Journal of Clinical and Aesthetic Dermatology • Hot Topics in Melanoma July 2025 • ORIGINAL RESEARCH

J. MICHAEL GUENTHER, MD; ANDREW WARD, MD; BRIAN J. MARTIN, PhD; MARK CRIPE, DO; TIMOTHY BEARD, MD; OLIVER WISCO, DO, FAAD, FACMS; ROHIT SHARMA, MD; STANLEY P. LEONG, MD; RICHARD ESSNER, MD; JOSEPH I. CLARK, MD; JOHN HAMNER, MD; BRENDA SICKLE-SANTANELLO, MD; and MAKI YAMAMOTO, MD 2025-07-04 17:52:56

A Prospective, Multicenter Analysis of Recurrence-free Survival After Sentinel Lymph Node Biopsy Decisions Influenced by the 31-GEP

Dr. Guenther is with St. Elizabeth Physicians General and Vascular Surgery in Edgewood, Kentucky. Dr. Ward is with the University of Tennessee Medical Center in Knoxville, Tennessee. Dr. Martin is with Castle Biosciences in Friendswood, Texas. Dr. Cripe is with OhioHealth Physician Group in Columbus, Ohio. Dr. Wisco is with Brown Dermatology in Providence, Rhode Island. Dr. Sharma is with Marshfield Clinic in Marshfield, Wisconsin. Dr. Leong is with the California Pacific Medical Center and Research Institute in San Francisco, California. Dr. Essner is with the Melanoma and Cutaneous Oncology Research Program at Saint John's Cancer Institute in Santa Monica, California. Dr. Clark is with the Loyola University Medical Center in Maywood, Illinois. Dr. Hamner is with the University of Colorado Denver in Colorado Springs, Colorado. Dr. Sickle-Santanello is with Surgical Oncology Associates of Columbus in Columbus, Ohio. Dr. Yamamoto is with the University of California-Irvine School of Medicine in Orange, California.

BACKGROUND: Although most patients with cutaneous melanoma (CM) will have a negative sentinel lymph node biopsy (SLNB), up to 20 to 30 percent of these patients will recur. The 31-gene expression profile (31-GEP) test has been prospectively validated to identify patients at low (Class 1A), intermediate (Class 1B/2A), and high (Class 2B) risk of SLN positivity and recurrence. METHODS: DECIDE is a prospective, multicenter study to assess the effect of 31-GEP testing on SLNB performance rates in patients with T1 to T2 tumors considering SLNB and to study long-term outcomes. Here, we assessed outcomes in patients with a Class 1A 31-GEP result (n=130). RESULTS: Of Class 1A patients, 63 had an SLNB, with a 3.2 percent SLN positivity rate (2/63). No Class 1A patients, regardless of SLN status, experienced a recurrence (2-year median follow-up). CONCLUSION: These results are consistent with previous studies that showed the 31-GEP can identify patients at low risk of SLN positivity and recurrence.

Sentinel lymph node biopsy (SLNB) for cutaneous melanoma (CM) is considered prognostic for the risk of melanoma recurrence and patient survival.¹ Guidelines for SLNB suggest avoiding the procedure if the risk of a positive node is less than five percent, considering SLNB if the risk is 5 to 10 percent, and offering SLNB if the risk is greater than 10 percent.² Traditionally, guidelines for SLNB recommendations are based on a patient’s predicted risk of SLN positivity using only clinicopathologic features, including Breslow thickness, ulceration, age, mitotic rate, anatomic location, and lymphovascular invasion.² However, relying upon these traditional clinicopathologic features results in up to 88 percent of SLNB returning a negative result,³ subjecting patients to increased healthcare costs and complication risks.⁴ Furthermore, many patients (up to 16.0%) with a negative SLNB will experience tumor recurrence or die from their disease, most within the first two years following diagnosis.¹, ⁵-⁷ Of particular importance, patients who have early recurrence of their disease, particularly within the first year, have shorter overall survival and survival after recurrence than those who develop later recurrence.¹⁸,⁹ Although tools using only clinical and pathologic factors have attempted to identify patients who may potentially forego SLNB,¹⁰,¹¹ none have been shown to add benefit over performing SLNB for all eligible patients,¹² been prospectively validated, or demonstrated that patients who forego SLNB based on the assessment tool are not harmed by recurrences. Additionally, because adjuvant therapy is now available for patients with stage IIB and IIC melanoma, a positive SLNB is not necessary to be eligible for adjuvant treatment. SLNB is associated with higher patient and healthcare-related costs and a non-negligible 11-percent complication rate.³,⁴ Thus, novel tools incorporating objective risk measures with clinical and pathological risk factors could help safely reduce unnecessary surgical procedures and associated healthcare costs and patient morbidity.

