Validation of the non-sentinel lymph node metastasis prediction models in Chinese breast cancer population and the construction of a new model

Jianwei LU; Peiqi WU

doi:10.3969/j.issn.1674-4500.2018.02.18

Volume 41 Issue 2

May 2018

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Article Navigation > Journal of Molecular Imaging > 2018 > 41(2): 212-218

Jianwei LU, Peiqi WU. Validation of the non-sentinel lymph node metastasis prediction models in Chinese breast cancer population and the construction of a new model[J]. Journal of Molecular Imaging, 2018, 41(2): 212-218. doi: 10.3969/j.issn.1674-4500.2018.02.18

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Jianwei LU, Peiqi WU. Validation of the non-sentinel lymph node metastasis prediction models in Chinese breast cancer population and the construction of a new model[J]. Journal of Molecular Imaging, 2018, 41(2): 212-218. doi: 10.3969/j.issn.1674-4500.2018.02.18

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Validation of the non-sentinel lymph node metastasis prediction models in Chinese breast cancer population and the construction of a new model

doi: 10.3969/j.issn.1674-4500.2018.02.18

Jianwei LU^1
,,
Peiqi WU^{2,3
,
,}

1.
Department of Radiology, Jiangmen Xinhui District Maternal and Child Health Hospital, Jiangmen 529100, China
2.
Department of Radiology, Shenzhen Yantian District Peoples’s Hospital, Shenzhen 518081, China
3.
Department of Radiology, Guangdong General Hospital, Guangzhou 510080, China

Received Date: 2018-01-29
Publish Date: 2018-04-01

Abstract

Abstract

Objective To assess the clinical values of 3 non-sentinel lymph node (SLN) metastasis prediction models, including MSKCC, Louisville and SCH, in Chinese population, and to construct a new model for predicting the risk of non-sentinel lymph node metastasis. Methods A total of 220 breast cancer patients who underwent SLN biopsy and axillary lymph node dissection (ALND) in our hospital were included in this study. After performing a univariate analysis and multivariate logistic regression analysis on the clinicopathological data of the patients, a new non-SLN metastasis risk prediction model was established based on the independent predictors we identified. MSKCC, Louisville, SCH and the newly established model were compared using the clinicopathological data of our patients, after which the receiver operating characteristic curve (ROC) was plotted and the area under the curve (AUC) and false negative rates (FNR) of each model was calculated to evaluate the discrimination capability and clinical value of above models. Results Of the 220 breast cancer patients included, 97 patients (44.1%) were found to have positive non-SLNs. Logistic regression analysis indicated that only the size of the primary tumor size, vessel cancerous emboli, number of positive SLN and proportion of positive SLN/total SLN were independent predictors of non-SLN metastasis, based on which a new prediction model was constructed. The AUC values of the MSKCC, Louisville, SCH and the new model were 0.683, 0.747, 0.657 and 0.762 respectively. When FNR was adjusted close to 10%, the percentage of patients who were classified into the low-risk group by MSKCC, Louisville, SCH and the new model were 17.27%, 20.00%, 15.00% and 33.18%. Conclusion The new model established in this study may be more clinically valuable in predicting the risk of non-SLN metastasis than MSKCC, Louisville and SCH, but before its application a larger sample is needed for model validation and adjustment. Doctors should be cautious when using non-SLN metastasis predicting models for decision making as whether patients with positive SLN biopsy should complete ALND.
- breast cancer,
- prediction models,
- sentinel lymph node,
- non-sentinel lymph node metastasis,
- nomogram

