肺免疫预后指数联合预后营养指数对NSCLC患者免疫治疗反应的预测价值

Predictive value of lung immune prognostic index combined with prognostic nutritional index for the response to immunotherapy in patients with non-small cell lung cancer

    摘要
  • 摘要:
    目的 分析肺免疫预后指数（lung immune prognostic index，LIPI）联合预后营养指数（prognostic nutritional index，PNI）对非小细胞肺癌（non-small cell lung cancer，NSCLC）患者免疫治疗反应的预测价值。
    方法 选取驻马店市中心医院2022年1月至2023年12月106例NSCLC患者，根据免疫治疗后反应情况分为反应组72例、无反应组34例。比较两组临床资料、LIPI、PNI，分析LIPI、PNI与临床病理特征、治疗反应的关系，受试者工作特征曲线（receiver operating characteristic curve，ROC）、曲线下面积（area under the curve，AUC）分析LIPI、PNI对NSCLC患者免疫治疗反应的预测价值，精准-召回（precision-recall，PR）曲线评估联合预测价值。
    结果 两组TNM分期、淋巴结转移、远处转移比较，差异具有统计学意义（P<0.05）；无反应组LIPI良好患者占比低于反应组，LIPI不良患者占比高于反应组（P<0.05），无反应组PNI低于反应组（P<0.05）；LIPI与TNM分期、淋巴结转移、远处转移、治疗反应呈正相关，PNI与TNM分期、淋巴结转移、远处转移、治疗反应呈负相关（P<0.05）；校正后Logistic回归分析，LIPI、PNI与NSCLC免疫治疗反应情况仍显著相关（P<0.05）；LIPI、PNI联合预测患者免疫治疗反应的AUC为0.936，明显高于LIPI、PNI单独预测（P<0.05）；PR曲线显示AUC为0.852，说明联合预测有较高召回率和精准率。
    结论 NSCLC患者LIPI、PNI与TNM分期、淋巴结转移、远处转移、治疗反应密切相关，且LIPI、PNI联合预测NSCLC免疫治疗反应具有较高的参考价值。

     

    Abstract:
    Objective To evaluate the prognostic value of the lung immune prognostic index (LIPI) combined with the prognostic nutritional index (PNI) for predicting immunotherapy response in patients with non-small cell lung cancer (NSCLC).
    Methods A total of 106 patients with NSCLC who received immunotherapy in Zhumadian Central Hospital from January 2022 to December 2023 were selected and assigned into a response group (n=72) and non-response group (n=34) according to their response after immunotherapy. Clinical data, LIPI, and PNI of the two groups were compared to analyze the relationship between LIPI and PNI with clinicopathological features and treatment response and to analyze the predictive value of LIPI and PNI in the immunotherapy response of patients with NSCLC. The precision-recall (PR) curve was used to evaluate combined predictive values.
    Results The TNM stage, lymph node metastasis, and distant metastasis were significantly different between the two groups (P<0.05). The proportion of patients with good LIPI in the non-response group was lower than that in the response group, the proportion of patients with poor LIPI was higher than that in the response group (P<0.05), and the PNI in the non-response group was lower than that in the response group (P<0.05). LIPI positively correlated with TNM stage, lymph node metastasis, distant metastasis, and treatment response, whereas PNI negatively correlated with TNM stage, lymph node metastasis, distant metastasis, and treatment response (P<0.05). Logistic regression analysis showed that LIPI and PNI were still significantly correlated with immunotherapy response in patients with NSCLC (P<0.05). The area under the curve (AUC) of the combined prediction of LIPI and PNI was 0.936, which was significantly higher than that of LIPI and PNI alone (P<0.05). The PR curve showed an AUC of 0.852, indicating that the combined prediction had high recall and accuracy rates.
    Conclusions LIPI and PNI are closely related to TNM stage, lymph node metastasis, distant metastasis, and treatment response in patients with NSCLC. The combination of LIPI and PNI has a high reference value for predicting immunotherapy response in patients with NSCLC.

     

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