Yuan Bei, Lu Haojie, Hu Dong, Xu Kai, Xiao Songhua
Department of Orthopaedics, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Front Surg. 2023 Jan 13;9:1014781. doi: 10.3389/fsurg.2022.1014781. eCollection 2022.
Esophageal cancer (EC) is a common malignant tumor worldwide, and patients with both EC and bone metastasis (BM) have a poor prognosis. We aimed to determine the risk and prognostic factors for BM in patients with newly diagnosed EC and to conduct two nomograms to predict the probability of BM and overall survival after BM.
Data from patients with EC from 2010 to 2015 were reviewed in the Surveillance, Epidemiology, and End Results (SEER) database. We divided participants into training and validation cohorts using univariate and multivariate logistic regression analyses and Cox regression models to explore the risk and prognostic factors of BM, respectively. Moreover, two nomograms were developed for predicting the risk and prognosis of BM in patients with EC. Then we used receiver operating characteristic curves, decision curve analysis, and calibration curves to evaluate the nomogram models. The overall survival of patients with EC and BM was analyzed using the Kaplan-Meier method.
A total of 10,730 patients with EC were involved, 735 of whom had BM at the time of diagnosis. Histologic type, sex, age, N stage, primary site, liver, lung, and brain metastases, and tumor differentiation grade were identified as independent BM risk factors. Histological type, chemotherapy, brain, liver, and lung metastases were identified as prognostic risk factors for patients with EC and BM. We developed diagnostic and prognostic nomograms according to the results. Receiver operating characteristic curves, calibration, and Kaplan-Meier curves, and decision curve analysis all indicated that both nomograms had great clinical predictive ability and good clinical application potential.
Two novel nomograms were constructed to predict the risk and prognosis of BM in patients with EC. These prediction models can effectively assist clinicians in clinical decision-making based on their good accuracy and reliability.
食管癌（EC）是全球常见的恶性肿瘤，同时患有食管癌和骨转移（BM）的患者预后较差。我们旨在确定新诊断的食管癌患者发生骨转移的风险和预后因素，并构建两个列线图来预测骨转移的概率以及骨转移后的总生存期。
回顾了监测、流行病学和最终结果（SEER）数据库中2010年至2015年食管癌患者的数据。我们分别使用单因素和多因素逻辑回归分析以及Cox回归模型将参与者分为训练队列和验证队列，以探讨骨转移的风险和预后因素。此外，还开发了两个列线图来预测食管癌患者骨转移的风险和预后。然后我们使用受试者工作特征曲线、决策曲线分析和校准曲线来评估列线图模型。采用Kaplan-Meier方法分析食管癌和骨转移患者的总生存期。
共纳入10730例食管癌患者，其中735例在诊断时已有骨转移。组织学类型、性别、年龄、N分期、原发部位、肝、肺和脑转移以及肿瘤分化程度被确定为独立的骨转移危险因素。组织学类型、化疗、脑、肝和肺转移被确定为食管癌和骨转移患者的预后危险因素。根据结果我们开发了诊断和预后列线图。受试者工作特征曲线、校准曲线、Kaplan-Meier曲线和决策曲线分析均表明，这两个列线图均具有良好的临床预测能力和临床应用潜力。
构建了两个新的列线图来预测食管癌患者骨转移的风险和预后。这些预测模型具有良好的准确性和可靠性，能够有效地协助临床医生进行临床决策。
