Annals of Surgical Oncology

, Volume 12, Issue 4, pp 282-288

First online:

A Nomogram That Predicts the Presence of Sentinel Node Metastasis in Melanoma With Better Discrimination Than the American Joint Committee on CancerStaging System

  • Sandra L. WongAffiliated withDepartment of Surgery, Memorial Sloan-Kettering Cancer Center
  • , Michael W. KattanAffiliated withDepartment of Biostatistics and Epidemiology, Cleveland Clinic Foundation
  • , Kelly M. McMastersAffiliated withDepartment of Surgery, Division of Surgical Oncology, University of Louisville School of Medicine
  • , Daniel G. CoitAffiliated withDepartment of Surgery, Memorial Sloan-Kettering Cancer Center Email author 

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The threshold and indications for sentinel lymph node (SLN) biopsy in patients with melanoma remain somewhat arbitrary. Many variables associated with SLN positivity have previously been identified, including a significant association between the American Joint Committee on Cancer (AJCC) staging system and SLN status. We developed a user-friendly nomogram that takes several characteristics into account simultaneously to more accurately predict the presence of SLN metastasis for an individual patient.


A total of 979 patients who underwent successful SLN biopsy for cutaneous melanoma at a single institution between February 1991 and November 2003 were included in the analysis. Predictors were used to develop a nomogram, based on logistic regression analysis, to predict the probability of SLN positivity. A large multi-institutional trial with 3108 patients was used to validate the predictive accuracy of the nomogram compared with the AJCC staging system.


The nomogram was developed and found to be accurate and discriminating. The concordance index of the nomogram, a measure of predictive ability, was .694 when evaluated with the validation dataset. In contrast, the concordance index of the AJCC staging system was lower (.663; P < .001).


Using commonly available clinicopathologic information, we developed a nomogram to accurately predict the probability of a positive SLN in patients with melanoma. This tool takes several characteristics into account simultaneously. This model should enable improved patient counseling and treatment selection.


Melanoma Sentinel node biopsy Nomogram Prognosis