摘要
目的 评价混合型肝癌(cHCC-CC)患者预后相关影响因素并构建预后模型。方法 回顾性分析SEER数据库2004—2015年267例cHCC-CC患者临床信息,并将患者按7∶3随机分为训练集和验证集。采用Kaplan-Meier法进行生存分析。基于R软件,在训练集中采用单因素及多因素Cox回归模型评价预后影响因素,并进一步构建列线图预后模型。最后,在训练集和验证集中使用C指数、ROC曲线和校准曲线对列线图的效能进行评价。结果 本研究共纳入267例cHCC-CC患者(训练集188例,验证集79例)。经过单因素和多因素Cox回归分析,将年龄、肿瘤大小、分化程度、TNM分期、纤维化评分和手术情况作为影响预后的独立因素纳入列线图。列线图在训练集中的C指数为0.778,预测1、3、5年总生存率的ROC曲线下面积分别为0.846、0.874、0.893;在验证集中的C指数为0.765,预测1、3、5年总生存率的ROC曲线下面积分别为0.843、0.781、0.755,提示该列线图具有良好的预后预测能力。同时,校准曲线提示列线图在训练集和验证集中均有较好的校准度。结论 本研究中构建的列线图模型可有效预测cHCC-CC患者的总生存率,对于评估患者预后和指导治疗具有一定参考价值。
Objective To evaluate the factors related to the prognosis of combined hepatocellular cholangiocarcinoma(cHCC-CC) and construct a prognosis evaluation model. Methods The clinical information of 267 patients with cHCC-CC in the SEER database from 2004 to 2015 was retrospectively analyzed. The patients were randomly divided into training cohort and validation cohort by a ratio of 7∶3. The survival analysis was performed by Kaplan-Meier method. Based on R software, the univariate and multivariate Cox proportional hazards model was used to evaluate the related influencing factors of prognosis in the training cohort, and then a nomogram model was constructed. At last, C-index, ROC curve and calibration curve were used to evaluate the efficiency of the nomogram model in training cohort and validation cohort. Results A total of 267 patients with cHCC-CC were enrolled in this study(188 in the training cohort and 79 in the validation cohort). Significant factors affecting the prognosis, including age, tumor size, degree of differentiation, TNM stage, fibrosis score and surgical treatment were taken into the nomogram based on univariate and multivariate Cox regression analysis. The C-index of the nomogram model is 0.778, while the areas under ROC curves of predicted 1-year, 3-year and 5-year overall survival rates were 0.846, 0.874, 0.893, respectively, in the training cohort. And the C-index of the nomogram model is 0.765, while the areas under ROC curves of 1-year, 3-year and 5-year overall survival rates were 0.843, 0.781, 0.755, respectively, in the validation cohort. These results indicated good prognostic prediction ability of the nomogram model. Meanwhile, the calibration curves showed that the nomogram model had a good calibration degree in both the training cohort and the validation cohort. Conclusion The nomogram model constructed in the study could effectively predict the overall survival rate of patients with cHCC-CC and play a vital role in evaluating the prognosis of patients as well as guiding treatment.
作者
王大林
田济铭
闫泽宇
安家泽
WANG Dalin;TIAN Jiming;YAN Zeyu;AN Jiaze(Department of Hepatobiliary Surgery,Xijing Hospital,Air Force Medical University,Xi'an 710032,China;Department of Gynaecology and Obstetrics,First School of Clinical Medicine,Lanzhou University,Lanzhou 730099,China;Department of General Surgery,Tangdu Hospital,Air Force Medical University,Xi'an 710038,China)
出处
《空军军医大学学报》
CAS
2022年第1期60-65,共6页
Journal of Air Force Medical University
基金
国家自然科学基金面上项目(82172919)
陕西省重点研发计划项目(2017SF-188)。
关键词
混合型肝癌
SEER
预后
列线图
combined hepatocellular cholangiocarcinoma
SEER
prognosis
nomogram