The 31-gene expression profile (31-GEP) test for CM is prospectively validated to identify patients at low (Class 1A), intermediate (Class 1B/2A), and high (Class 2B) risk of recurrence, metastasis, or death.¹³,¹⁴ Furthermore, the 31-GEP is retrospectively and prospectively validated to identify patients with less than five percent risk of SLN positivity when the 31-GEP result is included in a patient’s risk assessment with other factors when considering foregoing SLNB, and these low-risk patients had high recurrence-free survival (RFS), distant metastasis-free survival, and melanoma-specific survival rates.¹⁵-¹⁷ Moreover, two recent studies demonstrated that patients tested with the 31-GEP have higher survival rates than patients not tested with the 31-GEP,¹⁴ and that patients with 31-GEP testing have tumor recurrence detected earlier at a lower tumor burden with higher overall survival than patients without 31-GEP testing,¹⁸ indicating that using the 31-GEP as part of routine clinical care can improve patient outcomes.

The objective of the present study was to assess recurrence in patients who would have been recommended to forego SLNB based on low-risk (Class 1A) 31-GEP results. We assessed whether these patients experienced any recurrence, particularly early recurrences, regardless of whether an SLNB was performed or SLNB positivity.

The DECIDE (DecisionDx-Melanoma Impact on Sentinel Lymph Node Biopsy Decisions and Clinical Outcomes) study is a prospective, multicenter study of patients with predominantly T1 to T2 tumors being considered for an SLNB. The study assesses the performance of the 31-GEP test in these SLNB-eligible patients through evaluating long-term follow-up outcomes, and the effect of 31-GEP testing on SLNB performance.16 Briefly, patients diagnosed with invasive CM from May 2020 to May 2022 at 22 institutions (enrollment 89% by surgical oncologists, 8% by dermatologists, and 3% by medical oncologists)16 for whom SLNB was being considered and who had the 31-GEP test ordered for clinical reasons were included. The study was approved by the WCG Institutional Review Board (WCG-IRB), and approval was obtained from the institutional IRBs at the participating centers. At Visit 1, patients who met inclusion criteria were provided informed consent and enrolled in the study. After reviewing all clinical data, including the 31-GEP test results, the clinician proceeded with the decided treatment course. At protocol-designated time points, information related to 31-GEP test results, SLNB performance, and which clinical, pathological, molecular, and patient factors influenced the decision to perform an SLNB were recorded by designated site personnel into a secure, web-based electronic case report form (eCRF). Subsequent follow-up visits recorded recurrence outcomes through chart review or participant phone call at six-month intervals. Institutional review board approval was obtained at each participating institution prior to participant enrollment. Prior to the current analysis, 100-percent source data verification was completed to ensure data completeness and data management was completed for all participants to ensure data integrity. Missing ulceration status or mitotic rate information were considered absent or zero, respectively. Initial DECIDE study results confirmed the performance of the 31-GEP to identify low-risk patients (Class 1A) with less than five percent likelihood of a positive SLNB and increased SLNB positivity rates in patients with a Class 1B/2A and Class 2B test result.¹⁶

The original study by Yamamoto et al16 was powered to detect a significant reduction in SLNB performance compared with a group of patients who did not have the 31-GEP as part of their clinical decision-making surrounding SLNB, which met its primary endpoint. This subsequent report focuses on the early outcomes (RFS) of patients with T1a, T1b, T2a, or T2b tumors and a Class 1A 31-GEP result (n=131) who forego SLNB when integrating the 31-GEP into clinical decision-making to ensure patients considered low risk by the 31-GEP (Class 1A) are not harmed by avoiding an SLNB. Although the 31-GEP was recently integrated with clinicopathologic factors,¹⁷ the data included in the present study were obtained prior to the development of the integrated model; therefore, only the 31-GEP Class result is shown here. RFS for patients with a Class 1A 31-GEP result was estimated using Kaplan–Meier analysis.

