Heng Qiuhan, Hou Mingxing, Leng Ying, Yu Hua
Department of the School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Department of General Surgery, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
J Gastrointest Oncol. 2025 Aug 30;16(4):1562-1572. doi: 10.21037/jgo-2025-143. Epub 2025 Aug 25.
Chemotherapy is an important treatment for intrahepatic cholangiocarcinoma (ICC) patients, but there is a lack of survival prediction models. This study aims to develop a nomogram to predict cancer-specific survival (CSS) in ICC patients receiving chemotherapy.
A retrospective analysis was performed using data from the Surveillance, Epidemiology, and End Results (SEER) database involving 1,363 ICC patients who receiving chemotherapy between 2010 and 2019. The patients were randomly allocated in a 7:3 ratio to the training cohort and validation cohort. Cox proportional hazards regression analysis was employed to identify prognostic factors for nomogram construction. The accuracy of the model was assessed using the concordance index (C-index), area under the curve (AUC) value, and calibration curve. Additionally, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were utilized to evaluate the clinical value of the nomogram and to compare it with tumor staging based on American Joint Committee on Cancer (AJCC) criteria.
Multivariate Cox regression analysis selected seven variables to establish the nomogram. The C-index and AUC value indicate that the nomogram has high accuracy. The calibration curve shows good consistency between the actual observed values and the nomogram-predicted CSS. Meanwhile, DCA, NRI, and IDI demonstrate that the nomogram has significant clinical applicability compared to tumor staging based on AJCC criteria. Furthermore, a risk classification system with satisfactory ability to identify different-risk patients was established.
We have developed a nomogram for predicting the prognosis of ICC patients receiving chemotherapy, which can effectively assess the prognosis of this patient population.
化疗是肝内胆管癌(ICC)患者的重要治疗方法,但缺乏生存预测模型。本研究旨在开发一种列线图,以预测接受化疗的ICC患者的癌症特异性生存(CSS)情况。
使用监测、流行病学和最终结果(SEER)数据库中的数据进行回顾性分析,该数据库纳入了2010年至2019年间接受化疗的1363例ICC患者。患者按7:3的比例随机分配到训练队列和验证队列。采用Cox比例风险回归分析确定列线图构建的预后因素。使用一致性指数(C指数)、曲线下面积(AUC)值和校准曲线评估模型的准确性。此外,利用决策曲线分析(DCA)、净重新分类改善(NRI)和综合判别改善(IDI)来评估列线图的临床价值,并将其与基于美国癌症联合委员会(AJCC)标准的肿瘤分期进行比较。
多变量Cox回归分析选择了7个变量来建立列线图。C指数和AUC值表明列线图具有较高的准确性。校准曲线显示实际观察值与列线图预测的CSS之间具有良好的一致性。同时,DCA、NRI和IDI表明,与基于AJCC标准的肿瘤分期相比,列线图具有显著的临床适用性。此外,还建立了一个能够有效识别不同风险患者的风险分类系统。
我们开发了一种用于预测接受化疗的ICC患者预后的列线图,它可以有效地评估该患者群体的预后。