Predictive Nomogram of Subsequent Liver Metastasis After Mastectomy or Breast-Conserving Surgery in Patients With Nonmetastatic Breast Cancer

被引:4
作者
Yang, Anli [1 ]
Xiao, Weikai [2 ]
Zheng, Shaoquan [1 ]
Kong, Yanan [1 ]
Zou, Yutian [1 ]
Li, Mingyue [3 ]
Ye, Feng [1 ]
Xie, Xiaoming [1 ]
机构
[1] Sun Yat sen Univ Canc Ctr, Dept Breast Oncol, Collaborat Innovat Ctr Canc Med, State Key Lab Oncol South China, Guangzhou 510060, Peoples R China
[2] Guangdong Acad Med Sci, Guangdong Prov Peoples Hosp, Dept Breast Canc, Ctr Canc, Guangzhou, Peoples R China
[3] Univ Penn, Dept Pathol & Lab Med, Perelman Sch Med, Philadelphia, PA USA
关键词
breast cancer; postoperative liver metastasis; nomogram; prediction; validation; RADIOFREQUENCY ABLATION;
D O I
10.1177/1073274821997418
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Metastasis accounts for the majority of deaths in patients with breast cancer. Liver metastasis is reported common for breast cancer patients. The purpose of this study was to construct a nomogram to predict the likelihood of subsequent liver metastasis in patients with nonmetastatic breast cancer, thus high-risk patient populations can be prevented and monitored. Methods: A total of 1840 patients with stage I-III breast cancer were retrospectively included and analyzed. A nomogram was constructed to predict liver metastasis based on multivariate logistic regression analysis. SEER database was used for external validation. C-index, calibration curve and decision curve analysis were used to evaluate the predictive performance of the model. Results: The nomogram included 3 variables related to liver metastasis: HER2 status (odds ratio (OR) 1.86, 95%CI 1.02 to 3.41; P = 0.045), tumor size (OR 3.62, 1.91 to 6.87; P < 0.001) and lymph node metastasis (OR 2.26, 1.18 to 4.34; P = 0.014). The C index of the training cohort, internal validation cohort and external validation cohort were 0.699, 0.814 and 0.791, respectively. The nomogram was well-calibrated, with no statistical difference between the predicted and the observed probabilities. Conclusion: We have developed and validated a robust tool enabled to predict subsequent liver metastasis in patients with nonmetastatic breast cancer. Distinguishing a population of patients at high risk of liver metastasis will facilitate preventive treatment or monitoring of liver metastasis.
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页数:7
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