Patient demographics are shown in Table 1. There were no differences between patients who had an SLNB and those who did not for age (p=0.492), ulceration status (p=0.558), transected base (p=0.416), or mitotic rate (p=0.361). However, patients who received SLNB had slightly thicker tumors than those who did not (0.9mm vs. 0.8mm, p<0.001). Follow-up data were available for 94 percent (130/138) of the patients with a Class 1A result, with a median follow-up time of 2.0 years (range 0.4–3.5 years). Of the patients with a Class 1A 31-GEP result, 63 (48.5%) had an SLNB, with a 3.2 percent (2/63) SLN positivity rate (1 T1b and 1 T2a), and 67 (51.5%) did not undergo SLNB. No patient (0% [0/130]) with a 31-GEP Class 1A result had a recurrence, regardless of SLN status (positive, negative, or not performed), at the time of the last follow-up (100% 3-year RFS). DISCUSSION Because some patients with a negative SLNB will still experience a recurrence or die from their disease,¹ it is essential that tools attempting to identify patients with low risk of SLN positivity be evaluated for accuracy to predict the risk of disease progression to ensure the patient is not harmed by foregoing SLNB. The 31-GEP is the only prospectively validated test to identify patients with CM at low risk of SLN positivity and low or high risk of tumor recurrence, metastasis, or death.¹³,¹⁶ Previous studies have determined that the 31-GEP can better identify which patients can safely forego SLNB than either T stage or other GEP tests.¹⁹ This current study is clinically significant as it is the first to demonstrate that using a GEP test for CM can help safely guide patients away from SLNB, as there were no early recurrences in the low-risk (Class 1A) patient population, regardless of SLN status or whether SLNB was performed. Importantly, these results were obtained when the 31-GEP was actively considered in combination with clinicopathological factors in the decision to avoid or perform an SLNB. Although not assessed in the current study, patients with a Class 1B/2A or Class 2B result have been shown to have greater than five percent risk of SLN positivity and increased risk of tumor recurrence compared to those with a Class 1A result.¹⁵ Therefore, although patients with a Class 1A result can consider avoiding SLNB and have reduced management intensity, patients with a non-Class 1A result should be considered for SLNB and increased management intensity.

Current guidelines suggest that patients with T1 tumors have a 5 to 10 percent population-estimated risk of SLN positivity (T1b and certain T1a with high-risk features) and may choose to consider SLNB.²⁰ Weitemeyer et al21 showed that the change from the American Joint Committee on Cancer (AJCC) 7th edition to the 8th edition resulted in more SLNBs performed in patients with T1b tumors, though with a lower positivity rate. Multiple other studies demonstrate that SLNBs performed in patients with T1a and T1b tumors have high node-negativity rates,²²-²⁴ with one study at primarily surgical centers showing that 66 percent of patients with a 5 to 10 percent risk of SLN positivity had an SLNB performed.¹⁷ SLNB can be costly, adding significant cost to the healthcare system, especially because most SLNBs (88%) are negative.³,⁴ A recent health economic impact study, which included using the 31-GEP to guide SLNB decisions, found that including the 31-GEP with AJCC staging, compared to staging alone, for SLNB management decisions resulted in a healthcare payer savings of over $500,000 per 1,000,000 plan members.²⁵ As demonstrated by Yamamoto et al, incorporating the 31-GEP into clinical decision-making regarding SLNB can significantly reduce the number of unnecessary SLNBs performed, thus reducing costs to the patient and healthcare system. Furthermore, the current study demonstrates that patients who forego SLNB based on the 31-GEP result do so safely, as no early recurrences were noted at the time of last follow-up. Although other biomarker tests are under investigation, they are indicated only for SLNB risk prediction²⁶ or risk of recurrence,²⁷ whereas the 31-GEP is indicated for both SLNB risk prediction and risk of recurrence stratification, as demonstrated in the current study. Furthermore, previous studies have determined that the 31-GEP can better identify which patients can safely forego SLNB than either NCCN guidelines, the CP-GEP, or other nomograms.¹²,¹⁹ Using the 31-GEP in this population has the potential to significantly reduce the number of unnecessary SLNBs performed, while not adversely affecting RFS rates when compared with the use of other GEP tests or prediction nomograms, which have no clinical utility data and have not shown a benefit in patients with T1b tumors.¹²,²⁶,²⁸ These and other data suggest that the 31-GEP provides valuable prognostic information in multiple steps of the patient’s clinical course. First, using the 31-GEP to guide SLNB decisions can reduce the number of SLNBs by at least 29 percent, with a low risk of recurrence.16 Second, in patients with a negative SLNB, the 31-GEP identifies patients at high risk of tumor recurrence (Class 2A and 2B) who should be followed more closely so that recurrence can be detected and treated earlier, as described previously (Figure 1).¹⁸,²⁹

