Predictive Value of Lymphocyte-to-Neutrophil Ratio and Platelet-to-Neutrophil Ratio on PD-L1 Expression in Lung Cancer

IF 1.9 4区 医学 Q3 RESPIRATORY SYSTEM
Shun-Shun Cui, Ya Shen, Rui-Qing Yang
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引用次数: 0

Abstract

Objective

This study aimed to examine the predictive effect of the lymphocyte-to-neutrophil ratio (LNR) and the platelet-to-neutrophil ratio (PNR) on the expression of programmed death receptor ligand 1 (PD-L1) in patients diagnosed with lung cancer.

Methods

The clinical records of 86 patients diagnosed with lung cancer between January 2020 and February 2022 at Fu Yang People's Hospital were retrospectively analyzed. The records included information on age, gender, smoking history, hematological indices at the time of admission, staging of the lung malignancy, histopathological subtype, comorbidities, and the expression levels of PD-L1. Patients were stratified into two distinct cohorts based on their PD-L1 expression levels: Those with an expression level greater than or equal to 1% were classified into the PD-L1 positive expression group, while the remainder were categorized as the PD-L1 negative expression group. Univariate analysis and multivariate logistic regression analysis were used to identify the influencing factors of PD-L1, and the diagnostic efficacy was calculated using the receiver operating characteristic (ROC) curve.

Results

Upon analysis, the PD-L1 positive expression group manifested notably lower values as compared to their counterparts in the PD-L1 negative expression group (LNR: 0.262 ± 0.105 vs. 0.390 ± 0.201; PNR: 41.03 [29.64, 50.11] vs. 49.50 [37.38, 73.83]), and these differences were statistically significant. There was a notable disparity in PD-L1 expression based on gender, with males exhibiting a statistically significant higher positivity rate compared to females. Furthermore, patients in Stages I–III of the disease demonstrated a markedly elevated PD-L1 positivity rate compared to those in Stage IV (p < 0.05). Incorporating univariates with statistical differences into multivariate logistic regression analysis suggests that stage and LNR are independent risk factors for PD-L1 negative expression. ROC curve analyses revealed that the area under the ROC curve (AUC) for LNR as an indicator for PD-L1 positive expression stood at 0.706, while the AUC for PNR was calculated at 0.687.

Conclusion

PD-L1 expression is correlated with gender and lung cancer staging, and LNR and PNR have a predictive value for PD-L1 expression.

Abstract Image

淋巴细胞与中性粒细胞比率和血小板与中性粒细胞比率对肺癌 PD-L1 表达的预测价值
研究目的本研究旨在探讨淋巴细胞与中性粒细胞比值(LNR)和血小板与中性粒细胞比值(PNR)对肺癌患者程序性死亡受体配体1(PD-L1)表达的预测作用:回顾性分析阜阳市人民医院2020年1月至2022年2月期间确诊的86例肺癌患者的临床病历。这些病历包括患者的年龄、性别、吸烟史、入院时的血液学指标、肺部恶性肿瘤分期、组织病理学亚型、合并症以及 PD-L1 的表达水平。根据患者的 PD-L1 表达水平将其分为两个不同的组群:PD-L1表达水平大于或等于1%的患者被分为PD-L1阳性表达组,其余患者被分为PD-L1阴性表达组。采用单变量分析和多变量逻辑回归分析确定PD-L1的影响因素,并利用接收者操作特征曲线(ROC)计算诊断效果:经分析,PD-L1阳性表达组的数值明显低于PD-L1阴性表达组(LNR:0.262 ± 0.105 vs. 0.390 ± 0.201;PNR:41.03 [29.64, 50.11] vs. 49.50 [37.38, 73.83]),这些差异具有统计学意义。PD-L1的表达在性别上存在明显差异,男性的阳性率明显高于女性。此外,与 IV 期患者相比,I-III 期患者的 PD-L1 阳性率明显升高(p 结论:PD-L1 的表达与性别相关:PD-L1 的表达与性别和肺癌分期相关,LNR 和 PNR 对 PD-L1 的表达具有预测价值。
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来源期刊
Clinical Respiratory Journal
Clinical Respiratory Journal 医学-呼吸系统
CiteScore
3.70
自引率
0.00%
发文量
104
审稿时长
>12 weeks
期刊介绍: Overview Effective with the 2016 volume, this journal will be published in an online-only format. Aims and Scope The Clinical Respiratory Journal (CRJ) provides a forum for clinical research in all areas of respiratory medicine from clinical lung disease to basic research relevant to the clinic. We publish original research, review articles, case studies, editorials and book reviews in all areas of clinical lung disease including: Asthma Allergy COPD Non-invasive ventilation Sleep related breathing disorders Interstitial lung diseases Lung cancer Clinical genetics Rhinitis Airway and lung infection Epidemiology Pediatrics CRJ provides a fast-track service for selected Phase II and Phase III trial studies. Keywords Clinical Respiratory Journal, respiratory, pulmonary, medicine, clinical, lung disease, Abstracting and Indexing Information Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Embase (Elsevier) Health & Medical Collection (ProQuest) Health Research Premium Collection (ProQuest) HEED: Health Economic Evaluations Database (Wiley-Blackwell) Hospital Premium Collection (ProQuest) Journal Citation Reports/Science Edition (Clarivate Analytics) MEDLINE/PubMed (NLM) ProQuest Central (ProQuest) Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier)
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