Predicting response to PD-1 inhibitors in head and neck squamous cell carcinomas using peripheral blood inflammatory markers

IF 5 2区医学 Q2 Medicine

Translational Oncology Pub Date : 2024-12-01 DOI:10.1016/j.tranon.2024.102222

Ruihua Fang , Yi Chen , Bixue Huang , Zhangfeng Wang , Xiaolin Zhu , Dawei Liu , Wei Sun , Lin Chen , Minjuan Zhang , Kexing Lyu , Wenbin Lei

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引用次数: 0

Abstract

Immune checkpoint inhibitor (ICI) treatment has the potential to induce durable disease remission. However, the current combined positive score (CPS) is insufficient accurate for predicting which patients will benefit from it. In the present study, a real-world retrospective study was conducted on 56 patients of HNSCC who received ICI treatment. Then the treatment that patient received and levels of pre-treatment blood inflammatory markers (NLR, MLR and PLR) were identified to develop a model for predicting immunotherapy response. Notably, the model achieved an area under the curve (AUC) of 0.877 (95 % CI 0.769–0.985) , providing a larger net benefit than the CPS marker (AUC=0.614, 95 % CI 0.466–0.762). Furthermore, the internal validation of the prediction model showed a C-index of 0.835. Patients with high score of the model would get improved PFS than those with low score. Therefore, the prediction model for patients with local advanced or R/M HNSCC receiving ICI treatment, which represented an better efficient prediction of immunotherapy response than CPS marker.

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利用外周血炎症标志物预测头颈部鳞状细胞癌患者对PD-1抑制剂的反应

免疫检查点抑制剂（ICI）治疗有可能诱导持久的疾病缓解。然而，目前的联合阳性评分（CPS）不足以准确预测哪些患者将从中受益。在本研究中，对56例接受ICI治疗的HNSCC患者进行了现实世界的回顾性研究。然后确定患者接受的治疗和治疗前血液炎症标志物（NLR， MLR和PLR）的水平，以建立预测免疫治疗反应的模型。值得注意的是，该模型的曲线下面积（AUC）为0.877 (95% CI 0.769-0.985)，比CPS标记（AUC=0.614, 95% CI 0.466-0.762）提供了更大的净效益。预测模型内部验证的c指数为0.835。模型评分高的患者比评分低的患者PFS得到改善。因此，该预测模型对于局部晚期或R/M恶性鳞癌患者接受ICI治疗，比CPS标志物更能有效预测免疫治疗反应。

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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来源期刊

Translational Oncology ONCOLOGY-

CiteScore

8.40

自引率

2.00%

发文量

314

审稿时长

54 days

期刊介绍： Translational Oncology publishes the results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of oncology patients. Translational Oncology will publish laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer. Peer reviewed manuscript types include Original Reports, Reviews and Editorials.