Limitations. Limitations of the study include the relatively small number of patients and low number of patients who had an SLNB to assess; however, the multicenter prospective study design increases the generalizability of the results to a wider population. Additionally, follow- up time is limited to a median of two years; however, monitoring of patients is ongoing and prior studies have shown that the median time to recurrence in early-stage melanoma is less than two years,⁸,³⁰ consistent with previously reported prospective data of the 31-GEP indicating early-stage patients with a Class 1A result who experience recurrence are likely to experience it within two years.¹³ These data provide evidence that, in the current study, providers are using the 31-GEP to select the correct patients with a Class 1A result who can safely avoid SLNB, and no recurrences were detected at a median follow-up of two years.³¹,³² Understanding how the 31-GEP can reduce healthcare-related costs is of critical importance for patients and the healthcare system, and tools that can reduce costs should be studied.

The current study demonstrates that patients with a Class 1A result may safely forgo the SLNB procedure. No patients had a recurrence within the study period, regardless of SLN status, supporting the clinical value of the 31-GEP test in guiding patient care.

¹. Morton DL, Thompson JF, Cochran AJ et al. “Final Trial Report of Sentinel-Node Biopsy Versus Nodal Observation in Melanoma. N Engl J Med. 2014 Feb 13;370(7):599–609.

³. Chen J, Xu Y, Zhou Y, et al. Prognostic Role of Sentinel Lymph Node Biopsy for Patients With Cutaneous Melanoma: A Retrospective Study of Surveillance, Epidemiology, and End-Result Population-Based Data. Oncotarget. 2016 Jul 19;7(29):45671–45677.

⁴. Moody JA, Ali RF, Carbone AC, et al. Complications of Sentinel Lymph Node Biopsy for Melanoma – A Systematic Review of the Literature. Eur J Surg Oncol. 2017 Feb;43(2):270–277.

⁵. Thomas DC, Han G, Leong SP, et al. Recurrence of Melanoma After a Negative Sentinel Node Biopsy: Predictors and Impact of Recurrence Site on Survival. Ann Surg Oncol. 2019 Jul;26(7):2254–2262.

⁶. Jones EL, Jones TS, Pearlman NW, et al. Long-Term Follow-Up and Survival of Patients Following a Recurrence of Melanoma After a Negative Sentinel Lymph Node Biopsy Result. JAMA Surg. 2013 May;148(5):456–461.

⁷. Zogakis TG, Essner R, Wang HJ, et al. Natural History of Melanoma in 773 Patients With Tumor-Negative Sentinel Lymph Nodes. Ann Surg Oncol. 2007 May;14(5):1604–1611.

⁸. Liang C, Hu W, Li J, et al. Early Time to Recurrence Predicts Worse Survival in Patients With Localized or Regionally Advanced Cutaneous Melanoma. Dermatol Ther. 2021 Jul;34(4):e14981.

⁹. Dong XD, Tyler D, Johnson JL, et al. Analysis of Prognosis and Disease Progression After Local Recurrence of Melanoma. Cancer. 2000 Mar 1;88(5):1063-1071.

¹⁰. Lo SN, Ma J, Scolyer RA, et al. Improved Risk Prediction Calculator for Sentinel Node Positivity in Patients With Melanoma: The Melanoma Institute Australia Nomogram. J Clin Oncol. 2020 Aug 20;38(24):2719-2727.

¹¹. Wong SL, Kattan MW, McMasters KM, et al. A Nomogram That Predicts the Presence of Sentinel Node Metastasis in Melanoma With Better Discrimination Than the American Joint Committee on Cancer Staging System. Ann Surg Oncol. 2005 Apr;12(4):282-288.

¹². Hosein S, Drebin HM, Kurtansky NR, et al. “Are the MIA and MSKCC Nomograms Useful in Selecting Patients With Melanoma for Sentinel Lymph Node Biopsy? J Surg Oncol. 2023 Jun;127(7):1167–1173.

¹³. 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 Apr 6:5:PO.20.00119.

¹⁴. Bailey CN, Martin BJ, Petkov VI, et al. 31-Gene Expression Profile Testing in Cutaneous Melanoma and Survival Outcomes in a Population-Based Analysis: A SEER Collaboration. JCO Precis Oncol. 2023 Jun:7:e2300044.

¹⁵. 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 Apr;15(11):1207–1217.

