尽管包括化疗和免疫检查点抑制剂（ICIs）在内的联合治疗改善了非小细胞肺癌（NSCLC）患者的总生存率（OS），但不良事件和治疗中断的发生率更高。由于程序化死亡配体-1（PD-L1）不能作为预测性生物标志物，我们调查了中性粒细胞与淋巴细胞比值（NLR）作为预测性生物标志物。在我们先前的研究中，我们证明了在高PD-L1表达（>50%）的患者接受化疗免疫联合治疗而不是单独免疫治疗时，低NLR可以预测生存益处。在这个当前的研究中，我们的目标是评估这种预测能力在低PD-L1表达（<50%）患者中的作用。共有142名患者入组，其中28名接受联合治疗，114名接受单独化疗。使用Kaplan-Meier法估计无进展生存（PFS）和OS，并使用log-rank检验进行比较。接受联合治疗的患者的PFS和OS明显优于接受单药治疗的患者。在低NLR亚组中，接受联合治疗的患者表现出具有临床意义的延长PFS和OS，这也得到了多变量Cox回归分析的验证。我们的研究展示了在NSCLC晚期患者中，当低PD-L1表达时，NLR作为生物标志物用于预测联合化疗和ICIs治疗的生存益处的潜力。Copyright © 2023 Chen, Lin, Tsai, Lin, Chang, Yen, Tseng, Su and Lin.

Although combination therapy including chemotherapy and immune checkpoint inhibitors (ICIs) improves overall survival (OS) of patients with non-small-cell lung cancer (NSCLC), there is a higher incidence of adverse events and treatment discontinuation. Since programmed death-ligand 1 (PD-L1) could not serve as a predictive biomarker, we investigated the neutrophil-to-lymphocyte ratio (NLR) as a predictive biomarker. In our previous research, we demonstrated that a low NLR could predict survival benefits when patients with high PD-L1 expression (> 50%) received chemoimmunotherapy as opposed to immunotherapy alone. In this current study, our objective is to evaluate this predictive capacity in patients with low PD-L1 expression (< 50%). A total of 142 patients were enrolled, 28 receiving combination therapy and 114 receiving chemotherapy alone. Progression-free survival (PFS) and OS were estimated using the Kaplan-Meier method and compared using the log-rank test. Patients who received combination therapy had significantly better PFS and OS than those who received monotherapy. In the subgroup of patients with low NLR, those who received combination therapy exhibited extended PFS and OS with clinical significance, which was also confirmed by multivariate Cox regression analysis. Our study demonstrates the potential use of NLR as a biomarker for predicting survival benefits when receiving combination therapy with chemotherapy and ICIs in patients with advanced NSCLC and low PD-L1 expression.Copyright © 2023 Chen, Lin, Tsai, Lin, Chang, Yen, Tseng, Su and Lin.