Simple parameters to solve a complex issue: predicting response to checkpoint inhibitor therapy in lung cancer.

Pub Date : 2020-11-23 DOI:10.2217/lmt-2020-0024

James Newman, Isabel Preeshagul, Nina Kohn, Craig Devoe, Nagashree Seetharamu

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引用次数: 3

Abstract

Background: Noninvasive biomarkers predicting immune checkpoint inhibitor (ICI) response are urgently needed. We evaluated the predictive value of pretreatment neutrophil-to-lymphocyte ratio (NLR), smoking history, smoking intensity, BMI and programmed death ligand 1 (PD-L1) expression in non-small-cell lung cancer (NSCLC) patients treated with ICIs.

Materials & methods: Single-center retrospective study included 137 patients from July 2015 to February 2018. Outcomes included 3-month disease control rate, progression-free survival, and overall survival. Predictive value of biomarkers was assessed independently and in a multivariable model.

Results: NLR was associated with all outcomes. Smoking history was predictive of progression-free survival and smoking intensity was predictive of disease control rate. BMI and PD-L1 were not associated with any outcome. High BMI was associated with low NLR.

Conclusion: Simple clinical biomarkers can predict response to ICIs. A score incorporating both clinical factors and established tissue/serum biomarkers may be useful in identifying NSCLC patients who would benefit from ICIs.

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简单的参数解决一个复杂的问题:预测肺癌对检查点抑制剂治疗的反应。

背景:迫切需要预测免疫检查点抑制剂(ICI)反应的无创生物标志物。我们评估了预处理中性粒细胞与淋巴细胞比率(NLR)、吸烟史、吸烟强度、BMI和程序性死亡配体1 (PD-L1)表达在非小细胞肺癌(NSCLC)患者接受ICIs治疗中的预测价值。材料与方法:2015年7月至2018年2月，单中心回顾性研究纳入137例患者。结果包括3个月疾病控制率、无进展生存期和总生存期。在多变量模型中独立评估生物标志物的预测价值。结果:NLR与所有结果相关。吸烟史可预测无进展生存，吸烟强度可预测疾病控制率。BMI和PD-L1与任何结果无关。高BMI与低NLR相关。结论:简单的临床生物标志物可预测ICIs的疗效。结合临床因素和已建立的组织/血清生物标志物的评分可能有助于识别将受益于ICIs的非小细胞肺癌患者。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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