Department of General Surgery, Qilu Hospital of Shandong University, Jinan, China.
Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Science, Jinan, China.
Eur J Surg Oncol. 2024 Dec;50(12):108659. doi: 10.1016/j.ejso.2024.108659. Epub 2024 Sep 3.
CCA has a poor prognosis. Different anatomical subtypes are characterized by distinct clinical features, surgical options, and prognoses, which can potentially impact survival outcomes following radical resection. In addition to the malignancy of CCA itself, clinical staging and treatment methods are the main factors that can affect survival. This study aims to update a more reliable prediction model for the prognosis of CCA based on different anatomical locations.
A total of 1172 CCA patients (305 iCCA, 467 pCCA, and 400 dCCA) who underwent surgical resection between 2015 and 2022 were included in the analysis. The covariates included in the analysis were age, sex, tumor diameter, differentiation grade, T stage, N stage, M stage, neural invasion, cancer thrombus, history of hepatitis B or biliary calculi, and receipt of adjuvant chemotherapy. The data were randomly divided into training (80 %) and validation cohort (20 %).
We developed a nomogram of the sensitive model and calculated concordance indices of different constructed prognostic survival models. Meanwhile, we validated the effectiveness of the nomogram model and compared it with the TNM system through decision curve analysis (DCA) and internal cohort validation. The nomogram model had a better net benefit than the TNM system at any given threshold for iCCA, pCCA, and dCCA, regardless of their location.
We have updated the prognostic model for OS in CCA patients who underwent radical resection according to the different tumor locations. This model can effectively predict OS and has the potential to facilitate individual clinical decision-making.
CCA 预后较差。不同的解剖亚型具有不同的临床特征、手术选择和预后，这可能会影响根治性切除术后的生存结果。除了 CCA 本身的恶性程度外，临床分期和治疗方法是影响生存的主要因素。本研究旨在基于不同解剖部位更新更可靠的 CCA 预后预测模型。
共纳入 2015 年至 2022 年间接受手术切除的 1172 例 CCA 患者（305 例 iCCA、467 例 pCCA 和 400 例 dCCA）。分析中纳入的协变量包括年龄、性别、肿瘤直径、分化程度、T 分期、N 分期、M 分期、神经侵犯、癌栓、乙肝或胆石症病史以及辅助化疗。数据随机分为训练（80%）和验证队列（20%）。
我们开发了一个敏感模型的列线图，并计算了不同构建的预后生存模型的一致性指数。同时，我们通过决策曲线分析（DCA）和内部队列验证验证了列线图模型的有效性，并将其与 TNM 系统进行了比较。对于 iCCA、pCCA 和 dCCA，无论其位置如何，列线图模型在任何给定阈值下的净获益均优于 TNM 系统。
我们根据肿瘤的不同位置更新了接受根治性切除的 CCA 患者的 OS 预后模型。该模型可有效预测 OS，具有辅助个体化临床决策的潜力。