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[1]	Choi HY, Park M, Seo M, et al. Preoperative axillary lymph node evaluation in breast cancer current issues and literature review[J]. Ultrasound Q, 2017, 33(1): 6-14. doi: 10.1097/RUQ.0000000000000277
[2]	Krag DN, Weaver DL, Alex JC, et al. Surgical resection and radiolocalization of the sentinel lymph node in breast cancer using a gamma probe[J]. Surg Oncol, 1993, 2(6): 335-9. doi: 10.1016/0960-7404(93)90064-6
[3]	杨翼鹏, 嵇健, 刘民锋, 等. 腋窝治疗对于早期乳腺癌患者是否有必要[J]. 南方医科大学学报, 2014, 34(7): 1065-7.
[4]	Veronesi U, Paganelli G, Galimberti V, et al. Sentinel-node biopsy to avoid axillary dissection in breast cancer with clinically negative lymph-nodes[J]. Lancet, 1997, 349(969): 1864-7.
[5]	Chen SL, Iddings DM, Scheri RP, et al. Lymphatic mapping and sentinel node analysis: current concepts and applications[J]. CA Cancer J Clin, 2006, 56(5): 292-309. doi: 10.3322/canjclin.56.5.292
[6]	Poortmans PM, Struikmans H, Bartelink H. Regional nodal irradiation in Early-Stage breast cancer[J]. N Engl J Med, 2015, 373(19): 1879-80.
[7]	Speers C, Pierce LJ. Postoperative radiotherapy after Breast-Conserving surgery for Early-Stage breast cancer a review[J]. JAMA Oncol, 2016, 2(8): 1075-82. doi: 10.1001/jamaoncol.2015.5805
[8]	Garcia-Tejedor A, Falo C, Quetglas CA, et al. Feasibility, accuracy and prognosis of sentinel lymph node biopsy before neoadjuvant therapy in breast cancer. A prospective study[J]. Int J Surg, 2017, 39(11): 141-7. https://www.sciencedirect.com/science/article/pii/S1743919117301115
[9]	Manca G, Rubello D, Tardelli E, et al. Sentinel lymph node biopsy in breast cancer:indications,contraindications,and controversies[J]. Clin Nucl Med, 2016, 41(2): 126-33. doi: 10.1097/RLU.0000000000000985
[10]	Chen JY, Chen JJ, Yang BL, et al. Predicting sentinel lymph node metastasis in a Chinese breast cancer population: assessment of an existing nomogram and a new predictive nomogram[J]. Breast Cancer Res Treat, 2012, 135(3): 839-48. doi: 10.1007/s10549-012-2219-x
[11]	Chagpar AB, Scoggins CR, Martin IR, et al. Prediction of sentinel lymph node-only disease in women with invasive breast cancer[J]. Am J Surg, 2006, 192(6): 882-6. doi: 10.1016/j.amjsurg.2006.08.063
[12]	Qiu PF, Liu JJ, Wang YS, et al. Risk factors for sentinel lymph node metastasis and validation study of the MSKCC nomogram in breast cancer patients[J]. Jpn J Clin Oncol, 2012, 42(11): 1002-7. doi: 10.1093/jjco/hys150
[13]	Van Zee KJ, Manasseh DM, Bevilacqua JL, et al. A nomogram for predicting the likelihood of additional nodal metastases in breast cancer patients with a positive sentinel node biopsy[J]. Ann Surg Oncol, 2003, 10(10): 1140-51. doi: 10.1245/ASO.2003.03.015
[14]	Weaver DL, Ashikaga T, Krag DN, et al. Effect of occult metastases on survival in node-negative breast cancer[J]. N Engl J Med, 2011, 364(5): 412-21. doi: 10.1056/NEJMoa1008108
[15]	Barranger E, Coutant C, Flahault A, et al. An axilla scoring system to predict non-sentinel lymph node status in breast cancer patients with sentinel lymph node involvement[J]. Breast Cancer Res Treat, 2005, 91(2): 113-9. doi: 10.1007/s10549-004-5781-z
[16]	吴佩琪, 刘春玲, 刘再毅, 等. 钼靶、CT与DCE-MRI评价乳腺癌淋巴结转移的价值[J]. 南方医科大学学报, 2016, 36(4): 493-9.
[17]	Singletary SE, Greene FL, Sobin LH. Classification of isolated tumor cells:clarification of the 6th edition of the American Joint Committee on cancer staging manual[J]. Cancer, 2003, 98(12): 2740-1. doi: 10.1002/(ISSN)1097-0142
[18]	Kim WG, Lee JS. Axillary skip metastases and the False-Negative rate of sentinel lymph node biopsy in patients with breast cancer are related to negative ALDH-1 expression and Ki-67 expression[J]. Int J Surg Pathol, 2017, 25(5): 397-405. doi: 10.1177/1066896917690024
[19]	Kohrt HE, Olshen RA, Bermas HR, et al. New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients[J]. BMC Cancer, 2008, 8(12): 66-75. doi: 10.1186/1471-2407-8-66
[20]	Cho J, Han W, Lee JW, et al. A scoring system to predict nonsentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: A comparison with other scoring systems[J]. Ann Surg Oncol, 2008, 15(8): 2278-86. doi: 10.1245/s10434-008-9993-z
[21]	Perhavec A, Perme MP, Hocevar M, et al. Ljubljana nomograms for predicting the likelihood of non-sentinel lymph node metastases in breast cancer patients with a positive sentinel lymph node[J]. Breast Cancer Res Treat, 2010, 119(2): 357-66. doi: 10.1007/s10549-009-0561-4
[22]	Gur AS, Unal B, Ozbek U, et al. Validation of breast cancer nomograms for predicting the non-sentinel lymph node metastases after a positive sentinel lymph node biopsy in a multi-center study[J]. Eur J Surg Oncol, 2010, 36(1): 30-5. doi: 10.1016/j.ejso.2009.05.007
[23]	Huang J, Chen X, Fei X, et al. Risk factors of non-sentinel lymph node metastasis and performance of MSKCC nomogramin breast cancer patients with metastatic sentinel lymph node[J]. Chin J Surg, 2015, 53(12): 941-6.
[24]	陈嘉莹, 陈嘉健, 杨犇龙, 等. MSKCC乳腺癌前哨淋巴结转移预测模型的验证性研究[J]. 中国实用外科杂志, 2011, 28(01): 89-93. http://www.cqvip.com/QK/90965A/201101/36429809.html
[25]	黄佳慧, 陈小松, 费晓春, 等. 乳腺癌非前哨淋巴结转移危险因素及MSKCC模型预测效能研究[J]. 中华外科杂志, 2015, 53(12): 941-6. doi: 10.3760/cma.j.issn.0529-5815.2015.12.011
[26]	曹迎明, 刘淼, 周波, 等. MSKCC和SOC模型预测中国乳腺癌患者非前哨淋巴结转移的验证比较研究[J]. 中国肿瘤临床, 2014,33(08): 508-12. doi: 10.3969/j.issn.1000-8179.21031009
[27]	邱鹏飞, 刘雁冰, 王永胜, 等. 乳腺癌前哨淋巴结转移相关因素与MSKCC列线图的验证性研究[J]. 中华内分泌外科杂志, 2012, 06(5): 307-12. http://d.wanfangdata.com.cn/Periodical_nfmwk201205006.aspx
[28]	罗铭. 乳腺癌非前哨淋巴结转移风险预测模型的验证及新模型的建立[D]. 南宁: 广西医科大学, 2014.
[29]	陈嘉莹. 早期乳腺癌前哨淋巴结及非前哨淋巴结转移预测模型的建立和验证[D]. 上海: 复旦大学, 2012.

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