优化壶腹癌术后化疗:一种风险驱动的精确护理方法

Di Zhang , Yuan Zheng , Mingru Liu , Jiaoyang Lu
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引用次数: 0

摘要

背景和目的本研究旨在建立一种创新的预测模型,用于估计壶腹癌患者的总生存期(OS),并评估针对个体风险特征量身定制的术后化疗(POCT)的临床益处。方法回顾性分析壶腹癌患者的临床资料。多变量分析确定了关键的预后因素,并将其纳入预测nomogram。POCT对OS的影响在按nomogram分层的风险组中进行评估。结果共纳入3921例患者,其中训练组2744例,验证组1177例。包含年龄、性别、肿瘤分级、T分期、N分期和肿瘤大小的nomogram (nomogram)优于TNM分期系统,3年、5年和8年OS的曲线下面积在训练组分别为0.755 vs 0.687、0.752 vs 0.694和0.750 vs 0.694,在验证组分别为0.705 vs 0.664、0.717 vs 0.679和0.734 vs 0.703。校正图显示预测和观察到的生存结果非常一致。决策曲线分析表明,跨阈值概率的净收益高于TNM分期。基于该模型的风险分层显示,高危患者的死亡风险显著增加(p <;0.001)。值得注意的是,POCT可显著改善高危患者的OS (p <;0.001),但在低风险患者中没有。结论并非所有患者都能从POCT中获益。该诺模图预测生存有效并可以指导治疗决策,优化结果通过提供额外的化疗对高危患者,同时保留低风险病人不必要的治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing postoperative chemotherapy for ampullary cancer: A risk-driven approach to precision care

Background and aims

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.

Methods

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.

Results

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 (p < 0.001). Notably, POCT significantly improved OS in high-risk patients (p < 0.001) but not in low-risk patients.

Conclusion

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.
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