Scientific Publications

Publications Related to DecisionDx®-Melanoma

DecisionDx-Melanoma Clinical Validity to Identify Patients at Low Risk for SLN Positivity

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.

Cook RW, Monzon FA, Caruso HG, et al. Identification of melanoma patients with low risk of sentinel lymph node positivity and favorable prognosis using a 31-gene expression profile (GEP) test. Poster at Society for Melanoma Research (SMR) Congress: Nov 20-23, 2019; Salt Lake City, Utah.

DecisionDx-Melanoma Clinical Validity and Performance Studies to Predict Risk of Recurrence


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.

Podlipnik S, Carrera C, Boada A, et al. Early outcome of a 31-gene expression profile test in 86 AJCC stage Ib-II melanoma patients. A prospective multicenter cohort study. J Eur Acad Dermatol Venereol 2019;33:857-62.

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.

Gastman BR, Zager JS, Messina JL, et al. Performance of a 31-gene expression profile test in cutaneous melanomas of the head and neck. Head Neck2019;41:871-9.

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.

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.

Leachman S, Covington KR, Cook RW, et al. Implications of a 31-gene expression profile test for cutaneous melanoma on AJCC-based risk assessment and adjuvant therapy trial design. Poster presented at 2018 Society for Melanoma Research International Congress.

Greenhaw BD, 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.

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.

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.

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.

DecisionDx-Melanoma Clinical Impact Studies


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.

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.

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.

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.

Svoboda RM, Glazer AM, Farberg AS, et al. Factors affecting dermatologists’ use of a 31-gene expression profiling test as an adjunct for predicting metastatic risk in cutaneous melanoma. J Drugs Dermatol 2018;17:544-7.

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.

Farberg AS, Glazer AM, White R, et al. Impact of a 31-gene expression profiling test for cutaneous melanoma on dermatologists’ clinical management decisions. J Drugs Dermatol 2017;16:611-6.

Ferris LK, Farberg AS, Middlebrook B, et al. Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile-based classification. J Am Acad Dermatol 2017;76;818-25.e3. doi: 10.1016/j.jaad.2016.11.051.

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.

Systematic Reviews & Guidelines

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.

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.

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

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 Med2019;3:291-306.

Dubin DP, Dinehart SM & Farberg AS. Level of evidence review for a gene expression profile test for cutaneous melanoma. Am J Clin Dermatol2019;20:763-70.

Winkelmann RR, Farberg AS, Glazer AM, et al. Integrating skin cancer-related technologies into clinical practice. Dermatol Clin 2017;35:565-76.

DecisionDx-Melanoma Analytic Validity

Cook RW, Middlebrook B, Wilkinson J, et al. Analytic validity of DecisionDx-Melanoma, a gene expression profile test for determining metastatic risk in melanoma patients. Diagn Pathol 2018;13:13. doi:10.1186/s13000-018-0690-3.

Recent DecisionDx-Melanoma Presentations and Posters

Cook RW, Monzon FA, Caruso HG, et al. Identification of melanoma patients with low risk of sentinel lymph node positivity and favorable prognosis using a 31-gene expression profile (GEP) test. Poster at Society for Melanoma Research (SMR) Congress: Nov 20-23, 2019; Salt Lake City, Utah.

Monzon FA, Caruso HG, Covington KR, et al. Identification of T1-T2 melanoma patients at low risk for a positive sentinel lymph node using the 31-gene expression profile test. Oral presentation at 8th International Congress on Cancer Metastasis (ICCM): October 25-27, 2019; San Francisco, California.

Thorpe R, Covington K, Caruso H, et al. Development and validation of a clinically useful nomogram incorporating molecular clinicopathologic factors to predict risk of recurrence in patients with cutaneous melanoma. Oral presentation at American Society for Dermatologic Surgery (ASDS) Annual Meeting, October 24-27, 2019; Chicago, Illinois.

Estrada S, Covington KR, Caruso HG, et al. Identification of T1 melanoma patients at low risk for a positive sentinel lymph node (SLN) using a 31-gene expression profile (31-GEP). Poster at American Society of Dermatopathology (ASDP) 56th Annual Meeting: October 17-20, 2019; San Diego, California.

Prado G, Teplitz RW, Covington KR, et al. The prognostic 31-gene expression profile (31-GEP) test improves risk prediction in cutaneous melanoma (CM) patients within current AJCC stages. Poster at 2019 Fall Clinical Dermatology Conference for PAs and NPs: May 31-June 2, 2019; Scottsdale, Arizona.

Melanoma Background

Poklepovic AS, Carvajal RD. Prognostic value of low tumor burden in patients with melanoma. Oncology 2018;32:e90-e96.

Park TS, Phan GQ, et al. Routine computer tomography imaging for the detection of recurrences in high-risk melanoma patients. Ann Surg Oncol2017;24:947-51.

Winkelmann RR, Farberg AS, Glazer AM, et al. Noninvasive technologies for the diagnosis of cutaneous melanoma. Dermatol Clin 2017;35:453-6.

Podlipnik S, Carrera C, Sanchez M, et al. Performance of diagnostic tests in an intensive follow-up protocol for patients with American Joint Committee on Cancer (AJCC) stage IIB, IIC, and III localized primary melanoma: A prospective cohort study. J Am Acad Dermatol 2016;75:516-24.

Livingstone E, Krajewski C, Eigentler TK, et al. Prospective evaluation of follow-up in melanoma patients in Germany – results of a multicenter and longitudinal study. Eur J Cancer 2015;51:653-67.

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