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Scientific evidence

An extensively-researched approach for risk stratification

DecisionDx-Melanoma is strongly evidenced in more than 50 peer-reviewed publications and has been studied in more than 10,000 patients. In these studies, DecisionDx-Melanoma consistently outperforms traditional staging alone in a variety of melanoma patient cohorts.

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DecisionDx-Melanoma featured studies

  • 1
    Meta-analysis

    Meta-analysis of 1,479 patients showed that DecisionDx-Melanoma consistently identified melanoma patients who were at an increased risk of metastasis, independent of traditional clinicopathologic factors, and can be used in conjunction with traditional staging to improve patient risk stratification.

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  • 2
    PERSONALIZED RISK OF RECURRENCE (i31-ROR VALIDATION)

    This study validated a proprietary algorithm integrating the DecisionDx-Melanoma 31-GEP class score with clinicopathologic factors to provide personalized risk of recurrence assessment. The study showed that patients with a low-risk i31-ROR result has significantly higher 5-year survival than patients with a high-risk i31-ROR result.

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  • 3
    LIKELIHOOD OF SENTINEL LYMPH NODE POSITIVITY (i31-SLNB VALIDATION)

    Validation of the neural network algorithm incorporating clinicopathologic factors with the 31-GEP class score for personalized SLNB positivity risk assessment.

    • Of all factors, the 31-GEP was the most predictive of a positive SLN
    • The i31-SLNB algorithm reclassified 63% of patients with T1 tumors, originally classified with a 5-10% likelihood of SLN positivity.
    • Increase from 8.5% to 27.7% in patients with T1-T4 tumors predicted to have <5% SLN positive likelihood, with 98% NPV
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Strongly evidenced

10,000+

patients studied

50+ 

peer-reviewed publications 

2 meta-analyses 

representing the largest body of data for cutaneous melanoma (CM) prognostic test

Trusted in practice

150,000+

DecisionDx-Melanoma has been ordered more than 150,000 times for patients diagnosed with cutaneous melanoma (through December  31, 2023)

13,000+

healthcare professionals have ordered the test for CM

99%

technical success rate in 53,000+ clinical samples

DecisionDx-Melanoma and NCI collaboration delivers real-world data

Castle Biosciences partners with the National Cancer Institute (NCI) in an ongoing collaboration to link DecisionDx-Melanoma testing data with data from the Surveillance, Epidemiology and End Results (SEER) Program’s registries on cutaneous melanoma cases. This helps us put our test results into perspective with current standards and to learn where it is most beneficial to patients.

Scientific collaborators sit around a desk discussing real world data

Scientific references

  1. Gastman BR, Gerami P, Kurley SJ, et al. Identification of patients at risk for metastasis using a prognostic 31-gene expression profile in subpopulations of melanoma patients with favorable outcomes by standard criteria. J Am Acad Dermatol 2019. 80:149-157. doi:10.1016/j.jaad.2018.07.028.
  2. Gerami P, Cook RW, Wilkinson J, et al. Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res 2015;21:175-83.
  3. Gerami P, Cook RW, Russell MC, et al. Gene expression profiling for molecular staging of cutaneous melanoma in patients with sentinel lymph node biopsy. J Am Acad Dermatol 2015;72:780-5.e3.
  4. Jarell A, Gastman BR, Dillon LD, Hsueh EC, Podlipnik S, Covington KR, Cook RW, Bailey CN, Quick AP, Martin BJ, Kurley SJ, Goldberg M, Puig S, Optimizing treatment approaches for patients with cutaneous melanoma by integrating clinical and pathologic features with the 31- gene expression profile test, Journal of the American Academy of Dermatology (2022), doi: https:// doi.org/10.1016/j.jaad.2022.06.1202.
  5. Marks E, Caruso HG, Kurley SJ, et al. Establishing an evidence-based decision point for clinical use of the 31-gene expression profile test in cutaneous melanoma. SKIN J Cutaneous Med 2019;3:239-49.
  6. Vetto JT, Hsueh EC, Gastman BR, et al. Guidance of sentinel lymph node biopsy decisions in patients with T1-T2 melanoma using gene expression profiling. Future Oncol 2019;15:1207-17.
  7. Zager JS, Gastman BR, Leachman S, et al. Performance of a prognostic 31-gene expression profile in an independent cohort of 523 cutaneous melanoma patients. BMC Cancer 2018;18:130.

