临床研究

术前影像病理特征及肿瘤标志物预测乳腺癌前哨淋巴结转移风险

  • 李劭晋 ,
  • 郑世鹏
展开
  • 郑州大学第一附属医院乳腺外科 (郑州 450052 )

收稿日期: 2023-12-29

  网络出版日期: 2024-09-13

基金资助

河南省高等学校重点科研项目计划(19B320042);河南省医学科技攻关计划(联合共建)项目(LHGJ20190141);河南省医学教育研究项目(Wjlx2020063)

Relevant preoperative imaging pathological features and tumor markers serve as predictive indicators for the risk of sentinel lymph node metastasis in breast cancer

  • Shaojin LI ,
  • Shipeng. ZHENG
Expand
  • Department of Breast Surgery,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China

Received date: 2023-12-29

  Online published: 2024-09-13

摘要

目的 根据乳腺癌患者术前的影像病理特征以及肿瘤标志物指标来构建预测模型以预测前哨淋巴结(SLN)的转移情况。 方法 回顾性分析2022年1月至2023年4月在郑州大学第一附属医院收治的232例乳腺癌患者的术前检查资料,并按照3∶1随机分为训练集(174例)和验证集(58例),进行单因素分析和多因素logistic回归分析,以确定影响SLN转移的独立预测因素,并构建列线图,分别采用受试者工作特征曲线(ROC曲线)分析,校正曲线分析和决策曲线分析,评估模型的准确性以及临床应用价值。 结果 多因素分析结果显示,可触及性、CA153、钙化、ALN血流信号是SLN转移的独立危险因素(P < 0.05),将4个独立变量整合到nomogram图中,并绘制ROC,训练集和验证集的AUC分别为0.810(95%CI:0.744 ~ 0.876)、0.737(95%CI:0.606 ~ 0.867),校准曲线显示具有良好的预测准确性。 结论 建立一种nomogram来术前预测乳腺癌患者SLN转移风险,为临床实践提供了一种非侵入性的方法,并作为一种可靠的工具来识别不必要SLN活检的乳腺癌患者,有助于制定进一步腋窝淋巴结清扫术(ALND)及辅助治疗的决策。

本文引用格式

李劭晋 , 郑世鹏 . 术前影像病理特征及肿瘤标志物预测乳腺癌前哨淋巴结转移风险[J]. 实用医学杂志, 2024 , 40(17) : 2418 -2424 . DOI: 10.3969/j.issn.1006-5725.2024.17.011

Abstract

Objective To develop a prognostic model that integrates preoperative imaging, pathological features, and tumor marker indexes for predicting metastasis in sentinel lymph nodes(SLN). Methods The preoperative examination data of 232 breast cancer patients admitted to the First Affiliated Hospital of Zhengzhou University between January 2022 and April 2023 were retrospectively analyzed. The dataset was randomly divided into a training set (174 cases) and a validation set (58 cases) at a ratio of 3∶1. Univariate and multivariate logistic regression analyses were performed to identify independent predictors influencing SLN metastasis. A nomogram was constructed, and its accuracy and clinical applicability were evaluated using receiver operating characteristic (ROC curve) analysis, calibration curve analysis, and decision curve analysis. Results The multivariate analysis revealed that palpability, CA153, calcification, and ALN blood flow signal were identified as independent risk factors for SLN metastasis (P < 0.05). These four variables were integrated into a nomogram and plotted on the ROC curve. The area under the curves (AUCs) for the training set and validation set were 0.810 (95%CI: 0.744 ~ 0.876) and 0.737 (95%CI: 0.606 ~ 0.867), respectively, indicating good predictive accuracy as demonstrated by the calibration curve. Conclusion Revised sentence: "Developing a nomogram for preoperative prediction of SLN metastasis in breast cancer patients offers a non-invasive approach for clinical application and serves as a reliable tool to identify breast cancer patients who may not require SLN biopsy, thereby facilitating decisions regarding further axillary lymph node dissection (ALND) and adjuvant therapy.

