A Nomogram for Distinction and Potential Prediction of Liver Metastasis in Breast Cancer Patients.
A Nomogram for Distinction and Potential Prediction of Liver Metastasis in Breast Cancer Patients.
复制标题
用于区分和潜在预测乳腺癌患者肝转移的列线图
DOI：
10.7150/jca.24445
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发表时间：
2018
影响因子：
3.9
通讯作者：
Pan Q
中科院分区：
文献类型：
--
作者：
Lin Z;Yan S;Zhang J;Pan Q
乳腺癌肝转移预后差。本研究旨在开发一种可靠的工具，用于区分和预测乳腺癌患者的肝转移，从而帮助临床诊断和治疗。在这项研究中，共有6238例患者从SEER数据库中已知的远处转移状态和临床病理变量，并随机分为训练组和验证组。Logistic回归用于筛选变量，并构建诺模图。经多因素Logistic回归分析，性别、组织学类型、N分期、分级、年龄、ER、PR、HER2状态为构建诺模图的显著变量。判别和预测乳腺癌肝转移的诺模图通过了校正和验证步骤，训练集和验证集的受试者工作特征曲线下面积分别为0.6602和0.6511。我们的诺模图是一个可靠的和强大的工具，用于区分和预测乳腺癌患者的肝转移，从而帮助更好地选择医学检查和优化治疗方案，在医学肿瘤学家和外科医生的合作。
Liver metastasis from breast cancer has poor prognosis. We aimed at developing a reliable tool for making a distinction and prediction for liver metastasis in breast cancer patients, thus helping clinical diagnosis and treatment. In this study, totally 6238 patients from SEER database with known distant metastasis status and clinicopathologic variables were enrolled and divided randomly into training and validating groups. Logistic regression was used to screen variables and a nomogram was constructed. After multivariate logistic regression, sex, histology type, N stage, grade, age, ER, PR, HER2 status as significant variables for constructing the nomogram. The nomogram for distinguishing and predicting liver metastasis in breast cancer passed the calibration and validation steps and the areas under the receiver operating characteristic curve of the training set and the validation set were 0.6602 and 0.6511 respectively. Our nomogram is a reliable and robust tool for the distinction and prediction of liver metastasis in breast cancer patients, thus helping better choose medical examinations and optimize therapeutic regimen under the cooperation among medical oncologists and surgeons.
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