On April 22, 2021 Castle Biosciences, Inc. (Nasdaq: CSTL), a skin cancer diagnostics company providing personalized genomic information to improve cancer treatment decisions, reported participation in the Dermatology Nurses’ Association 2021 Annual Convention (Press release, Castle Biosciences, APR 22, 2021, View Source [SID1234578373]). Castle presented posters highlighting each of the company’s three skin cancer gene expression profile (GEP) tests.
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Poster information is as follows:
DecisionDx-Melanoma:
The poster is entitled, "31-gene expression profiling improves risk stratification in patients with T1 cutaneous melanoma."
DecisionDx-Melanoma is Castle’s 31-gene expression profile test that uses an individual patient’s tumor biology to predict risk of cutaneous melanoma metastasis or recurrence, as well as sentinel lymph node (SLN) positivity, independent of traditional staging factors.
Study methods and findings:
Nearly 70% of melanomas are diagnosed with tumor thickness that is less than or equal to 1.0 mm (T1 tumors), and recurrence-free survival (RFS) is generally good among these patients. However, up to 15% of patients with T1 tumors may experience a recurrence. Moreover, due to the large number of patients with T1 tumors, 27-30% of melanoma-related deaths occur in patients originally diagnosed with a T1 tumor, suggesting better identification of T1 patients at high risk of recurrence or metastasis is needed.
DecisionDx-Melanoma is designed to classify a patient’s recurrence risk as low (Class 1: Class 1A lowest) or high (Class 2: Class 2B highest) and has been validated in multiple prospective and retrospective studies.
Univariate analysis of the study data shows DecisionDx-Melanoma to be a stronger predictor of RFS than SLN status.
Multivariable analysis shows DecisionDx-Melanoma to be a strong, independent predictor of RFS.
With Class 2B RFS status similar to SLN positive status, Class 2B patients warrant follow-up strategies similar to SLN positive patients.
DecisionDx-SCC:
The poster is entitled, "Clinical utility of the 40-gene expression profile (40-GEP) for improved patient management decisions and disease related outcomes when combined with current clinicopathological risk factors for cutaneous squamous cell carcinoma (cSCC): Case Series."
DecisionDx-SCC is Castle’s prognostic 40-gene expression profile test for patients diagnosed with high-risk cutaneous squamous cell carcinoma (SCC) designed to use a patient’s tumor biology to predict individual risk of metastasis for patients with SCC and one or more risk factors.
Study methods and findings:
Two SCC cases were presented that highlight DecisionDx-SCC’s utility in stratifying risk in SCC.
The cases were very similar at diagnosis, both presenting with a history of immunosuppression along with identical staging (T2a per Brigham and Women’s Hospital staging; T1 per American Joint Committee on Cancer staging), but had divergent outcomes:
Case 1 did not recur, despite incomplete resection.
Case 2 developed local recurrence and regional metastasis, and died from SCC, despite clear surgical margins, radiation and chemotherapy treatments.
Subsequent DecisionDx-SCC test results yielded risk level assignments that correlated with the two patients’ outcomes:
Case 1 had a retrospective low-risk (Class 1) DecisionDx-SCC result.
Case 2 had a highest-risk (Class 2B) DecisionDx-SCC result.
The authors concluded that incorporating DecisionDx-SCC as a prognostic factor with traditional clinicopathological risk factors can improve stratification of high-risk SCC patients with at least one risk factor, thereby informing risk-appropriate management strategies.
DecisionDx DiffDx-Melanoma:
The poster is entitled, "Development, validation, and clinical utility of the 35-gene expression profile test for use as an adjunctive melanoma diagnostic tool."
DecisionDx DiffDx-Melanoma is designed to aid dermatopathologists in characterizing difficult-to-diagnose melanocytic lesions.
Study methods and findings:
DecisionDx DiffDx-Melanoma was developed using artificial intelligence methods trained on 200 benign nevi and 216 melanomas to select a panel of 32 discriminant and 3 control genes.
The test’s ability to differentiate accurately between benign and malignant pigmented skin lesions was characterized.
The test provides a high technical success rate at 96.6% with a modest intermediate-risk zone of 3.6%.
The analytical validity data of the DecisionDx DiffDx-Melanoma test demonstrates high precision as an indication of technical success.
Dermatopathologists utilized the DecisionDx DiffDx-Melanoma result to refine their diagnoses and their diagnostic confidence increased by 51%.
Dermatologists utilized the DecisionDx DiffDx-Melanoma result, which in the majority of responses, led to altered treatment plans in agreement with the DecisionDx DiffDx-Melanoma result.
About DecisionDx-Melanoma
DecisionDx-Melanoma is a gene expression profile test that uses an individual patient’s tumor biology to predict individual risk of cutaneous melanoma metastasis or recurrence, as well as sentinel lymph node positivity, independent of traditional staging factors, and has been studied in more than 5,700 patient samples. Using tissue from the primary melanoma, the test measures the expression of 31 genes. The test has been validated in four archival risk of recurrence studies of 901 patients and six prospective risk of recurrence studies including more than 1,600 patients. To predict likelihood of sentinel lymph node positivity, the Company utilizes its proprietary algorithm, i31-GEP, to produce an integrated test result. i31-GEP is an artificial intelligence-based neural network algorithm (independently validated in a cohort of 1,674 prospective, consecutively tested patients with T1-T4 cutaneous melanoma) that integrates the DecisionDx-Melanoma test result with the patient’s traditional clinicopathologic features. Impact on patient management plans for one of every two patients tested has been demonstrated in four multicenter and single-center studies including more than 560 patients. The consistent performance and accuracy demonstrated in these studies provides confidence in disease management plans that incorporate DecisionDx-Melanoma test results. Through December 31, 2020, DecisionDx-Melanoma has been ordered more than 68,920 times for use in patients with cutaneous melanoma.
More information about the test and disease can be found at www.CastleTestInfo.com.
About DecisionDx DiffDx-Melanoma
DecisionDx DiffDx-Melanoma is designed to aid dermatopathologists in characterizing difficult-to-diagnose melanocytic lesions. Of the approximately 2 million suspicious pigmented lesions biopsied annually in the U.S., Castle estimates that approximately 300,000 of those cannot be confidently classified as either benign or malignant through traditional histopathology methods. DecisionDx DiffDx-Melanoma classifies these lesions as: benign (gene expression profile suggestive of benign neoplasm); intermediate-risk (gene expression profile cannot exclude malignancy); or malignant (gene expression profile suggestive of melanoma). Interpreted in the context of other clinical, laboratory and histopathologic information, DecisionDx DiffDx-Melanoma is designed to add diagnostic clarity and confidence for dermatopathologists while helping dermatologists deliver more informed patient management plans.
More information about the test and disease can be found at www.CastleTestInfo.com.
About DecisionDx-SCC
DecisionDx-SCC is a 40-gene expression profile test that uses an individual patient’s tumor biology to predict individual risk of cutaneous squamous cell carcinoma metastasis for patients with one or more risk factors. The test result, in which patients are stratified into a Class 1, 2A or 2B risk category, predicts individual metastatic risk to inform risk-appropriate management.
Peer-reviewed publications have demonstrated that DecisionDx-SCC is an independent predictor of metastatic risk and that integrating DecisionDx-SCC with current prognostic methods can add positive predictive value to clinician decisions regarding staging and management.
More information about the test and disease can be found at www.CastleTestInfo.com.