Department of Orthopedics, Huashan Hospital, Fudan University, 12, Wulumuqi Rd., Jing'an District, Shanghai, China.
Department of Radiotherapy, Oncology Hospital, Fudan University, Shanghai, China.
J Orthop Surg Res. 2020 Mar 4;15(1):88. doi: 10.1186/s13018-020-01607-8.
This study is to determine the risk factors for metastasis of Ewing sarcoma (ES) patients in SEER database. Then explore clinicopathological factors associated with poor prognosis. Furthermore, develop the nomogram to predict the probability of overall survival and cancer-specific survival METHODS: Thus, we collected clinicopathological data of ES patients in SEER database, and then used chi-square test and logistic regression to determine risk factors associated to metastasis. We also did survival analysis including Kaplan-Meier curve and Cox proportional hazard model to explore the risk factors associated to overall survival and cancer-specific survival, and then developed the nomogram to visualize and quantify the probability of survival.
After statistics, we find that patients with older ages (11-20 years old: OR = 1.517, 95% confidence interval [CI] 1.033-2.228, p = 0.034; 21-30 years old: OR = 1.659. 95%CI 1.054-2.610, p = 0.029), larger tumor size (> 8 cm: OR = 1.914, 95%CI 1.251-2.928, p = 0.003), and pelvic lesions (OR = 2.492, 95%CI 1.829-3.395, p < 0.001) had a higher risk of metastasis. ROC curves showed higher AUC (0.65) of combined model which incorporate these three factors to predict the presence of metastasis at diagnosis. In survival analysis, patients with older ages (11-20 years: HR = 1.549, 95%CI 1.144-2.099, p = 0.005; 21-30 years: HR = 1.808, 95%CI 1.278-2.556, p = 0.001; 31-49 years: HR = 3.481, 95%CI 2.379-5.094, p < 0.001; ≥ 50 years: HR = 4.307, 95%CI 2.648-7.006, p < 0.001) , larger tumor size (5-8 cm: HR = 1.386, 95%CI 1.005-1.991, p = 0.046; > 8 cm: HR = 1.877, 95%CI 1.376-2.561, p < 0.001), black race (HR = 2.104, 95%CI 1.296-3.416, p = 0.003), and wider extension (regional: HR = 1.373, 95%CI 1.033-1.823, p = 0.029; metastatic: HR = 3.259, 95%CI 2.425-4.379, p < 0.001) were associated with worse prognosis. Chemotherapy was associated with better prognosis (HR = 0.466, 95%CI 0.290-0.685, p < 0.001). The nomogram which developed by training set and aimed to predict OS and CSS showed good consistency with actual observed outcomes internally and externally.
In conclusion, tumor size and primary site were associated with distant metastasis at diagnosis. Age, tumor size, primary site, tumor extent, and chemotherapy were associated with overall survival and cancer-specific survival. Nomogram could predict the probability of OS and CSS and showed good consistency with actual observed outcomes internally and externally.
本研究旨在确定 SEER 数据库中尤文肉瘤(ES)患者转移的风险因素。然后探讨与不良预后相关的临床病理因素。此外,建立列线图以预测总生存率和癌症特异性生存率。
因此,我们收集了 SEER 数据库中 ES 患者的临床病理数据,然后使用卡方检验和逻辑回归来确定与转移相关的风险因素。我们还进行了生存分析,包括 Kaplan-Meier 曲线和 Cox 比例风险模型,以探讨与总生存率和癌症特异性生存率相关的风险因素,并建立列线图来可视化和量化生存概率。
经过统计学分析,我们发现年龄较大的患者(11-20 岁:OR = 1.517,95%置信区间 [CI] 1.033-2.228,p = 0.034;21-30 岁:OR = 1.659,95%CI 1.054-2.610,p = 0.029)、肿瘤较大(> 8cm:OR = 1.914,95%CI 1.251-2.928,p = 0.003)和骨盆病变(OR = 2.492,95%CI 1.829-3.395,p < 0.001)的患者转移风险更高。ROC 曲线显示,纳入这三个因素的联合模型对预测诊断时转移的存在具有更高的 AUC(0.65)。在生存分析中,年龄较大的患者(11-20 岁:HR = 1.549,95%CI 1.144-2.099,p = 0.005;21-30 岁:HR = 1.808,95%CI 1.278-2.556,p = 0.001;31-49 岁:HR = 3.481,95%CI 2.379-5.094,p < 0.001;≥ 50 岁:HR = 4.307,95%CI 2.648-7.006,p < 0.001)、肿瘤较大(5-8cm:HR = 1.386,95%CI 1.005-1.991,p = 0.046;> 8cm:HR = 1.877,95%CI 1.376-2.561,p < 0.001)、黑种人(HR = 2.104,95%CI 1.296-3.416,p = 0.003)和更广泛的扩展(区域性:HR = 1.373,95%CI 1.033-1.823,p = 0.029;转移性:HR = 3.259,95%CI 2.425-4.379,p < 0.001)与预后不良相关。化疗与更好的预后相关(HR = 0.466,95%CI 0.290-0.685,p < 0.001)。通过训练集开发的列线图旨在预测 OS 和 CSS,内部和外部均显示出与实际观察结果的良好一致性。
总之,肿瘤大小和原发部位与诊断时的远处转移有关。年龄、肿瘤大小、原发部位、肿瘤范围和化疗与总生存率和癌症特异性生存率有关。列线图可以预测 OS 和 CSS 的概率,并在内部和外部均显示出与实际观察结果的良好一致性。