Zhang Di, Zheng Yuan, Liu Mingru, Lu Jiaoyang
Department of Medical Oncology, Qilu Hospital of Shandong University, Jinan 250012, Shandong, China.
Department of Gastroenterology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China.
ILIVER. 2025 Apr 26;4(2):100166. doi: 10.1016/j.iliver.2025.100166. eCollection 2025 Jun.
This research aimed to develop an innovative predictive model for estimating overall survival (OS) in patients with ampullary carcinoma and to evaluate the clinical benefits of postoperative chemotherapy (POCT) tailored to individual risk profiles.
Data from patients with ampullary carcinoma were retrospectively analyzed. Multivariable analysis identified key prognostic factors, which were incorporated into a predictive nomogram. The impact of POCT on OS was assessed within risk groups stratified by the nomogram.
Data for 3921 patients were included, with 2744 in the training cohort and 1177 in the validation cohort. A nomogram incorporating age, sex, tumor grade, T stage, N stage, and tumor size outperformed the TNM staging system, with areas under the curve for 3-year, 5-year, and 8-year OS of 0.755 vs 0.687, 0.752 vs 0.694, and 0.750 vs 0.694, respectively, in the training cohort and 0.705 vs 0.664, 0.717 vs 0.679, and 0.734 vs 0.703 in the validation cohort. Calibration plots showed excellent agreement between predicted and observed survival outcomes. Decision curve analysis indicated a net benefit across threshold probabilities above that of TNM staging. Risk stratification based on the model indicated that high-risk patients had a significantly increased mortality risk ( < 0.001). Notably, POCT significantly improved OS in high-risk patients ( < 0.001) but not in low-risk patients.
Not all patients benefit from POCT. The proposed nomogram predicts survival effectively and can guide treatment decisions, optimizing outcomes by providing additional chemotherapy for high-risk patients while sparing low-risk patients from unnecessary treatment.
本研究旨在开发一种创新的预测模型，用于估计壶腹癌患者的总生存期（OS），并评估根据个体风险特征定制的术后化疗（POCT）的临床益处。
对壶腹癌患者的数据进行回顾性分析。多变量分析确定关键预后因素，并将其纳入预测列线图。在根据列线图分层的风险组中评估POCT对OS的影响。
纳入3921例患者的数据，其中训练队列2744例，验证队列1177例。包含年龄、性别、肿瘤分级、T分期、N分期和肿瘤大小的列线图优于TNM分期系统，训练队列中3年、5年和8年OS的曲线下面积分别为0.755对0.687、0.752对0.694和0.750对0.694，验证队列中分别为0.705对0.664、0.717对0.679和0.734对0.703。校准图显示预测生存结果与观察到的生存结果之间具有良好的一致性。决策曲线分析表明，在高于TNM分期的阈值概率范围内存在净获益。基于该模型的风险分层表明，高危患者的死亡风险显著增加（<0.001）。值得注意的是，POCT显著改善了高危患者的OS（<0.001），但对低危患者没有改善。
并非所有患者都能从POCT中获益。所提出的列线图能有效预测生存，并可指导治疗决策，通过为高危患者提供额外化疗，同时避免低危患者接受不必要的治疗来优化治疗结果。
