J Clin Pathol 67:112-119 doi:10.1136/jclinpath-2013-201524
  • Original article

Predicting the likelihood of additional lymph node metastasis in sentinel lymph node positive breast cancer: validation of the Memorial Sloan-Kettering Cancer Centre (MSKCC) nomogram

  1. Puay Hoon Tan3
  1. 1Yong Loo Lin School of Medicine, National University of Singapore, Singapore
  2. 2Department of Surgical Oncology, National Cancer Centre Singapore, Singapore
  3. 3Department of Pathology, Singapore General Hospital, Singapore
  4. 4Department of Clinical Research, Singapore General Hospital, Singapore
  5. 5Department of General Surgery, Singapore General Hospital, Singapore
  1. Correspondence to Dr Puay Hoon Tan, Department of Pathology, Singapore General Hospital, Singapore 169608, Singapore; tan.puay.hoon{at}
  • Received 6 February 2013
  • Revised 8 July 2013
  • Accepted 31 July 2013
  • Published Online First 18 September 2013


Aim To identify important clinicopathological parameters that are most helpful in predicting additional non-sentinel lymph node (SLN) metastasis among patients with a positive SLN biopsy in the Singapore breast cancer population.

Methods A total of 1409 patients who underwent SLN biopsy were reviewed over a 5 year period from July 2004 to October 2009. A Singapore General Hospital (SGH) nomogram was developed from predictors in the Memorial Sloan-Kettering Cancer Centre (MSKCC) nomogram using 266 patients with primary invasive breast cancer and a positive SLN biopsy who subsequently had an axillary lymph node dissection. The SGH nomogram was calibrated using bootstrapped data, while the MSKCC nomogram was calibrated using SGH data. The performance of these two nomograms was compared with the calculation of the area under the receiver–operator characteristics curve and adequacy indices.

Results The MSKCC nomogram achieved an area under the curve (AUC) of 0.716 (range 0.653–0.779) in our study population, while the SGH nomogram, which used only three pathological parameters, lymphovascular invasion, number of positive and negative SLN biopsies, achieved an AUC of 0.750 (range 0.691–0.808). The SGH nomogram with a higher adequacy index (0.969) provided better estimates compared with the MSKCC nomogram (0.689).

Conclusions The use of the MSKCC nomogram was validated in our local patient population. The SGH nomogram showed promise to be equally, if not, more predictive as a model in our own population, while using only three pathological parameters.