Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Breast Cancer Research and Treatment
Published in: Breast Cancer Research and Treatment 3/2013

01-02-2013 | Clinical Trial

Which nomogram is best for predicting non-sentinel lymph node metastasis in breast cancer patients? A meta-analysis

Authors: Liling Zhu, Liang Jin, Shunrong Li, Kai Chen, Weijuan Jia, Quanyuan Shan, Stephen Walter, Erwei Song, Fengxi Su

Published in: Breast Cancer Research and Treatment | Issue 3/2013

Login to get access

Abstract

To present a systemic review and meta-analysis to evaluate the nomograms developed to predict non-sentinel lymph node (NSLN) metastasis in breast cancer patients. We focused on the six nomograms (Cambridge, MSKCC, Mayo, MDA, Tenon, and Stanford) that are the most widely validated. The AUCs were converted to odds ratios for the meta-analysis. In total, the Cambridge, Mayo, MDA, MSKCC, Stanford, and Tenon models were validated in 2,156, 2,431, 843, 8,143, 3,700, and 3,648 patients, respectively. The pooled AUCs for the Cambridge, MDA, MSKCC, Mayo, Tenon, and Stanford models were 0.721, 0.706, 0.715, 0.728, 0.720, and 0.688, respectively. Subgroup analysis revealed that in populations with a higher micrometastasis rate in the SLNs, the Tenon and Stanford models had a significantly higher predictive accuracy. A meta-regression analysis revealed that the SLN micrometastasis rate, but not the NSLN-positivity rate, was associated with improved predictive accuracy in the Tenon and Stanford models. The performance of the MSKCC and Cambridge models was not influenced by these two factors. All of these prediction models perform better than random chance. The Stanford model seems to be relatively inferior to the other models. The accuracy of the Tenon and Stanford models is influenced by the tumor burden in the SLNs.
Appendix
Available only for authorised users
Literature
1.
Krag DN et al (2010) Sentinel-lymph-node resection compared with conventional axillary-lymph-node dissection in clinically node-negative patients with breast cancer: overall survival findings from the NSABP B-32 randomised phase 3 trial. Lancet Oncol 11(10):927–933PubMedCrossRef
2.
Giuliano AE et al (2011) Axillary dissection vs no axillary dissection in women with invasive breast cancer and sentinel node metastasis: a randomized clinical trial. J Am Med Assoc 305(6):569–575CrossRef
3.
Chen K et al (2012) Validation and comparison of models to predict non-sentinel lymph node metastasis in breast cancer patients. Cancer Sci 103(2):274–281PubMedCrossRef
4.
Pal A et al (2008) A model for predicting non-sentinel lymph node metastatic disease when the sentinel lymph node is positive. Br J Surg 95(3):302–309PubMedCrossRef
5.
Chagpar AB et al (2006) Prediction of sentinel lymph node-only disease in women with invasive breast cancer. Am J Surg 192(6):882–887PubMedCrossRef
6.
Zee KJ et al (2003) A nomogram for predicting the likelihood of additional nodal metastases in breast cancer patients with a positive sentinel node biopsy. Ann Surg Oncol 10(10):1140–1151PubMedCrossRef
7.
Saidi RF et al (2004) Nonsentinel lymph node status after positive sentinel lymph node biopsy in early breast cancer. Am Surg 70(2):101–105 discussion 105PubMed
8.
Degnim AC et al (2005) Nonsentinel node metastasis in breast cancer patients: assessment of an existing and a new predictive nomogram. Am J Surg 190(4):543–550PubMedCrossRef
9.
Cho J et al (2008) A scoring system to predict nonsentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: a comparison with other scoring systems. Ann Surg Oncol 15(8):2278–2286PubMedCrossRef
10.
Hwang RF et al (2003) Clinicopathologic factors predicting involvement of nonsentinel axillary nodes in women with breast cancer. Ann Surg Oncol 10(3):248–254PubMedCrossRef
11.
Kohrt HE et al (2008) New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients. BMC Cancer 8:66PubMedCrossRef
12.
Barranger E et al (2005) An axilla scoring system to predict non-sentinel lymph node status in breast cancer patients with sentinel lymph node involvement. Breast Cancer Res Treat 91(2):113–119PubMedCrossRef
13.
Perhavec A et al (2009) Ljubljana nomograms for predicting the likelihood of non-sentinel lymph node metastases in breast cancer patients with a positive sentinel lymph node. Breast Cancer Res Treat 119(2):357–366CrossRef
14.
Coufal O et al (2009) Predicting non-sentinel lymph node status after positive sentinel biopsy in breast cancer: what model performs the best in a czech population? Pathol Oncol Res 15(4):733–740PubMedCrossRef
15.
Walter SD, Sinuff T (2007) Studies reporting ROC curves of diagnostic and prediction data can be incorporated into meta-analyses using corresponding odds ratios. J Clin Epidemiol 60(5):530–534PubMedCrossRef
