Castle Biosciences Announces Publication of Fourth Study Demonstrating Significant Impact of DecisionDx-UM on Treatment Plan Recommendations for Patients with Uveal Melanoma

Castle Biosciences, Inc. (Nasdaq: CSTL), a skin cancer diagnostics company providing personalized genomic information to improve cancer treatment decisions, today announced the publication of a multicenter, prospective study demonstrating that DecisionDx®-UM test results significantly impacted treatment plan recommendations for patients with uveal melanoma (UM). The study was published in the peer-reviewed journal Melanoma Management.

DecisionDx-UM is Castle’s 15-gene expression profiling (GEP) test developed to identify patients at low risk (Class 1) or high risk (Class 2) of metastasis, based on the unique biology of their primary tumor, and is current standard of care for uveal melanoma patients. It is estimated that nearly 8 in 10 patients diagnosed with uveal melanoma in the U.S. receive the DecisionDx-UM test as part of their diagnostic workup.

The multicenter CLEAR II study (Clinical Application of DecisionDx-UM Gene Expression Assay Results II) was designed to prospectively evaluate patterns of physician referral and metastatic surveillance regimens for UM patients who were tested with DecisionDx-UM as part of their diagnostic work up, and to compare management plans between DecisionDx-UM low-risk (Class 1) and DecisionDx-UM high-risk (Class 2) patients.

“The results from the CLEAR II study demonstrate that the DecisionDx-UM test has a significant impact on treatment plan recommendations for patients with uveal melanoma,” said first author Amy C. Schefler, M.D., Associate Professor of Clinical Ophthalmology, Weill Cornell Medical College/Houston Methodist Hospital and the University of Texas Health Science Center at Houston, and Retina Consultants of Houston. “DecisionDx-UM stratifies patients, based on tumor biology, into high- and low-risk groups, and this study demonstrates that physicians developed appropriate, risk-aligned treatment plans based on this genomic information.”`

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Avery Williams2020