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. Issue 2 (18th September 2013)

• Record Type: Journal Article
• Authors: Chue, Koy Min; Yong, Wei Sean; Thike, Aye Aye; Ahmed, Syed Salahuddin; Li, Hui Hua; Wong, Chow Yin; Ho, Gay Hui; Madhukumar, Preetha; Tan, Benita Kiat Tee; Ong, Kong Wee; Tan, Puay Hoon
• Is Part Of: Journal of clinical pathology. Volume 67:Issue 2(2014)
• Page Start: 112
• Page End: 119
• Publication Date: 2013-09-18
• Subjects: Breast Cancer -- Lymph Nodes -- Breast Pathology; Pathology -- Periodicals; Pathology, Molecular -- Periodicals; 616.0705
• DOI: 10.1136/jclinpath-2013-201524
• Languages: English
• ISSNs: 0021-9746

Abstract

Abstract : 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.