Advertisement

Annals of Surgical Oncology

, Volume 26, Issue 12, pp 3955–3961 | Cite as

Age and Lymphovascular Invasion Accurately Predict Sentinel Lymph Node Metastasis in T2 Melanoma Patients

  • Michael E. EggerEmail author
  • Megan Stevenson
  • Neal Bhutiani
  • Adrienne C. Jordan
  • Charles R. Scoggins
  • Prejesh Philips
  • Robert C. G. MartinII
  • Kelly M. McMasters
Melanoma

Abstract

Background

The risk of sentinel lymph node (SLN) metastasis in melanoma is related directly to tumor thickness and inversely to age. The authors hypothesized that for T2 (thickness 1.1–2.0 mm) melanoma, age, and other factors may be able to identify a cohort of patients with a low risk of SLN metastases.

Methods

The authors developed logistic regression models to predict positive SLNs in patients undergoing SLN biopsy for T2 melanoma using the National Cancer Database. Classification and regression-tree analysis were used to identify groups of patients with high and low risk for SLN metastases. The prediction model then was applied to a separate data set from a multicenter randomized clinical trial.

Results

The study identified 12,918 patients with T2 melanoma undergoing SLN biopsy with clinically node-negative melanoma. In the multivariable analysis, increasing thickness, younger age, lymphovascular invasion (LVI), mitotic rate of 1/mm2 or more, axial location, and Clark level of 4 or 5 were independent risk factors for SLN metastases. A cohort based on age (> 56 years) and no LVI was identified with a relatively low risk (7.8%; 95% confidence interval 7.2–8.4%) of SLN metastases. The independent data set of 1531 patients with T2 melanoma confirmed these findings. Among elderly patients (age > 75 years) with melanoma 1.2 mm or smaller and no LVI, the risk of a positive SLN was 4.9% (95% confidence interval 3.3–7.1%).

Conclusions

Younger age and LVI are powerful predictors of SLN metastases for patients with T2 melanoma. This prediction model can inform shared decision-making regarding whether to perform SLN biopsy for older patients with otherwise low-risk T2 melanoma.

Notes

Disclosure

Kelly M. McMasters serves on the Scientific Advisory Board for Elucida Oncology. The National Cancer Data Base (NCDB) is a joint project of the Commission on Cancer (CoC) of the American College of Surgeons and the American Cancer Society. The CoC’s NCDB and the hospitals participating in the CoC NCDB are the source of the de-identified data used in this study. They have not verified the statistical validity of the data analysis or the conclusions derived by the authors and are not responsible for these.

Supplementary material

10434_2019_7690_MOESM1_ESM.pdf (56 kb)
Fig. S1 Flow diagram showing how a classification and regression tree (CART) model is built. The tree is built by the parsing of variables, one by one, to reduce the variation of the outcome in each successive split. This is the process of building or growing the tree. Including an excessive number of variables can lead to overfitting of the data and excessive complexity. The model then is “pruned” according to a cost-complexity algorithm, eliminating unnecessary variables and splits that do not significantly add to the ability of the model to discriminate the outcomes. The variables are chosen based on their ability to parse the data into meaningful subgroups. The analyst chooses only which variables to consider in the model. All variables are investigated, and only the statistically significant ones are retained, based on the number of final leaves (groups) requested by the analyst. (PDF 55 kb)