¹⁶. 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. Curr Med Res Opin. 2023 Mar;39(3):417–423.

¹⁷. Whitman ED, Koshenkov VP, Gastman BR, et al. Integrating 31-Gene Expression Profiling With Clinicopathologic Features to Optimize Cutaneous Melanoma Sentinel Lymph Node Metastasis Prediction. CO Precis Oncol. 2021 Sep 13:5:PO.21.00162.

¹⁸. Dhillon S, Duarte-Bateman D, Fowler G, et al. Routine Imaging Guided by a 31-Gene Expression Profile Assay Results in Earlier Detection of Melanoma With Decreased Metastatic Tumor Burden Compared to Patients Without Surveillance Imaging Studies. Arch Dermatol Res. 2023 Oct;315(8):2295–2302.

¹⁹. Glazer A, Tassavor M, Portela D, Soleymani T.The integrated 31-gene expression profile test (i31-GEP) for cutaneous melanoma outperforms the CP-GEP at identifying patients who can forego sentinel lymph node biopsy when applying NCCN guidelines. SKIN J Cutan Med. 2022;6(6):474–481.

²¹. Weitemeyer MB, Helvind NM, Brinck AM, Hölmich LR, Chakera AH. More sentinel lymph node biopsies for thin melanomas after transition to AJCC 8th edition do not increase positivity rate: a Danish population-based study of 7148 patients. J Surg Oncol. 2022;125(3):498–508.

²². Friedman C, Lyon M, Torphy RJ, et al. A nomogram to predict node positivity in patients with thin melanomas helps inform shared patient decision making. J Surg Oncol. 2019;120:1276–1283.

²³. Conic RRZ, Ko J, Damiani G, et al. Predictors of sentinel lymph node positivity in thin melanoma using the National Cancer Database. J Am Acad Dermatol. 2019;80(2):441-447.

²⁴. Sinnamon AJ, Neuwirth MG, Yalamanchi P, et al. Association between patient age and lymph node positivity in thin melanoma. JAMA Dermatol. 2017;153(9):866–873.

²⁵. Zakria D, Burshtein J, Shah M, et al. The health economic impact of the 31-gene expression profile test for treatment and surveillance management plans in patients with cutaneous melanoma. EJC Skin Cancer. 2024;2:47.

²⁶. Stassen RC, Mulder EEAP, Mooyaart AL, et al. Clinical evaluation of the clinicopathologic and gene expression profile (CP-GEP) in patients with melanoma eligible for sentinel lymph node biopsy: a multicenter prospective Dutch study. Eur J Surg Oncol. 2023;49(12):107249.

²⁷. Amaral TMS, Hoffmann M-C, Sinnberg T, et al. Clinical validation of a prognostic 11-gene expression profiling score in prospectively collected FFPE tissue of patients with AJCC v8 stage II cutaneous melanoma. Eur J Cancer. 2020;125:38–45.

²⁸. Bartlett EK, Marchetti MA, Coit DG. Gene expression profile-based risk modeling to select patients with melanoma who can avoid sentinel lymph node biopsy: are we there yet? JCO Precis Oncol. 2020;4:988–989.

²⁹. Gastman BR, Gerami P, Kurley SJ, et al. Identification of patients at risk of 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(1):149–157.e4.

³⁰. Tas F, Erturk K.Relapse patterns in patients with local and regional cutaneous melanoma. Clin Transl Oncol. 2019;21(4):412-419.

³¹. Tas F, Erturk K.Recurrence behavior in early-stage cutaneous melanoma: pattern, timing, survival, and influencing factors. Melanoma Res. 2017;27(2):134–139.

³². Wan G, Nguyen N, Liu F, et al. Prediction of early-stage melanoma recurrence using clinical and histopathologic features. NPJ Precis Oncol. 2022;6(1):1–16.

*COPYRIGHT: © 2025 Castle Biosciences Inc. and the author(s). Cancer Medicine published by John Wiley & Sons Ltd. This article is an open-access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The article may have been modified to adhere to journal style.
FUNDING: Funding was provided by Castle Biosciences, Inc.
DISCLOSURES: Dr. Martin is an employee and stock/options holder at Castle Biosciences Inc. Drs. Guenther and Sharma are on the Speaker’s bureau for Castle Biosciences. The remaining authors report no conflicts of interest relevant to the contents of this article.
CORRESPONDENCE: Brian J. Martin, PhD; Email: bmartin@castlebiosciences.com