnostics company providing personalized genomic information to inform treatment decisions, today announced recent presentations on two of its skin cancer gene expression profile tests at the 2021 American Academy of Dermatology (AAD) Summer Meeting, held Aug. 5-8, 2021.\n\nDecisionDx®-Melanoma:\n\nDecisionDx-Melanoma is Castle’s gene expression profile test that uses an individual patient’s tumor biology to predict the risk of cutaneous melanoma metastasis or recurrence, as well as sentinel lymph node (SLN) positivity, independent of traditional staging factors.\n\n“Integrating 31-gene expression profiling with clinicopathologic features improves prognostication of recurrence and metastasis in patients with stage I-III cutaneous melanoma” was presented by Nicholas Taylor, M.D., Ph.D., Zitelli and Brodland, P.C., Pittsburgh and Central Dermatology Center, Chapel Hill, N.C. in the Frontiers in Research, Science and Technology (FiRST) session on Saturday, Aug. 7.\n\n“The study demonstrated that DecisionDx-Melanoma added significant prognostic value for a patient beyond traditional staging,” said Taylor. “The study further showed that the ability to integrate a patient’s unique tumor biology with their personal clinical and pathologic risk factors helped both patients and clinicians.”\n\nStudy methods and findings:\n\n\nDecisionDx-Melanoma’s 31-gene expression profile (31-GEP) has been validated to both identify patients at low risk of sentinel lymph node positivity and refine risk of recurrence prognosis.\n\n\nA new integrated algorithm (i31-GEP ROR (risk of recurrence) for outcomes prediction) was developed (n=1581) and validated (n=523) using Cox regression and 10x4-fold cross-validation on patients with stage I-III cutaneous melanoma from multiple centers.\n\n\nThe final integrated outcomes prediction algorithm combined DecisionDx-Melanoma’s continuous 31-GEP score and patient-specific clinicopathologic risk factors, including Breslow thickness, ulceration, mitotic rate, age, tumor location, sentinel lymph node (SLN) status and/or the presence of microsatellites.\n\n\nCompared to American Joint Committee on Cancer Eighth Edition (AJCC8) staging, the i31-GEP ROR algorithm for outcomes prediction significantly improved the classifica...