Yang Xi-Lin, Huang Nan, Wang Ming-Ming, Lai Hua, Wu Da-Jun
Department of Radiation Oncology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
Department of Oncology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Med (Lausanne). 2021 Jul 9;8:688535. doi: 10.3389/fmed.2021.688535. eCollection 2021.
To compare the prognostic predictive performance of six lymph node (LN) staging schemes: American Joint Committee on Cancer (AJCC) N stage, number of retrieved lymph nodes (NRLN), number of positive lymph nodes (NPLN), number of negative lymph nodes (NNLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) among node-positive endometrioid endometrial cancer (EEC) patients. A total of 3,533 patients diagnosed with node-positive EEC between 2010 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively analyzed. We applied X-tile software to identify the optimal cutoff value for different staging schemes. Univariate and multivariate Cox regression models were used to assess the relationships between different LN schemes and survival outcomes [disease-specific survival (DSS) and overall survival (OS)]. Moreover, Akaike information criterion (AIC) and Harrell concordance index (C-index) were used to evaluate the predictive performance of each scheme in both continuous and categorical patterns. N stage (N1/N2) was not an independent prognostic factor for node-positive EEC patients based on multivariate analysis (DSS: = 0.235; OS: = 0.145). Multivariate model incorporating LNR demonstrated the most superior goodness of fit regardless of continuous or categorical pattern. Regarding discrimination power of the models, LNR outperformed other models in categorical pattern (OS: C-index = 0.735; DSS: C-index = 0.737); however, LODDS obtained the highest C-index in continuous pattern (OS: 0.736; DSS: 0.739). N stage (N1/N2) was unable to differentiate the prognosis for node-positive EEC patients in our study. However, LNR and LODDS schemes seemed to have a better predictive performance for these patients than other number-based LN schemes whether in DSS or OS, which revealed that LNR and LODDS should be more helpful in prognosis assessment for node-positive EEC patients than AJCC N stage.
比较六种淋巴结(LN)分期方案:美国癌症联合委员会(AJCC)N分期、切除淋巴结数量(NRLN)、阳性淋巴结数量(NPLN)、阴性淋巴结数量(NNLN)、淋巴结比率(LNR)以及阳性淋巴结对数比值(LODDS)在淋巴结阳性的子宫内膜样子宫内膜癌(EEC)患者中的预后预测性能。对2010年至2016年期间来自监测、流行病学和最终结果(SEER)数据库的3533例诊断为淋巴结阳性EEC的患者进行回顾性分析。我们应用X-tile软件确定不同分期方案的最佳截断值。采用单因素和多因素Cox回归模型评估不同LN方案与生存结局[疾病特异性生存(DSS)和总生存(OS)]之间的关系。此外,使用赤池信息准则(AIC)和哈雷尔一致性指数(C指数)评估每种方案在连续和分类模式下的预测性能。基于多因素分析,N分期(N1/N2)不是淋巴结阳性EEC患者的独立预后因素(DSS: =0.235;OS: =0.145)。纳入LNR的多因素模型无论在连续还是分类模式下均显示出最优越的拟合优度。关于模型的辨别力,LNR在分类模式下优于其他模型(OS:C指数=0.735;DSS:C指数=0.737);然而,LODDS在连续模式下获得最高的C指数(OS:0.736;DSS:0.739)。在我们的研究中,N分期(N1/N2)无法区分淋巴结阳性EEC患者的预后。然而,无论是在DSS还是OS方面,LNR和LODDS方案对这些患者的预测性能似乎优于其他基于数量的LN方案,这表明LNR和LODDS在淋巴结阳性EEC患者的预后评估中比AJCC N分期更有帮助。