首都医科大学学报 ›› 2025, Vol. 46 ›› Issue (3): 410-419.doi: 10.3969/j.issn.1006-7795.2025.03.003

• 肿瘤研究进展:从基础到临床 • 上一篇    下一篇

15种营养/炎症指标对手术后肿瘤患者的预后预测能力比较

刘晓倩1,2#,孙凯1,2#,王晓琳1,2,赵倩倩1,2,武笑笑1,2,沈方琪1,2,陈曦1,2,田晨旭1,2,吴迪1,2,宋春花3,许红霞4,丛明华5,石汉平1,2,贾平平1,2*   

  1. 1. 首都医科大学附属北京世纪坛医院临床营养科,北京 100038;2. 国家市场监管重点实验室(肿瘤特医食品),北京 100038;3. 郑州大学公共卫生学院,郑州 450001;4. 陆军军医大学大坪医院临床营养科,重庆 400037;5. 中国医学科学院肿瘤医院肿瘤综合科,北京 100021
  • 收稿日期:2025-02-27 出版日期:2025-06-21 发布日期:2025-06-24
  • 通讯作者: 贾平平 E-mail:pingpingj@ccmu.edu.cn
  • 基金资助:
    国家自然科学基金项目(82273940),国家重点研发计划项目(2022YFC2010100,2022YFC2010101)。

Comparison of the prognostic value of 15 nutritional/inflammatory indicators in postoperative cancer patients

Liu Xiaoqian1,2#, Sun Kai1,2#, Wang Xiaolin1,2, Zhao Qianqian1,2, Wu Xiaoxiao1,2, Shen Fangqi1,2, Chen Xi1,2,Tian Chenxu1,2, Wu Di1,2, Song Chunhua3, Xu HongXia4, Cong Minghua5, Shi Hanping1,2, Jia Pingping1,2*   

  1. 1.Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing 100038, China; 2. State Market Regulation, Key Laboratory of Cancer FSMP for State Market Regulation, Beijing 100038, China; 3.College of Public Health, Zhengzhou University, Zhengzhou 450001, China, 4.Department of Clinical Nutrition, Daping Hospital, Army Medical University, Chongqing 400037, China; 5.Department of Comprehensive Oncology,Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021,China
  • Received:2025-02-27 Online:2025-06-21 Published:2025-06-24
  • Supported by:
    This study was supported by National Natural Science Foundation of China (82273940), the National Key Research and Development Program of China (2022YFC2010100,2022YFC2010101).

摘要: 目的  探索术后肿瘤患者中,对总生存期(overall survival, OS)预测能力最强的营养/炎症相关指标,为肿瘤患者的术后康复提供指导。方法  收集3 191例手术患者的15种营养/炎症相关指标,采用最大选择秩统计法计算连续性指标的最佳截断值。Kaplan-Meier方法用于评估OS,采用Cox比例风险模型分析上述15种指标与生存的关联及通过时间依赖性受试者工作特征(receiver operating characteristic,ROC)曲线和C指数评估15种指标的预测能力。结果  多变量分析表明,15种指标均与接受手术患者的较差OS显著相关(P均<0.05)。时间曲线下面积(area under the curve, AUC)和C指数分析显示,术后肿瘤患者的OS预测能力最强的3个指数是营养风险指数(nutritional risk index, NRI)(C指数: 0.597),C反应蛋白与白蛋白比值(C-reactive protein-to-albumin ratio, CAR)(C指数:  0.587)和C反应蛋白与淋巴细胞比值(C-reactive protein-to-lymphocyte ratio, CLR)(C指数: 0.587)。最大选择秩统计法求出NRI的最佳截断值为104.31 (即NRI<104.31时提示患者出现营养不良),CAR的最佳截断值为0.05 (即CAR≥0.05时提示患者出现较强的炎症反应,且通常伴随营养不良), CLR最佳截断值为1.18(即CLR≥1.18时提示患者出现较强的炎症反应)。亚组分析结果表明,NRI、CAR和CLR与肿瘤分期的交互作用较好,患者在出现较强炎症反应或出现营养不良时,肿瘤淋巴结转移(tumor node metastasis, TNM)Ⅲ/Ⅳ期的患者与TNM Ⅰ/Ⅱ期的患者有显著的差异。结论  在术后的肿瘤患者中,NRI、CLR和CAR预后预测价值较高,且结合患者临床分期可以更好地指导临床诊疗。

关键词: 炎症指标, 营养指标, 肿瘤, 术后, 预后预测

Abstract: Objective  To explore and identify the nutritional/inflammatory indicator with the highest predictive potential for overall survival (OS) in postoperative tumor patients so as to provide guidance for postoperative rehabilitation of tumor patients. Methods  Data from 3 191 surgical patients were collected, including 15 nutritional/inflammatory indicators. The maximum selection rank statistic method was used to calculate the optimal cut-off values for continuous indicators. The Kaplan-Meier method was used to assess OS, and Cox proportional hazards models were used to analyze the association between the aforementioned 15 indicators and survival. The predictive value of these 15 indicators was evaluated with receiver operating characteristic (ROC) curves and C-index. Results  Multivariate analysis showed that all 15 indicators were significantly associated with poorer OS in surgical patients (P<0.05 for all). Time-dependent area under the curve (AUC) and C-index analysis indicated that 3 indicators with the highest predictive potential in OS in postoperative tumor patients were the nutritional risk index (NRI) (C-index: 0.597), C-reactive protein-to-albumin ratio (CAR) (C-index: 0.587), and C-reactive protein-to-lymphocyte ratio (CLR) (C-index: 0.587). The optimal cut-off value for NRI was determined to be 104.31 (i.e., NRI<104.31 suggests malnutrition) with the maximum selection rank statistic method, the optimal cut-off value for CAR to be 0.05 (i.e., CAR≥0.05 suggests a strong inflammatory response, often accompanied by malnutrition), and the optimal cut-off value for CLR to be 1.18 (i.e., CLR≥1.18 suggests a strong inflammatory response). Subgroup analysis indicated that NRI, CAR, and CLR had good correlation with tumor staging, and there were significant differences between tumor node metastasis (TNM) Ⅲ/Ⅳ stage patients and TNM Ⅰ/Ⅱ stage patients when there was a strong inflammatory response or malnutrition. Conclusion In postoperative tumor patients, NRI, CLR, and CAR have high prognostic value. Combining  these with the patient's clinical stage, it enables more precise guidance for clinical diagnosis and treatment strategies. 

Key words: inflammation indicators, nutritional indicators, cancer, postoperative outcomes, prognosis prediction

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