血液学参数作为免疫相关不良事件的预测指标：接受免疫治疗的非小细胞肺癌患者的危险因素分析
Hematological parameters as predictors of immune-related adverse events: risk factor analysis in non-small cell lung cancer patients undergoing immunotherapy.
作者信息
Jia Yong, Wang Rong, Shen Junlong, Wang Yingying
机构信息
Department of Thoracic Surgery, Baoji Central Hospital No. 8 Jiangtan Road, Weibin District, Baoji 721000, Shaanxi, China.
Department of Oncology Hematology, Baoji Traditional Chinese Medicine Hospital No. 2 Baozhong Road, Jintai District, Baoji 721000, Shaanxi, China.
出版信息
Am J Transl Res. 2025 Jul 15;17(7):4976-4985. doi: 10.62347/EUHL7337. eCollection 2025.
OBJECTIVE
To evaluate the predictive value of hematological biomarkers in assessing the risk of immune-related adverse events (irAEs) in non-small cell lung cancer (NSCLC) patients undergoing immunotherapy and to identify potential risk factors for personalized treatment optimization.
METHODS
Clinical data of 274 NSCLC patients who received immunotherapy between April 2018 and January 2021 were retrospectively analyzed. Patients were divided into irAEs and non-irAEs groups based on the occurrence of irAEs. Peripheral blood indices within one week before treatment initiation were assessed and compared, including absolute neutrophil count (ANC), lymphocyte count (LYM), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), albumin-to-alkaline phosphatase ratio (AAPR), and albumin-to-fibrinogen ratio (AFR). Kaplan-Meier analysis compared overall survival (OS) and progression-free survival (PFS), while logistic regression identified independent risk factors for irAEs. Receiver operating characteristic (ROC) curve analysis evaluated predictive performance.
RESULTS
Among the 274 patients, 116 (42.2%) developed irAEs. Compared to the non-irAEs group, the irAEs group exhibited significantly higher ANC, NLR, PLR, and SII, along with lower LYM, AAPR, and AFR as well as lower OS and PFS rates (all P < 0.05). Logistic regression showed that all hematological indicators were independent risk factors for irAEs (P < 0.05). ROC analysis showed an AUC of 0.722 for NLR and 0.829 for the combined model.
CONCLUSION
Pretreatment assessment of ANC, LYM, NLR, PLR, SII, AAPR, and AFR provides valuable predictive utility for irAEs risk in NSCLC patients undergoing immunotherapy. Integrating these biomarkers into clinical practice may enhance risk stratification and guide personalized treatment strategies to improve safety and therapeutic outcomes.
目的
评估血液生物标志物在评估接受免疫治疗的非小细胞肺癌（NSCLC）患者免疫相关不良事件（irAEs）风险中的预测价值，并确定个性化治疗优化的潜在风险因素。
方法
回顾性分析2018年4月至2021年1月期间接受免疫治疗的274例NSCLC患者的临床资料。根据irAEs的发生情况将患者分为irAEs组和非irAEs组。评估并比较治疗开始前一周内的外周血指标，包括绝对中性粒细胞计数（ANC）、淋巴细胞计数（LYM）、中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）、全身免疫炎症指数（SII）、白蛋白与碱性磷酸酶比值（AAPR）以及白蛋白与纤维蛋白原比值（AFR）。采用Kaplan-Meier分析比较总生存期（OS）和无进展生存期（PFS），同时通过逻辑回归确定irAEs的独立危险因素。采用受试者工作特征（ROC）曲线分析评估预测性能。
结果
274例患者中，116例（42.2%）发生irAEs。与非irAEs组相比，irAEs组的ANC、NLR、PLR和SII显著更高，而LYM、AAPR和AFR更低，OS和PFS率也更低（均P<0.05）。逻辑回归显示，所有血液学指标均为irAEs的独立危险因素（P<0.05）。ROC分析显示，NLR的曲线下面积（AUC）为0.722，联合模型的AUC为0.829。
结论
治疗前评估ANC、LYM、NLR、PLR、SII、AAPR和AFR可为接受免疫治疗的NSCLC患者的irAEs风险提供有价值的预测效用。将这些生物标志物纳入临床实践可能会加强风险分层并指导个性化治疗策略，以提高安全性和治疗效果。
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