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刘旭东, 赵斌, 杜鹏, 张国强, 郑强, 赖佳敏, 程志斌. 基于术前FAR和SII的预后模型与TNM分期系统在评估胰腺癌根治术患者预后中的比较[J]. 肿瘤防治研究, 2023, 50(3): 264-270. DOI: 10.3971/j.issn.1000-8578.2023.22.1090
引用本文: 刘旭东, 赵斌, 杜鹏, 张国强, 郑强, 赖佳敏, 程志斌. 基于术前FAR和SII的预后模型与TNM分期系统在评估胰腺癌根治术患者预后中的比较[J]. 肿瘤防治研究, 2023, 50(3): 264-270. DOI: 10.3971/j.issn.1000-8578.2023.22.1090
LIU Xudong, ZHAO Bin, DU Peng, ZHANG Guoqiang, ZHENG Qiang, LAI Jiamin, CHENG Zhibin. Prognostic Model Based on Preoperative FAR and SII Versus TNM Staging System in Evaluating Prognosis of Patients with Pancreatic Cancer After Radical Resection[J]. Cancer Research on Prevention and Treatment, 2023, 50(3): 264-270. DOI: 10.3971/j.issn.1000-8578.2023.22.1090
Citation: LIU Xudong, ZHAO Bin, DU Peng, ZHANG Guoqiang, ZHENG Qiang, LAI Jiamin, CHENG Zhibin. Prognostic Model Based on Preoperative FAR and SII Versus TNM Staging System in Evaluating Prognosis of Patients with Pancreatic Cancer After Radical Resection[J]. Cancer Research on Prevention and Treatment, 2023, 50(3): 264-270. DOI: 10.3971/j.issn.1000-8578.2023.22.1090

基于术前FAR和SII的预后模型与TNM分期系统在评估胰腺癌根治术患者预后中的比较

Prognostic Model Based on Preoperative FAR and SII Versus TNM Staging System in Evaluating Prognosis of Patients with Pancreatic Cancer After Radical Resection

  • 摘要:
    目的 探讨胰腺导管腺癌患者术前纤维蛋白原/白蛋白比值(FAR)和系统免疫炎症指数(SII)对预后的预测价值。
    方法 受试者工作特征(ROC)曲线确定FAR、SII的最佳截断值,并进行分组。Cox风险比例模型分析胰腺癌根治术的预后影响因素,依此建立列线图(Nomogram)预后模型。C-index、AUC和校准曲线评估列线图的辨别和校准能力。DCA曲线评估列线图的临床有效性。
    结果 术前FAR及SII的最佳截断值分别为0.095和532.945。Cox比例风险回归模型显示:FAR≥ 0.095、SII≥ 532.945、CA199≥ 450.9 U/ml、肿瘤最大径≥ 4 cm、术后未进行化疗是影响胰腺癌预后不佳的独立危险因素(P< 0.05)。C-index、AUC、校准曲线和DCA曲线表明,列线图预后模型的辨别能力、校准能力和临床有效性均优于TNM分期系统预后模型。
    结论 构建的Nomogram预后模型较TNM分期预后模型具有更高的准确性、区分度及临床获益。

     

    Abstract:
    Objective To investigate the predictive value of preoperative fibrinogen/albumin ratio (FAR) and systemic immune inflammation index (SII) on the postoperative prognosis of patients with pancreatic ductal adenocarcinoma.
    Methods An ROC curve was used in determining the best cutoff values of FAR and SII and then grouped. The Cox proportional hazards model was used in analyzing the prognostic factors of radical pancreatic cancer surgery, and then a Nomogram prognostic model was established. C-index, AUC, and calibration curve were used in evaluating the discrimination and calibration ability of the Nomogram. DCA curves were used in assessing the clinical validity of the Nomograms.
    Results The optimal cutoff values for preoperative FAR and SII were 0.095 and 532.945, respectively. FAR≥ 0.095, SII≥ 532.945, CA199≥ 450.9 U/ml, maximum tumor diameter≥ 4 cm, and the absence of postoperative chemotherapy were independent risk factors for the poor prognosis of pancreatic cancer (P<0.05). The discrimination ability, calibration ability, and clinical effectiveness of Nomogram prognostic model were better than those of the TNM staging system.
    Conclusion The constructed Nomogram prognostic model has higher accuracy and level of discrimination and more clinical benefits than the TNM staging prognostic model.

     

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