  1. Arnot SP, Han G, Fortino J, et al. Utility of a 31-gene expression profile for predicting outcomes in patients with primary cutaneous melanoma referred for sentinel node biopsy. Am J Surg 2021;221:1195-9.
  2. Dillon LD, McPhee M, et al. Expanded evidence that the 31-gene expression profile test provides clinical utility for melanoma management in a multicenter study; 2022; https://doi.org/10.1080/03007995.2022.2033560
  3. Greenhaw BN, Zitelli JA, Brodland DG. Estimation of prognosis in invasive cutaneous melanoma: An independent study of the accuracy of a gene expression profile test. Dermatol Surg 2018;44:1494-1500. doi: 10.1097/DSS.0000000000001588.
  4. Hsueh EC, DeBloom JR, Lee J, et al. Interim analysis of survival in a prospective, multi-center registry cohort of cutaneous melanoma tested with a prognostic 31-gene expression profile test. J Hematol Oncol 2017;10(152):1-8.
  5. Hsueh EC, DeBloom JR, Lee JH, et al. Long-term outcomes in a multicenter, prospective cohort evaluating the prognostic 31-gene expression profile for cutaneous melanoma. JCO Precis Oncol 2021;5:589-601.
  6. Keller J, Schwartz TL, Lizalek JM, et al. Prospective validation of the prognostic 31-gene expression profiling test in primary cutaneous melanoma. Cancer Med 2019;8:2205-12.

  1. Zakria, D., Brownstone, N., Berman, B., Ceilley, R., Goldenberg, G., Lebwohl, M., Litchman, G., & Siegel, D. (2023). Incorporating Prognostic Gene Expression Profile Assays into the Management of Cutaneous Melanoma: An Expert Consensus Panel Report. SKIN The Journal of Cutaneous Medicine. 7(1), 556–569.
  2. Farberg AS, Marson JW, Glazer A. et al. Expert Consensus on the Use of Prognostic Gene Expression Profiling Tests for the Management of Cutaneous Melanoma: Consensus from the Skin Cancer Prevention Working Group. Dermatol Ther (Heidelb) 12, 807–823 (2022). 
  3. Berman B, Ceilley R, Cockerell C, et al. Appropriate use criteria for the integration of diagnostic and prognostic gene expression profile assays into the management of cutaneous malignant melanoma: an expert panel consensus-based modified Delphi process assessment. SKIN J Cutaneous Med 2019;3:291-306.
  4. Dubin DP, Dinehart SM & Farberg AS. Level of evidence review for a gene expression profile test for cutaneous melanoma. Am J Clin Dermatol 2019;20:763-70.
  5. Greenhaw BN, Covington KR, Kurley SJ, et al. Molecular risk prediction in cutaneous melanoma: a meta-analysis of the 31-gene expression profile prognostic test in 1,479 patients. J Am Acad Dermatol 2020. doi.org/10.1016/j.jaad.2020.03.053
  6. Kwatra SG, Hines H, Semenov YR, et al. A dermatologist's guide to implementation of gene expression profiling in the management of melanoma.  J Clin Aesthet Dermatol 2020;13(Suppl 1):s3-s14.
  7. Litchman GH, Prado G, Teplitz RW & Rigel DS.  A systematic review and meta-analysis of gene expression profiling for primary cutaneous melanoma prognosis.  SKIN J Cutaneous Med 2020;4:221-37. https://doi.org/10.25251/skin.4.3.3 

  1. Yamamoto M, Sickle-Santanello B, Beard T, et al. The 31-gene expression profile test informs sentinel lymph node biopsy decisions in patients with cutaneous melanoma: results of a prospective, multicenter study. Curr Med Res Opin. 2023;1-7. doi:10.1080/03007995.2023.2165813 
  2. Berger AC, Davidson RS, Poitras JK, et al. Clinical impact of a 31-gene expression profile test for cutaneous melanoma in 156 prospectively and consecutively tested patients. Curr Med Res Opin 2016;32:1599-1604. doi:10.1080/03007995.2016.1192997.
  3. Dillon LD, Gadzia JE, Davidson RS, et al. Prospective, multicenter clinical impact evaluation of a 31-gene expression profile test for management of melanoma patients. SKIN J Cutan Med 2018;2:111-21.
  4. Hyams DM, Covington KR, Johnson CE, et al. Integrating the melanoma 31-gene expression profile test to surgical oncology practice within national guideline and staging recommendations. Future Oncol 2020 doi.org/10.2217/fon-2020-0827.
  5. Mirsky R, Prado G, Svoboda R, et al. Management decisions made by physician assistants and nurse practitioners in cutaneous malignant melanoma patients: Impact of a 31-gene expression profile test. J Drugs Dermatol 2018;17:1220-3.
  6. Schuitevoerder D, Heath M, Cook RW, et al.  Impact of gene expression profiling on decision-making in clinically node negative melanoma patients after surgical staging. J Drugs Dermatol 2018;17:196-9.
  7. Scott AM, Dale PS, Conforti A, et al. Integration of a 31-gene expression profile into clinical decision-making in the treatment of cutaneous melanoma. Am Surgeon 2020. https://doi.org/10.1177/0003134820939944.

  1. Ahmed, K, Siegel, JJ, Morgan-Linnell, SK, LiPira, K. Attitudes of patients with cutaneous melanoma toward prognostic testing using the 31-gene expression profile test. Cancer Med. 2022; 00: 1- 8. doi: 10.1002/cam4.5047

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