16.
Berrang TS et al (2012) Which prediction models best identify additional axillary disease after a positive sentinel node biopsy for breast cancer? Breast Cancer Res Treat 133:695–702PubMedCrossRef
17.
Cripe MH et al (2006) The likelihood of additional nodal disease following a positive sentinel lymph node biopsy in breast cancer patients: validation of a nomogram. Am J Surg 192(4):484–487PubMedCrossRef
18.
Dauphine CE et al (2007) Evaluation of three scoring systems predicting non sentinel node metastasis in breast cancer patients with a positive sentinel node biopsy. Ann Surg Oncol 14(3):1014–1019PubMedCrossRef
19.
Ponzone R et al (2007) Comparison of two models for the prediction of nonsentinel node metastases in breast cancer. Am J Surg 193(6):686–692PubMedCrossRef
20.
Zgajnar J et al (2007) Low performance of the MSKCC nomogram in preoperatively ultrasonically negative axillary lymph node in breast cancer patients. J Surg Oncol 96(7):547–553PubMedCrossRef
21.
Klar M et al (2008) The MSKCC nomogram for prediction the likelihood of non-sentinel node involvement in a German breast cancer population. Breast Cancer Res Treat 112(3):523–531PubMedCrossRef
22.
Poirier E et al (2008) Analysis of clinical applicability of the breast cancer nomogram for positive sentinel lymph node: the Canadian experience. Ann Surg Oncol 15(9):2562–2567PubMedCrossRef
23.
Coutant C et al (2009) Comparison of models to predict nonsentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: a prospective multicenter study. J Clin Oncol 27(17):2800–2808PubMedCrossRef
24.
Coutant C et al (2009) Validation of the Tenon breast cancer score for predicting non-sentinel lymph node status in breast cancer patients with sentinel lymph node metastasis: a prospective multicenter study. Breast Cancer Res Treat 113(3):537–543PubMedCrossRef
25.
Gur AS et al (2009) Predictive probability of four different breast cancer nomograms for nonsentinel axillary lymph node metastasis in positive sentinel node biopsy. J Am Coll Surg 208(2):229–235PubMedCrossRef
26.
Scow JS et al (2009) Assessment of the performance of the Stanford online calculator for the prediction of nonsentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients. Cancer 115(18):4064–4070PubMedCrossRef
27.
van la Parra RF et al (2009) Validation of a nomogram to predict the risk of nonsentinel lymph node metastases in breast cancer patients with a positive sentinel node biopsy: validation of the MSKCC breast nomogram. Ann Surg Oncol 16(5):1128–1135PubMedCrossRef
28.
D’Eredita G et al (2010) Sentinel lymph node micrometastasis and risk of non-sentinel lymph node metastasis: validation of two breast cancer nomograms. Clin Breast Cancer 10(6):445–451PubMedCrossRef
29.
Moghaddam Y et al (2010) Comparison of three mathematical models for predicting the risk of additional axillary nodal metastases after positive sentinel lymph node biopsy in early breast cancer. Br J Surg 97(11):1646–1652PubMedCrossRef
30.
Sanjuan A et al (2010) Predicting non-sentinel lymph node status in breast cancer patients with sentinel lymph node involvement: evaluation of two scoring systems. Breast J 16(2):134–140PubMedCrossRef
31.
van den Hoven I et al (2010) Value of Memorial Sloan–Kettering Cancer Center nomogram in clinical decision making for sentinel lymph node-positive breast cancer. Br J Surg 97(11):1653–1658PubMedCrossRef
32.
D’Eredita G et al (2011) Comparison of two models for predicting non-sentinel lymph node metastases in sentinel lymph node-positive breast cancer patients. Updates Surg 63(3):163–170PubMedCrossRef
33.
Hessman CJ et al (2011) Comparative validation of online nomograms for predicting nonsentinel lymph node status in sentinel lymph node-positive breast cancer. Arch Surg 146(9):1035–1040PubMedCrossRef
34.
Hidar S et al (2011) Validation of nomograms to predict the risk of non-sentinels lymph node metastases in North African Tunisian breast cancer patients with sentinel node involvement. Breast 20(1):26–30PubMedCrossRef
35.
Lombardi A et al (2011) Non-sentinel lymph node metastases in breast cancer patients with a positive sentinel lymph node: validation of five nomograms and development of a new predictive model. Tumori 97(6):749–755PubMed
36.
Orsoni M et al (2011) Axillary lymph node dissection in the case of sentinel lymph node micrometastatic invasion: evaluation of three predictive models. Eur J Obstet Gynecol Reprod Biol 158(2):334–337PubMedCrossRef
37.
Tan EY et al (2011) Predictors of nonsentinel nodal involvement to aid intraoperative decision making in breast cancer patients with positive sentinel lymph nodes. ISRN Oncol 2011:539503PubMed
