基于白蛋白相关炎症复合指标的晚期非小细胞肺癌免疫治疗预后列线图构建及验证
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1.川北医学院附属医院 呼吸与危重症医学科;2.川北医学院

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教育部高等学校科学研究发展中心创新专项(2025XH022);四川省医学科技创新研究会(YCH-KY-YCZD2024-287);南充市科技局(22ZXKTYJ0001);川北医学院附属医院/广安区人民医院联合发展科研项目(2024LHFZ02);川北医学院校级科研发展基金项目(CBY23-QNA47)


Construction and validation of a nomogram for predicting the prognosis of advanced non-small cell lung cancer treated with immunotherapy based on albumin-related inflammatory composite indicators
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    摘要:

    【摘要】目的:探讨基于白蛋白相关炎症复合指标构建的列线图,对接受免疫检查点抑制剂(ICIs)治疗的晚期非小细胞肺癌(NSCLC)患者的预后预测价值,为临床个体化治疗提供参考。方法:回顾性收集274例晚期NSCLC患者的临床资料,以总生存期(OS)为主要终点,经Cox比例风险模型筛选独立预后因素并构建列线图,通过C指数、时间依赖性ROC曲线、校准曲线、DCA曲线等评估模型性能,同时分析其预后风险分层能力。结果:肝转移、TNM分期Ⅳ期、CEA≥2.54ng/mL、NPS高危组为OS独立危险因素,CALLY≥0.6为独立保护因素。该列线图预测1年、3年OS的AUC分别为0.755、0.801,C-index为0.72,校准曲线与DCA曲线证实模型拟合度及临床净获益良好,且可将患者分为低、中、高风险三组,分层能力显著(P<0.01)。结论:基于肝转移、TNM分期、CEA、NPS、CALLY构建的列线图,可有效预测患者OS,且预后风险分层能力良好,模型区分度、校准度优异,具有较高临床实用价值,可为个体化免疫治疗策略制定提供精准参考。

    Abstract:

    [Abstract]Objective: To investigate the prognostic predictive value of a nomogram constructed based on albumin-related inflammatory composite indicators for patients with advanced non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs), and to provide a reference for clinical individualized treatment. Methods: The clinical data of 274 patients with advanced NSCLC were retrospectively collected. The overall survival (OS) was set as the primary endpoint. Independent prognostic factors were selected through the Cox proportional hazards model and a nomogram was constructed. The performance of the model was evaluated using C-index, time-dependent ROC curve, calibration curve, and DCA curve, etc. At the same time, the prognostic risk stratification ability of the model was analyzed. Results: Liver metastasis, TNM stage IV, CEA ≥ 2.54 ng/mL, and high-risk group of NPS were independent risk factors for OS. CALLY ≥ 0.6 was an independent protective factor. The AUC of the nomogram for 1-year and 3-year OS was 0.755 and 0.801, respectively, and the C-index was 0.72. The calibration curve and DCA confirmed the good fit of the model and clinical net benefit, and the patients could be stratified into low, medium, and high-risk groups. The stratification ability was significant(P<0.01). Conclusion: The nomogram constructed based on liver metastasis, TNM stage, CEA, NPS, and CALLY can effectively predict the OS of patients, and the prognostic risk stratification ability is good. The model has excellent discrimination and calibration, and has high clinical practical value, which can provide precise references for the formulation of individualized immunotherapy strategies.

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  • 收稿日期:2026-03-20
  • 最后修改日期:2026-03-20
  • 录用日期:2026-04-13
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