References

  1. 1.
    Wong SL, Faries MB, Kennedy EB, et al. Sentinel lymph node biopsy and management of regional lymph nodes in melanoma: American Society of Clinical Oncology and Society of Surgical Oncology Clinical Practice Guideline Update. Ann Surg Oncol. 2018;25:356–77.CrossRefGoogle Scholar
  2. 2.
    Gajdos C, Griffith KA, Wong SL, et al. Is there a benefit to sentinel lymph node biopsy in patients with T4 melanoma? Cancer. 2009;115:5752–60.CrossRefGoogle Scholar
  3. 3.
    Scoggins CR, Bowen AL, Martin RC II, et al. Prognostic information from sentinel lymph node biopsy in patients with thick melanoma. Arch Surg. 2010;145:622–7.CrossRefGoogle Scholar
  4. 4.
    van der Ploeg AP, Haydu LE, Spillane AJ, et al. Outcome following sentinel node biopsy plus wide local excision versus wide local excision only for primary cutaneous melanoma: analysis of 5840 patients treated at a single institution. Ann Surg. 2014;260:149–57.CrossRefGoogle Scholar
  5. 5.
    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;370:599–609.CrossRefGoogle Scholar
  6. 6.
    Kachare SD, Brinkley J, Wong JH, Vohra NA, Zervos EE, Fitzgerald TL. The influence of sentinel lymph node biopsy on survival for intermediate-thickness melanoma. Ann Surg Oncol. 2014;21:3377–85.CrossRefGoogle Scholar
  7. 7.
    Leiter U, Stadler R, Mauch C, et al. Complete lymph node dissection versus no dissection in patients with sentinel lymph node biopsy positive melanoma (DeCOG-SLT): a multicentre, randomised, phase 3 trial. Lancet Oncol. 2016;17:757–67.CrossRefGoogle Scholar
  8. 8.
    Faries MB, Thompson JF, Cochran AJ, et al. Completion dissection or observation for sentinel-node metastasis in melanoma. N Engl J Med. 2017;376:2211–22.CrossRefGoogle Scholar
  9. 9.
    Sondak VK, Taylor JM, Sabel MS, et al. Mitotic rate and younger age are predictors of sentinel lymph node positivity: lessons learned from the generation of a probabilistic model. Ann Surg Oncol. 2004;11:247–58.CrossRefGoogle Scholar
  10. 10.
    McMasters KM, Wong SL, Edwards MJ, et al. Factors that predict the presence of sentinel lymph node metastasis in patients with melanoma. Surgery. 2001;130:151–6.CrossRefGoogle Scholar
  11. 11.
    Balch CM, Thompson JF, Gershenwald JE, et al. Age as a predictor of sentinel node metastasis among patients with localized melanoma: an inverse correlation of melanoma mortality and incidence of sentinel node metastasis among young and old patients. Ann Surg Oncol. 2014;21:1075–81.CrossRefGoogle Scholar
  12. 12.
    Amin MB, Edge SB, American Joint Committee on Cancer. AJCC Cancer Staging Manual. 8th ed. Springer, Switzerland, 2017.Google Scholar
  13. 13.
    McMasters KM, Noyes RD, Reintgen DS, et al. Lessons learned from the Sunbelt Melanoma Trial. J Surg Oncol. 2004;86:212–23.CrossRefGoogle Scholar
  14. 14.
    Breiman L, Friedman J, Stone CJ, Olshen RA. Classification and regression trees. Boca Raton, FL: Taylor & Francis; 1984Google Scholar
  15. 15.
    Sinnamon AJ, Neuwirth MG, Yalamanchi P, et al. Association between patient age and lymph node positivity in thin melanoma. JAMA Dermatol. 2017;153:866–73.CrossRefGoogle Scholar
  16. 16.
    Egger ME, Stevenson M, Bhutiani N, et al. Should sentinel lymph node biopsy be performed for all T1b melanomas in the new 8(th)-Edition American Joint Committee on Cancer Staging System? J Am Coll Surg. 2019;228:466–72.CrossRefGoogle Scholar
  17. 17.
    Conic RZ, 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;80:441–7CrossRefGoogle Scholar
  18. 18.
    National Comprehensive Cancer Network. Cutaneous Melanoma (Version 1.2019). https://www.nccn.org/professionals/physician_gls/pdf/cutaneous_melanoma.pdf. Retrieved 20 Nov 2018.
  19. 19.
    Bartlett EK, Peters MG, Blair A, et al. Identification of patients with intermediate-thickness melanoma at low risk for sentinel lymph node positivity. Ann Surg Oncol. 2016;23:250–6.CrossRefGoogle Scholar
  20. 20.
    Chang JM, Kosiorek HE, Dueck AC, et al. Stratifying SLN incidence in intermediate-thickness melanoma patients. Am J Surg. 2018;215:699–706.CrossRefGoogle Scholar
  21. 21.
    Paek SC, Griffith KA, Johnson TM, et al. The impact of factors beyond Breslow depth on predicting sentinel lymph node positivity in melanoma. Cancer. 2007;109:100–8.CrossRefGoogle Scholar
  22. 22.
    Mays MP, Martin RC, Burton A, et al. Should all patients with melanoma between 1- and 2-mm Breslow thickness undergo sentinel lymph node biopsy? Cancer. 2010;116:1535–44.CrossRefGoogle Scholar
  23. 23.
    Hanna AN, Sinnamon AJ, Roses RE, et al. Relationship between age and likelihood of lymph node metastases in patients with intermediate-thickness melanoma (1.01–4.00 mm): a National Cancer Database study. J Am Acad Dermatol. 2019;80:433–40.CrossRefGoogle Scholar

Copyright information

© Society of Surgical Oncology 2019

Authors and Affiliations

  • Michael E. Egger
    • 1
    Email author
  • Megan Stevenson
    • 1
  • Neal Bhutiani
    • 1
  • Adrienne C. Jordan
    • 2
  • Charles R. Scoggins
    • 1
  • Prejesh Philips
    • 1
  • Robert C. G. MartinII
    • 1
  • Kelly M. McMasters
    • 1
  1. 1.The Hiram C. Polk Jr, MD Department of SurgeryUniversity of Louisville School of MedicineLouisvilleUSA
  2. 2.Department of Pathology and Laboratory MedicineUniversity of Louisville School of MedicineLouisvilleUSA

Personalised recommendations