38.
Andersson Y et al (2012) Prediction of non-sentinel lymph node status in breast cancer patients with sentinel lymph node metastases: evaluation of the tenon score. Breast Cancer (Auckl) 6:31–38
39.
Sasada T et al (2012) Memorial Sloan–Kettering Cancer Center Nomogram to predict the risk of non-sentinel lymph node metastasis in Japanese breast cancer patients. Surg Today 42(3):245–249PubMedCrossRef
40.
Mittendorf EA et al (2012) Incorporation of sentinel lymph node metastasis size into a nomogram predicting nonsentinel lymph node involvement in breast cancer patients with a positive sentinel lymph node. Ann Surg 255(1):109–115PubMedCrossRef
41.
Fisher B et al (2002) Twenty-five-year follow-up of a randomized trial comparing radical mastectomy, total mastectomy, and total mastectomy followed by irradiation. N Engl J Med 347(8):567–575PubMedCrossRef
42.
Galimberti V, Cole BF, Zurrida S, Update of International Breast Cancer Study Group Trial 23–01 et al (2011) To compare axillary dissection versus no axillary dissection in patients with clinically node negative breast cancer and micrometastases in the sentinel node. Cancer Res 71(24 Suppl):102sCrossRef
43.
Cody HS 3rd, Houssami N (2012) Axillary management in breast cancer: what’s new for 2012? Breast 21(3):411–415PubMedCrossRef
44.
Kim T, Giuliano AE, Lyman GH (2006) Lymphatic mapping and sentinel lymph node biopsy in early-stage breast carcinoma: a metaanalysis. Cancer 106(1):4–16PubMedCrossRef
45.
Guth U et al (2012) The post ACOSOG Z0011 era: does our new understanding of breast cancer really change clinical practice? Eur J Surg Oncol 38(8):645–650PubMedCrossRef
46.
Meretoja TJ et al (2012) International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer. J Natl Cancer Inst
47.
Lee HS et al (2012) Predicting nonsentinel lymph node metastasis using lymphoscintigraphy in patients with breast cancer. J Nucl Med 53(11):1693–1700PubMedCrossRef
48.
Glasgow PD, Satchidanand N, Kowdley GC (2012) The predictive value of micrometastasis in nonsentinel lymph nodes. Am Surg 78(6):669–674PubMed
49.
Ozbas S et al (2012) Predicting the likelihood of nonsentinel lymph node metastases in triple negative breast cancer patients with a positive sentinel lymph node: Turkish Federation of Breast Disease Associations protocol MF09-01. Clin Breast Cancer 12(1):63–67PubMedCrossRef
50.
Meretoja TJ et al (2012) A simple nomogram to evaluate the risk of nonsentinel node metastases in breast cancer patients with minimal sentinel node involvement. Ann Surg Oncol 19(2):567–576PubMedCrossRef
51.
Haffty BG et al (2011) Positive sentinel nodes without axillary dissection: implications for the radiation oncologist. J Clin Oncol 29(34):4479–4481PubMedCrossRef
52.
Shahar KH et al (2004) Factors predictive of having four or more positive axillary lymph nodes in patients with positive sentinel lymph nodes: implications for selection of radiation fields. Int J Radiat Oncol Biol Phys 59(4):1074–1079PubMedCrossRef
53.
Katz A et al (2008) Nomogram for the prediction of having four or more involved nodes for sentinel lymph node-positive breast cancer. J Clin Oncol 26(13):2093–2098PubMedCrossRef
54.
Kapur U et al (2007) Prediction of nonsentinel lymph node metastasis in sentinel node-positive breast carcinoma. Ann Diagn Pathol 11(1):10–12PubMedCrossRef
Metadata
Title
Which nomogram is best for predicting non-sentinel lymph node metastasis in breast cancer patients? A meta-analysis
Authors
Liling Zhu
Liang Jin
Shunrong Li
Kai Chen
Weijuan Jia
Quanyuan Shan
Stephen Walter
Erwei Song
Fengxi Su
Publication date
01-02-2013
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 3/2013
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-012-2360-6

Other articles of this Issue 3/2013

Breast Cancer Research and Treatment 3/2013 Go to the issue

Preclinical study

14-3-3ζ as a predictor of early time to recurrence and distant metastasis in hormone receptor-positive and -negative breast cancers

Epidemiology

Physical activity and risk of breast cancer: a meta-analysis of prospective studies

Epidemiology

Estrogen receptor and progesterone receptor expression in normal terminal duct lobular units surrounding invasive breast cancer

Epidemiology

Effects of menopausal hormone therapy on ductal carcinoma in situ of the breast

Epidemiology

Interpersonal influences and attitudes about adjuvant therapy treatment decisions among non-metastatic breast cancer patients: an examination of differences by age and race/ethnicity in the BQUAL study

Epidemiology

Postmenopausal plasma sex hormone levels and breast cancer risk over 20 years of follow-up
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits