Head and Neck Unit, Royal Marsden Hospital NHS Trust, London, UK
Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.
J Immunother Cancer. 2021 Jun;9(6). doi: 10.1136/jitc-2021-002718.
Previous studies have suggested that inflammatory markers (neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH) and fibrinogen) are prognostic biomarkers in patients with a variety of solid cancers, including those treated with immune checkpoint inhibitors (ICIs). We aimed to develop a model that predicts response and survival in patients with relapsed and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) treated with immunotherapy.
Analysis of 100 consecutive patients with unresectable R/M HNSCC who were treated with ICI. Baseline and on-treatment (day 28) NLR, fibrinogen and LDH were calculated and correlated with response, progression-free survival (PFS) and overall survival (OS) using univariate and multivariate analyses. The optimal cut-off values were derived using maximally selected log-rank statistics.
Low baseline NLR and fibrinogen levels were associated with response. There was a statistically significant correlation between on-treatment NLR and fibrinogen and best overall response. On-treatment high NLR and raised fibrinogen were significantly associated with poorer outcome. In multivariate analysis, on-treatment NLR (≥4) and on-treatment fibrinogen (≥4 ng/mL) showed a significant negative correlation with OS and PFS. Using these cut-off points, we generated an on-treatment score for OS and PFS (0-2 points). The derived scoring system shows appropriate discrimination and suitability for OS (HR 2.4, 95% CI 1.7 to 3.4, p<0.0001, Harrell's C 0.67) and PFS (HR 1.8, 95% CI 1.4 to 2.3, p<0.0001, Harrell's C 0.68). In the absence of an external validation cohort, results of fivefold cross-validation of the score and evaluation of median OS and PFS on the Kaplan-Meier survival distribution between trained and test data exhibited appropriate accuracy and concordance of the model.
NLR and fibrinogen levels are simple, inexpensive and readily available biomarkers that could be incorporated into an on-treatment scoring system and used to help predict survival and response to ICI in patients with R/M HNSCC.
既往研究表明，炎症标志物（中性粒细胞与淋巴细胞比值（NLR）、乳酸脱氢酶（LDH）和纤维蛋白原）是多种实体瘤患者（包括接受免疫检查点抑制剂（ICI）治疗的患者）的预后生物标志物。我们旨在建立一个模型，预测接受免疫治疗的复发性和/或转移性（R/M）头颈部鳞状细胞癌（HNSCC）患者的反应和生存情况。
对 100 例不可切除的 R/M HNSCC 患者进行分析，这些患者接受了 ICI 治疗。计算基线和治疗期间（第 28 天）的 NLR、纤维蛋白原和 LDH，并使用单变量和多变量分析将其与反应、无进展生存期（PFS）和总生存期（OS）相关联。使用最大选择对数秩统计量得出最佳截断值。
低基线 NLR 和纤维蛋白原水平与反应相关。治疗期间 NLR 和纤维蛋白原与最佳总体反应之间存在统计学显著相关性。治疗期间高 NLR 和纤维蛋白原升高与预后较差显著相关。在多变量分析中，治疗期间 NLR（≥4）和治疗期间纤维蛋白原（≥4ng/mL）与 OS 和 PFS 呈显著负相关。使用这些截断值，我们生成了一个治疗期间的 OS 和 PFS 评分（0-2 分）。所生成的评分系统显示出适当的区分度和对 OS（HR 2.4，95%CI 1.7 至 3.4，p<0.0001，Harrell's C 0.67）和 PFS（HR 1.8，95%CI 1.4 至 2.3，p<0.0001，Harrell's C 0.68）的适用性。在没有外部验证队列的情况下，对该评分进行五倍交叉验证的结果以及在训练数据和测试数据之间的 Kaplan-Meier 生存分布上评估中位数 OS 和 PFS，显示出模型的适当准确性和一致性。
NLR 和纤维蛋白原水平是简单、廉价且易于获得的生物标志物，可纳入治疗期间的评分系统，并用于帮助预测 R/M HNSCC 患者对 ICI 的生存和反应。
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