参考文献

1 SUNG H, FERLAY J, SIEGEL R L,et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[J]. CA Cancer J Clin, 2021,71(3):209-249. doi:10.3322/caac.21660
2 ARNOLD M, MORGAN E, RUMGAY H,et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040[J]. Breast,2022,66:15-23. doi:10.1016/j.breast.2022.08.010
3 VERONESI P, CORSO G. Standard and controversies in sentinel node in breast cancer patients[J]. Breast,2019,48():S53-S56. doi:10.1016/s0960-9776(19)31124-5
4 QIU S Q, ZHANG G J, JANSEN L, et al. Evolution in sentinel lymph node biopsy in breast cancer[J]. Crit Rev Oncol Hematol,2018,123:83-94. doi:10.1016/j.critrevonc.2017.09.010
5 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):126-133. doi:10.1097/rlu.0000000000000985
6 GOLDHIRSCH A, WINER E P, COATES A S, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013[J]. Ann Oncol,2013,24(9):2206-2223.
7 张强,牛连杰, 黄涛,等.早期乳腺癌520例前哨淋巴结转移关联性分析及预测研究[J]. 中华肿瘤防治杂志, 2020, 27 (22): 1850-1854. doi:10.16073/j.cnki.cjcpt.2020.22.13
8 VAN LA PARRA R F, FRANCISSEN C M, PEER P G,et al. Assessment of the Memorial Sloan-Kettering Cancer Center nomogram to predict sentinel lymph node metastases in a Dutch breast cancer population[J]. Eur J Cancer, 2013,49(3):564-571. doi:10.1016/j.ejca.2012.04.025
9 ZHU L, JIN L, LI S, et al.Which nomogram is best for predicting non-sentinel lymph node metastasis in breast cancer patients? A meta-analysis[J]. Breast Cancer Res Treat,2013,137(3):783-795. doi:10.1007/s10549-012-2360-6
10 LALE A, YUR M, ?ZGüL H,et al. Predictors of non-sentinel lymph node metastasis in clinical early stage (cT1-2N0) breast cancer patients with 1-2 metastatic sentinel lymph nodes[J]. Asian J Surg,2020,43(4):538-549. doi:10.1016/j.asjsur.2019.07.019
11 LEONARDI M C, ARROBBIO C, GANDINI S,et al. Predictors of positive axillary non-sentinel lymph nodes in breast cancer patients with positive sentinel lymph node biopsy after neoadjuvant systemic therapy[J]. Radiother Oncol,2021,163:128-135. doi:10.1016/j.radonc.2021.08.013
12 QIU Y, ZHANG X, WU Z,et al. MRI-Based Radiomics Nomogram: Prediction of Axillary Non-Sentinel Lymph Node Metastasis in Patients With Sentinel Lymph Node-Positive Breast Cancer[J]. Front Oncol,2022,12:811347. doi:10.3389/fonc.2022.811347
13 FONG W, TAN L, TAN C, et al.Predicting the risk of axillary lymph node metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features and the use of nomograms: a prospective single-center observational study[J]. Eur Radiol,2022,32(12):8200-8212. doi:10.1007/s00330-022-08855-8
14 GAO Y, LUO Y, ZHAO C, et al. Nomogram based on radiomics analysis of primary breast cancer ultrasound images: prediction of axillary lymph node tumor burden in patients[J]. Eur Radiol,2021,31(2):928-937. doi:10.1007/s00330-020-07181-1
15 LI X, YANG L, JIAO X. Development and Validation of a Nomogram for Predicting Axillary Lymph Node Metastasis in Breast Cancer[J]. Clin Breast Cancer,2023,23(5):538-545. doi:10.1016/j.clbc.2023.04.002
16 暴珞宁, 王瑛, 陈东, 等. 超声影像组学标签预测乳腺癌前哨淋巴结转移的价值[J]. 实用医学杂志, 2021, 37 (15): 2007-2011. doi:10.3969/j.issn.1006-5725.2021.15.020
17 LIU M, MAO N, MA H, et al. Pharmacokinetic parameters and radiomics model based on dynamic contrast enhanced MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer[J]. Cancer Imaging, 2020,20(1):65. doi:10.1186/s40644-020-00342-x
18 MATHIS K L, HOSKIN T L, BOUGHEY J C, et al. Palpable presentation of breast cancer persists in the era of screening mammography[J]. J Am Coll Surg,2010,210(3):314-318. doi:10.1016/j.jamcollsurg.2009.12.003
19 AZAM S, ERIKSSON M, SJ?LANDER A,et al. Mammographic microcalcifications and risk of breast cancer[J]. Br J Cancer,2021,125(5):759-765. doi:10.1038/s41416-021-01459-x
20 胡仰玲, 曾辉, 何子龙, 等. 钙化型乳腺癌的分子分型特点及其预后分析[J]. 实用医学杂志, 2020, 36 (10): 1354-1359. doi:10.3969/j.issn.1006-5725.2020.10.017
21 XIONG J, ZUO W, WU Y, et al.Ultrasonography and clinicopathological features of breast cancer in predicting axillary lymph node metastases[J]. BMC Cancer,2022,22(1):1155. doi:10.1186/s12885-022-10240-z
22 WANG X F, ZHANG G C, ZUO Z C, et al. A novel nomogram for the preoperative prediction of sentinel lymph node metastasis in breast cancer[J]. Cancer Med,2023,12(6):7039-7050. doi:10.1002/cam4.5503
23 DARWISH I A, WANI T A, KHALIL N Y, et al. Novel automated flow-based immunosensor for real-time measurement of the breast cancer biomarker CA15-3 in serum[J]. Talanta,2012,97:499-504. doi:10.1016/j.talanta.2012.05.005
24 WANG W, XU X, TIAN B, et al. The diagnostic value of serum tumor markers CEA, CA19-9, CA125, CA15-3, and TPS in metastatic breast cancer[J]. Clin Chim Acta,2017,470:51-55. doi:10.1016/j.cca.2017.04.023
25 冯霖, 何真, 王欣欣. 超声BI-RADS分级联合血清CA153、CEA、ALP检测在乳腺癌早期诊断及腋窝淋巴结转移预测中的应用[J]. 中国医学创新, 2023, 20 (28): 146-152. doi:10.3969/j.issn.1674-4985.2023.28.034
26 LUO J, XIAO J, YANG Y, et al. Strategies for five tumour markers in the screening and diagnosis of female breast cancer[J]. Front Oncol,2023,12:1055855. doi:10.3389/fonc.2022.1055855
文章导航

/