Chen Mingyu, Cao Jiasheng, Zhang Bin, Pan Long, Cai Xiujun
Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University, Hangzhou 310016, China.
Key Laboratory of Endoscopic Technique Research of Zhejiang Province, Sir Run-Run Shaw Hospital, Zhejiang University, Hangzhou 310016, China.
J Cancer. 2019 Jun 2;10(14):3246-3252. doi: 10.7150/jca.30046. eCollection 2019.
: According to the stage of tumor, it's hard suitable to predict the prognosis for gallbladder cancer, especially for node-negative gallbladder cancer. Therefore, we aimed to create a nomogram based on demographic and clinicopathologic characteristics to estimate individualized potential impacts on postoperative overall survival. : 789 patients with node-negative gallbladder cancer were selected from the Surveillance, Epidemiology, and End Results and randomly divided into training and internal validation group. Univariate and multivariate survival analysis were used to identify prognostic factors. The nomogram was constructed using Cox proportional hazards models. We evaluated the performance of the nomogram with Harrell's concordance index and calibration curve. The nomogram was externally validated in 115 patients with node-negative gallbladder cancer from the Sir Run Run Shaw hospital. : The nomogram for overall survival was built on the basis of five independent factors, such as age, sex, histology, T-stage, and number of examined lymph nodes. The C-index of nomogram for overall survival in the internal and external validation group was up to 0.724 and 0.716, respectively. Both of those calibration curves showed good agreement between predicted and observed outcomes in the 1-, 3-, 5-year overall survival. Compared to the 7th edition AJCC stage, the nomogram had a better difference in predicting overall survival, even could further classify patients into four risk subgroups in each stage. : This nomogram can be used as a decision model to predict the outcomes of postoperative overall survival for node-negative gallbladder cancer, and may give useful guidance to clinicians for next treatment.
根据肿瘤分期，很难准确预测胆囊癌的预后，尤其是对于淋巴结阴性的胆囊癌。因此，我们旨在基于人口统计学和临床病理特征创建一个列线图，以估计对术后总生存的个体化潜在影响。从监测、流行病学和最终结果中选取789例淋巴结阴性的胆囊癌患者，并随机分为训练组和内部验证组。采用单因素和多因素生存分析来确定预后因素。使用Cox比例风险模型构建列线图。我们用Harrell一致性指数和校准曲线评估列线图的性能。该列线图在邵逸夫医院的115例淋巴结阴性的胆囊癌患者中进行了外部验证。总生存列线图基于年龄、性别、组织学、T分期和检查的淋巴结数量这五个独立因素构建。内部和外部验证组中总生存列线图的C指数分别高达0.724和0.716。这两条校准曲线在1年、3年、5年总生存的预测结果和观察结果之间显示出良好的一致性。与第7版美国癌症联合委员会（AJCC）分期相比，列线图在预测总生存方面有更好的差异，甚至可以在每个阶段进一步将患者分为四个风险亚组。该列线图可作为一种决策模型，用于预测淋巴结阴性胆囊癌术后总生存的结果，并可能为临床医生的下一步治疗提供有用的指导。
