Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China; Department of Thoracic and Cardiovascular Surgery, Nanjing Hospital of Chinese Medicine affiliated to Nanjing University of Chinese Medicine, Nanjing, 210012, China.
Department of Cardiothoracic Surgery, Jinling Hospital, Jinling School of Clinical Medicine, Nanjing Medical University, Nanjing, China.
Eur J Surg Oncol. 2021 Jun;47(6):1473-1480. doi: 10.1016/j.ejso.2020.12.004. Epub 2021 Jan 19.
Survival of patients with the same clinical stage varies widely and effective tools to evaluate the prognosis utilizing clinical staging information is lacking. This study aimed to develop a clinical nomogram for predicting survival of patients with Esophageal Squamous Cell Carcinoma (ESCC).
On the basis of data extracted from the SEER database (training cohort, n = 3375), we identified and integrated significant prognostic factors for nomogram development and internal validation. The model was then subjected to external validation with a separate dataset obtained from Jinling Hospital of Nanjing Medical University (validation cohort, n = 1187). The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index), Akaike information criterion (AIC) and calibration curves. And risk group stratification was performed basing on the nomogram scores.
On multivariable analysis of the training cohort, seven independent prognostic factors were identified and included into the nomogram. Calibration curves presented good consistency between the nomogram prediction and actual observation for 1-, 3-, and 5-year OS. The AIC value of the nomogram was lower than that of the 8th edition American Joint Committee on Cancer TNM (AJCC) staging system, whereas the C-index of the nomogram was significantly higher than that of the AJCC staging system. The risk groups stratified by CART allowed significant distinction between survival curves within respective clinical TNM categories.
The risk stratification system presented better discriminative ability for survival prediction than current clinical staging system and might help clinicians in decision making.
具有相同临床分期的患者的生存率差异很大，缺乏利用临床分期信息来评估预后的有效工具。本研究旨在开发一种用于预测食管鳞状细胞癌（ESCC）患者生存的临床列线图。
基于从 SEER 数据库中提取的数据（训练队列，n=3375），我们确定并整合了用于列线图开发和内部验证的显著预后因素。然后，我们使用来自南京医科大学金陵医院的独立数据集（验证队列，n=1187）对模型进行外部验证。通过一致性指数（C 指数）、赤池信息量准则（AIC）和校准曲线来确定列线图的预测准确性和判别能力。并根据列线图评分进行风险组分层。
在多变量分析的训练队列中，确定了七个独立的预后因素，并将其纳入到列线图中。校准曲线显示，列线图预测的 1、3 和 5 年 OS 与实际观察结果之间具有良好的一致性。列线图的 AIC 值低于第 8 版美国癌症联合委员会 TNM（AJCC）分期系统，而列线图的 C 指数明显高于 AJCC 分期系统。基于 CART 的风险组分层可以在各自的临床 TNM 类别内显著区分生存曲线。
与目前的临床分期系统相比，风险分层系统对生存预测具有更好的判别能力，可能有助于临床医生做出决策。
