Shao Chen-Ye, Yu Yue, Li Qi-Fan, Liu Xiao-Long, Song Hai-Zhu, Shen Yi, Yi Jun
Department of Cardiothoracic Surgery, Nanjing Hospital of Chinese Medicine, Nanjing, China.
Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Front Oncol. 2021 Sep 2;11:736573. doi: 10.3389/fonc.2021.736573. eCollection 2021.
Clinical staging is essential for clinical decisions but remains imprecise. We purposed to construct a novel survival prediction model for improving clinical staging system (cTNM) for patients with esophageal adenocarcioma (EAC).
A total of 4180 patients diagnosed with EAC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and included as the training cohort. Significant prognostic variables were identified for nomogram model development using multivariable Cox regression. The model was validated internally by bootstrap resampling, and then subjected to external validation with a separate cohort of 886 patients from 2 institutions in China. The prognostic performance was measured by concordance index (C-index), Akaike information criterion (AIC) and calibration plots. Different risk groups were stratified by the nomogram scores.
A total of six variables were determined related with survival and entered into the nomogram construction. The calibration curves showed satisfied agreement between nomogram-predicted survival and actual observed survival for 1-, 3-, and 5-year overall survival. By calculating the AIC and C-index values, our nomogram presented superior discriminative and risk-stratifying ability than current TNM staging system. Significant distinctions in survival curves were observed between different risk subgroups stratified by nomogram scores.
The established and validated nomogram presented better risk-stratifying ability than current clinical staging system, and could provide a convenient and reliable tool for individual survival prediction and treatment strategy making.
临床分期对临床决策至关重要，但仍不够精确。我们旨在构建一种新型生存预测模型，以改进食管腺癌（EAC）患者的临床分期系统（cTNM）。
从监测、流行病学和最终结果（SEER）数据库中提取了4180例诊断为EAC的患者作为训练队列。使用多变量Cox回归确定用于列线图模型开发的显著预后变量。该模型通过自助重采样进行内部验证，然后用来自中国2家机构的886例患者的独立队列进行外部验证。通过一致性指数（C指数）、赤池信息准则（AIC）和校准图来衡量预后性能。根据列线图得分对不同风险组进行分层。
共确定了6个与生存相关的变量并纳入列线图构建。校准曲线显示列线图预测的生存与1年、3年和5年总生存的实际观察生存之间具有良好的一致性。通过计算AIC和C指数值，我们的列线图比当前的TNM分期系统具有更好的鉴别和风险分层能力。在根据列线图得分分层的不同风险亚组之间观察到生存曲线有显著差异。
所建立并验证的列线图比当前临床分期系统具有更好的风险分层能力，可为个体生存预测和治疗策略制定提供便捷可靠的工具。
