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Castle Biosciences Announces Publication of Clinical Validation and Utility Data for DecisionDx® DiffDx™-Melanoma for Suspicious Pigmented Lesions
Two Companion Articles Recently Published in SKIN: The Journal of Cutaneous Medicine FRIENDSWOOD, Texas--(BUSINESS WIRE)-- Castle Biosciences, Inc. (Nasdaq:
About this update from Castle Biosciences, Inc.
[{"type":"text","content":"\nTwo Companion Articles Recently Published in SKIN: The Journal of Cutaneous Medicine\n\n FRIENDSWOOD, Texas--(BUSINESS WIRE)--\nCastle Biosciences, Inc. (Nasdaq: CSTL), a skin cancer diagnostics company providing personalized genomic information to improve cancer treatment decisions, today announced the publication of two studies in SKIN: The Journal of Cutaneous Medicine, which demonstrated that DecisionDx® DiffDx™-Melanoma adds significant diagnostic clarity for physicians when characterizing difficult-to-diagnose melanocytic lesions and establishes clinical utility with the potential to improve patient care.\n\nThe development and validation study, authored by Dr. Sarah I. Estrada, et al., is titled, “Development and Validation of a Diagnostic 35-Gene Expression Profile Test for Ambiguous or Difficult-To-Diagnose Suspicious Pigmented Skin Lesions.” This study describes the development and clinical validation of the DecisionDx DiffDx-Melanoma test, which is designed to refine the diagnoses of suspicious pigmented lesions.\n\nThe clinical utility study, authored by Dr. Aaron S. Farberg, et al., is titled, “A 35-Gene Expression Profile Test for Use in Suspicious Pigmented Lesions Impacts Clinical Management Decisions of Dermatopathologists and Dermatologists.” This study documents the influence of DecisionDx DiffDx-Melanoma test results on subsequent clinical management decisions, potentially leading to decreased unnecessary procedures while correctly identifying at-risk patients.\n\nEstrada et al. Study Background and Results:\n\n\nThe purpose of this study was to develop and validate DecisionDx DiffDx-Melanoma, including the test’s ability to accurately differentiate between benign and malignant pigmented lesions.\n\n\nDiscovery started with the assessment of 76 genes with quantitative reverse transcription polymerase chain reaction (RT-PCR); artificial intelligence methods were then employed for diagnostic gene selection and algorithm development using 200 benign nevi and 216 melanomas for training. The final algorithm included 32 discriminant and 3 control genes. To reflect the complex biology of melanocytic neoplasia, the DecisionDx DiffDx-Melanoma test was developed to include an intermediate-risk zone.\n\n\nThe results of the study showed that the DecisionDx DiffDx-Melanoma test:\n\n\nHad a technical success rate of 97%...