Biomarkers (NLR, PLR, SII) for Frequent COPD Exacerbations: Diagnostic and Clinical Management Implications in a Retrospective Study

Yufen Fu,1– 3 Yuxin Wang,1,4 Yujiao Wang,1,4 Ting Mou,1,4 Xiang He,2,4 Junyi Wang,2,4 Anying Xiong,2,4 Bomiao Qing,2,4 Dehong Wu,2,4 Guoping Li1,2,4 1Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China; 2Laboratory of Allergy and Precision Medicine, Chengdu Institute of Respiratory Health, the Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, Chengdu, 610031, People’s Republic of China; 3Department of Pulmonary and Critical Care Medicine, Longchang People’s Hospital, Neijiang, 642150, People’s Republic of China; 4Department of Pulmonary Medicine, Chengdu Third People’s Hospital branch of National Clinical Research Center for Respiratory Disease, Affiliated Hospital of Chongqing Medical University, Chengdu, 610031, People’s Republic of ChinaCorrespondence: Guoping Li, Email [email protected]: To evaluate the diagnostic and predictive value of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) for frequent exacerbations of chronic obstructive pulmonary disease (AECOPD), and to develop a risk stratification scoring system to optimize clinical management in resource-limited healthcare settings.Patients and Methods: This retrospective observational study enrolled 16,849 AECOPD patients, categorized into frequent exacerbators (≥ 2 exacerbations/year, n=3,488) and non-frequent exacerbators (< 2 exacerbations/year, n=13,361). Comparative analyses of clinical characteristics and inflammatory biomarkers (NLR, PLR, SII, CRP, PCT) were conducted. Spearman correlation, receiver operating characteristic (ROC) curve analysis, and binary logistic regression were employed to assess biomarker performance. A risk scoring system was developed using odds ratios (OR) and regression coefficients (β) of NLR and PLR.Results: The frequent exacerbators group exhibited significantly higher median NLR (6.71 vs 5.10, P < 0.001), mean PLR (239 ± 204 vs 218 ± 195, P < 0.001), and median SII (1,137.48 vs 847.54, P < 0.001). NLR, PLR and SII showed strong positive correlations with CRP and PCT (P < 0.001). ROC analysis identified NLR (specificity = 84.1%) and PLR (sensitivity = 55%) as optimal diagnostic indicators. Regression analysis confirmed NLR and PLR as independent risk factors for frequent exacerbations. The risk stratification system categorized patients into low-risk (< 290 points; annual exacerbation rate 17%), intermediate-risk (290– 768 points; 19.1%), and high-risk (> 768 points; 23.4%) groups.Conclusion: NLR and PLR serve as cost-effective biomarkers for identifying high-risk frequent exacerbators patients with COPD in primary care settings. The percentile-based scoring system enables management strategies to address clinical needs in resource-constrained healthcare environments.Keywords: COPD, exacerbation, NLR, PLR, biomarkers