Department of Orthopedics, Xianyang Central Hospital, Xianyang, China.
Clinical Medical Research Center, Xianyang Central Hospital, Xianyang, China.
Front Public Health. 2022 May 4;10:877736. doi: 10.3389/fpubh.2022.877736. eCollection 2022.
This study aims to predict the lymphatic metastasis in Ewing's sarcoma (ES) patients by nomogram. The risk of lymphatic metastasis in patients with ES was predicted by the built model, which provided guidance for the clinical diagnosis and treatment planning.
A total of 929 patients diagnosed with ES were enrolled from the year of 2010 to 2016 in the Surveillance, Epidemiology, and End Results (SEER) database. The nomogram was established to determine predictive factors of lymphatic metastasis according to univariate and multivariate logistic regression analysis. The validation of the model performed using multicenter data ( = 51). Receiver operating characteristics (ROC) curves and calibration plots were used to evaluate the prediction accuracy of the nomogram. Decision curve analysis (DCA) was implemented to illustrate the practicability of the nomogram clinical application. Based on the nomogram, we established a web calculator to visualize the risk of lymphatic metastases. We further plotted Kaplan-Meier overall survival (OS) curves to compare the survival time of patients with and without lymphatic metastasis.
In this study, the nomogram was established based on six significant factors (survival time, race, T stage, M stage, surgery, and lung metastasis), which were identified for lymphatic metastasis in ES patients. The model showed significant diagnostic accuracy with the value of the area under the curve (AUC) was 0.743 (95%CI: 0.714-0.771) for SEER internal validation and 0.763 (95%CI: 0.623-0.871) for multicenter data external validation. The calibration plot and DCA indicated that the model had vital clinical application value.
In this study, we constructed and developed a nomogram with risk factors to predict lymphatic metastasis in ES patients and validated accuracy of itself. We found T stage (Tx OR = 2.540, 95%CI = 1.433-4.503, < 0.01), M stage (M1, OR = 2.061, 95%CI = 1.189-3.573, < 0.05) and survival time (OR = 0.982, 95%CI = 0.972-0.992, < 0.001) were important independent factors for lymphatic metastasis in ES patients. Furthermore, survival time in patients with lymphatic metastasis or unclear situation ( < 0.0001) was significantly lower. It can help clinicians make better decisions to provide more accurate prognosis and treatment for ES patients.
本研究旨在通过列线图预测尤文肉瘤（ES）患者的淋巴转移。通过构建的模型预测 ES 患者发生淋巴转移的风险，为临床诊断和治疗方案的制定提供指导。
从 2010 年至 2016 年，SEER 数据库共纳入 929 例 ES 患者。通过单因素和多因素 logistic 回归分析，建立列线图以确定淋巴转移的预测因素。采用多中心数据（n = 51）对模型进行验证。使用受试者工作特征（ROC）曲线和校准图评估列线图的预测准确性。决策曲线分析（DCA）用于说明列线图临床应用的实用性。基于列线图，我们建立了一个网络计算器，以可视化淋巴转移的风险。我们进一步绘制 Kaplan-Meier 总生存（OS）曲线，以比较有和无淋巴转移患者的生存时间。
本研究基于 6 个显著因素（生存时间、种族、T 分期、M 分期、手术和肺转移）建立了预测 ES 患者淋巴转移的列线图模型。模型在 SEER 内部验证中的曲线下面积（AUC）值为 0.743（95%CI：0.714-0.771），在多中心数据外部验证中的 AUC 值为 0.763（95%CI：0.623-0.871），具有显著的诊断准确性。校准图和 DCA 表明该模型具有重要的临床应用价值。
本研究构建并开发了一个包含风险因素的列线图来预测 ES 患者的淋巴转移，并验证了其准确性。我们发现 T 分期（Tx OR = 2.540，95%CI = 1.433-4.503，<0.01）、M 分期（M1，OR = 2.061，95%CI = 1.189-3.573，<0.05）和生存时间（OR = 0.982，95%CI = 0.972-0.992，<0.001）是 ES 患者发生淋巴转移的重要独立因素。此外，有淋巴转移或情况不明（<0.0001）的患者的生存时间明显较低。它可以帮助临床医生做出更好的决策，为 ES 患者提供更准确的预后和治疗。
