Evidence map›Paper›PMID 40207023›Full record

Observational studyInternational journal of chronic obstructive pulmonary disease2025

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

Yufen Fu, Yuxin Wang, Yujiao Wang, Ting Mou, Xiang He, Junyi Wang, Anying Xiong, Bomiao Qing, Dehong Wu, Guoping Li

Abstract readObservational StudyComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in International journal of chronic obstructive pulmonary disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Frailty in COPD: Clinical Impact, Diagnosis, Biomarkers, and Management Strategies.International journal of chronic obstructive pulmonary disease · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yufen FuDepartment of Pulmonary and Critical Care Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People's Republic of China.
Yuxin WangDepartment of Pulmonary and Critical Care Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People's Republic of China.
Yujiao WangDepartment of Pulmonary and Critical Care Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People's Republic of China.
Ting MouDepartment of Pulmonary and Critical Care Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People's Republic of China.
Xiang HeLaboratory 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.
Junyi WangLaboratory 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.
Anying XiongLaboratory 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.
Bomiao QingLaboratory 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.
Dehong WuLaboratory 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.
Guoping LiDepartment of Pulmonary and Critical Care Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: 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.

Indexed as

Blood PlateletsDecision Support TechniquesInflammation MediatorsLymphocytesNeutrophilsPulmonary Disease, Chronic ObstructiveAgedBiomarkersDisease ProgressionFemaleHumansLymphocyte CountMaleMiddle AgedPlatelet CountPredictive Value of TestsBiomarkersInflammation MediatorsbiomarkersCOPDexacerbationNLRPLR

Identifiers

PMID40207023
PMCPMC11980941

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.