免疫检查点抑制剂（ICIs）在癌症治疗中的应用导致了免疫相关不良事件（irAEs）的增加，这可能导致治疗中断甚至致命反应。本研究的目的是评估外周生物标志物中性粒细胞与淋巴细胞比值（NLR）在预测irAEs方面的有用性。我们进行了数据库的系统搜索，以确定关于NLR对irAEs的预测价值的研究。如果原始研究中未提供调整后的OR和95%的置信区间，我们使用标准化均数差（SMD）来比较连续的NLR，使用原始的比值比（OR）来计算分组的NLR。meta分析包括47个研究，共涉及11491例接受ICIs治疗的癌症患者。与无irAEs的患者相比，基线连续NLR在患有irAEs的患者中显著降低（SMD=-1.55，95%CI=-2.64至-0.46，P=0.006）。同样，分类NLR显示，较低的基线NLR与增加的irAEs相关（OR=0.55，95%CI=0.41-0.73，P<0.001）。亚组分析揭示，NLR临界值为3和5时预测irAEs的OR分别为0.4和0.59。有趣的是，较高的基线NLR与较高的免疫相关肝损伤发生率相关（OR=2.44，95%CI=1.23-4.84，I2 = 0%，P=0.010）。我们的研究表明，较低的基线NLR与更高的整体irAEs风险相关。然而，进一步的研究仍需确定最佳的临界值，并探索NLR在预测特定类型irAEs中的有效性。版权所有 © 2023 Zhang, Tan, Li and Liu.

The use of immune checkpoint inhibitors (ICIs) in cancer treatment has led to an increase in immune-related adverse events (irAEs), which can cause treatment discontinuation and even fatal reactions. The purpose of this study was to evaluate the usefulness of the peripheral biomarker neutrophil to lymphocyte ratio (NLR) in predicting irAEs.A systematic search of databases was conducted to identify studies on the predictive value of NLR for irAEs. The standardized mean difference (SMD) was used to compare continuous NLR, while crude odds ratios (ORs) were calculated for categorized NLR if adjusted ORs and 95% confidence intervals (CIs) were not provided in the original study.The meta-analysis included 47 studies with a total of 11,491 cancer patients treated with ICIs. The baseline continuous NLR was significantly lower in patients with irAEs compared to those without (SMD=-1.55, 95%CI=-2.64 to -0.46, P=0.006). Similarly, categorized NLR showed that lower baseline NLR was associated with increased irAEs (OR=0.55, 95%CI=0.41-0.73, P<0.001). Subgroup analysis revealed that the OR for predicting irAEs with NLR cut-off values of 3 and 5 was 0.4 and 0.59, respectively. Interestingly, increased baseline NLR was associated with a higher incidence of immune-related liver injury (OR=2.44, 95%CI=1.23-4.84, I2 = 0%, P=0.010).Our study suggests that lower baseline NLR is associated with a higher risk of overall irAEs. However, further studies are needed to determine the best cut-off value and explore the efficacy of NLR in predicting specific types of irAEs.Copyright © 2023 Zhang, Tan, Li and Liu.