Avoid common mistakes on your manuscript.
Sentinel lymph node biopsy (SLNB) is a prognostic surgical procedure used to identify patients at highest risk of dying from melanoma, as part of the 8th edition of the American Joint Committee on Cancer (AJCC) staging criteria (AJCCv8). Patients with ≥5% risk of having a positive SLN are considered for (T1a with high-risk features/T1b) or offered (T2–T4) SLNB.1 However, using the T category from AJCCv8 (based exclusively on lesion Breslow thickness and ulceration status) to determine SLN eligibility has its limitations, as evidenced by the many algorithms and nomograms developed to incorporate additional clinicopathologic factors into the decision of whether to perform or avoid SLNB. Importantly, many of these nomograms have been shown to provide no benefit over SLNB for all patients, or have wide confidence intervals, reducing confidence in the prediction.2,3,4,5
Tripathi and colleagues describe another clinicopathologic-based tool for SLN metastasis prediction, i.e., ELMO (evaluating lymphatic metastasis outcomes).6 ELMO was developed and internally validated using data from the Surveillance, Epidemiology, and End Results (SEER) program and the National Cancer Database (NCDB).6 We concur with the authors that tools that can appropriately inform SLNB decision making are clinically useful.7 However, a limitation of the SEER database pre-2018 is that nodal status does not describe ‘SLN status’, but rather any ‘nodal status’, no matter how it was determined (e.g., palpation, fine-needle aspiration, or SLNB).
Underscoring this concern, the data used to develop ELMO do not appear consistent with published literature on stage-specific SLNB rates and suggest that 50% of patients with a known SLNB status enrolled in the SEER registry had a T1a tumor (Table 1), potentially resulting in a poorly calibrated model. To test the ability of ELMO to accurately predict SLN risk, we used ELMO (accessed using the online tool) to perform an analysis of T1b–T2a tumors with a known positive SLNB result, from a previously published dataset.8 Of the 41 SLN-positive patients analyzed, ELMO considered 24% (10/41) as having <5% risk, nearly five times higher than the accepted 5% false-negative rate.1
Finally, the authors state that “this personalized probability [of ELMO] is not available from any current commercial tests”. However, one such test that combines gene expression profiling (31-GEP) with clinical and pathological factors has demonstrated accuracy and precision for predicting SLN positivity, with 95% sensitivity and 98% negative predictive value,8,9 and the i31-GEP for SLNB was shown to provide net benefit in T1–T2 tumors over SLNB for all participants.5,10
There are clear limitations to the current staging system for determining the risk of SLN positivity, as reflected by the number of studies aiming to develop a better method for risk assessment. Why has the melanoma field failed to adopt a single clinicopathologic nomogram for SLNB metastasis risk? When will the field realize the shortcomings of algorithms that use only clinicopathologic factors? While we continue to evaluate the range of nomograms put forward for academic interest,4,5 tools incorporating GEP technology with clinicopathologic factors are supported by strong evidence and are clinically available to inform risk-aligned management for SLNB decision making.
References
NCCN Clinical Practice Guidelines in Oncology: Melanoma: Cutaneous Version 1.2023. Available at: https://www.nccn.org/professionals/physician_gls/pdf/cutaneous_melanoma.pdf.
Wong SL, Kattan MW, McMasters KM, Coit DG. 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;12:282–8.
Lo SN, et al. Improved risk prediction calculator for sentinel node positivity in patients with melanoma: the melanoma institute australia nomogram. J Clin Oncol. 2020;38(24):2719–27. https://doi.org/10.1200/JCO.19.02362.
Hosein S, et al. Are the MIA and MSKCC nomograms useful in selecting patients with melanoma for sentinel lymph node biopsy? J Surg Oncol. 2023;127(7):1167–73. https://doi.org/10.1002/jso.27231.
Zakria D, Brownstone N, Rigel D. The integrated 31-gene expression profile (i31-GEP) test for cutaneous melanoma outperforms a clinicopathologic-only nomogram at identifying patients who can forego sentinel lymph node biopsy. SKIN J Cutan Med. 2022;6:463–73.
Tripathi R, et al. A clinical decision tool to calculate pretest probability of sentinel lymph node metastasis in primary cutaneous melanoma. Ann Surg Oncol. 2023;30(7):4321–8. https://doi.org/10.1245/s10434-023-13220-0.
Yamamoto M, 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. Cur Med Res Opin. 2023;39:417–23.
Whitman ED, et al. Integrating 31-gene expression profiling with clinicopathologic features to optimize cutaneous melanoma sentinel lymph node metastasis prediction. JCO Precis Oncol. 2021;5:1466–79. https://doi.org/10.1200/PO.21.00162.
Vetto JT, 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.
Marchetti MA, Dusza SW, Bartlett EK. Utility of a model for predicting the risk of sentinel lymph node metastasis in patients with cutaneous melanoma. JAMA Dermatol. 2022;158(6):680–3. https://doi.org/10.1001/jamadermatol.2022.0970.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Disclosures
Peter A. Prieto is a speaker for Castle Biosciences. Matthew S. Goldberg is an employee and stock holder of Castle Biosciences, Inc. Brian Martin is an employee and stock and options holder at Castle Biosciences, Inc.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Prieto, P.A., Goldberg, M.S. & Martin, B. RE: A Clinical Decision Tool to Calculate Pretest Probability of Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma. Ann Surg Oncol 30, 6357–6358 (2023). https://doi.org/10.1245/s10434-023-13812-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1245/s10434-023-13812-w