Platelet-to-Lymphocyte Ratio (PLR), Neutrophil-to-Lymphocyte Ratio (NLR), Monocyte-to-Lymphocyte Ratio (MLR), and Eosinophil-to-Lymphocyte Ratio (ELR) as Biomarkers in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD)

Abstract

Purpose

The study comprehensively evaluated the prognostic roles of the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), basophil-to-lymphocyte ratio (BLR), and eosinophil-to-lymphocyte ratio (ELR) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).

Patients and Methods

Six hundred and nineteen patients with AECOPD and 300 healthy volunteers were retrospectively included into the study. The clinical characteristics of the patients with AECOPD and the complete blood counts (CBCs) of the healthy volunteers were collected. The associations of PLR, NLR, MLR, BLR, and ELR with airflow limitation, hospital length of stay (LOS), C-reactive protein (CRP), and in-hospital mortality in patients with AECOPD were analyzed.

Results

Compared with the healthy volunteers, PLR, NLR, MLR, BLR, and ELR were all elevated in COPD patients under stable condition. PLR, NLR, MLR, and BLR were further elevated while ELR was lowered during exacerbation. In the patients with AECOPD, PLR, NLR, and MLR were positively correlated with hospital LOS as well as CRP. In contrast, ELR was negatively correlated with hospital LOS as well as CRP. Elevated PLR, NLR, and MLR were all associated with more severe airflow limitation in AECOPD. Elevated PLR, NLR, and MLR were all associated with increased in-hospital mortality while elevated ELR was associated with decreased in-hospital mortality. Binary logistic regression analysis showed that smoking history, FEV1% predicted, pneumonia, pulmonary heart disease (PHD), uric acid (UA), albumin, and MLR were significant independent predictors ofin-hospital mortality. These predictors along with ELR were used to construct a nomogram for predicting in-hospital mortality in AECOPD. The nomogram had a C-index of 0.850 (95% CI: 0.799–0.901), and the calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) further demonstrated its good predictive value and clinical applicability.

Conclusion

In summary, PLR, NLR, MLR, and ELR served as useful biomarkers in patients with AECOPD.

Keywords:

• healthy volunteers
• in-hospital mortality
• length of stay
• nomogram
• pneumonia
• pulmonary heart disease

Abbreviations

COPD, Chronic obstructive pulmonary disease; PLR, platelet-to-lymphocyte ratio; NLR, neutrophil-to-lymphocyte ratio; MLR, monocyte-to-lymphocyte ratio; BLR, basophil-to-lymphocyte ratio; ELR, eosinophil-to-lymphocyte ratio; AECOPD, acute exacerbation of chronic obstructive pulmonary disease; CBC, complete blood count; LOS, length of stay; CRP, C-reactive protein; DCA, decision curve analysis; CIC, clinical impact curve; NRI, net reclassification improvement; IDI, integrated discrimination index; FEV1, forced expiratory volume in one second; FVC, forced vital capacity; EMR, electronic medical record; GOLD, Global Initiative for Chronic Obstructive Lung Disease; PaO2, arterial oxygen tension; PaCO2, arterial carbon dioxide tension; PHD, pulmonary heart disease; WBC, white blood cell; RBC, red blood cell; Hb, hemoglobin; UA, uric acid; Scr, serum creatinine; BUN, blood urea nitrogen; LDH, lactate dehydrogenase; OR, odds ratio; CI, confidence interval; ROC, receiver operating characteristic; C-index, index of concordance.

Data Sharing Statement

The clinical data for the patients with AECOPD used and/or analyzed during the current study are available from the corresponding author on reasonable request. The clinical data for the healthy volunteers used and/or analyzed during the current study are included within the Supplementary Material.

Ethics Approval and Informed Consent

This study was performed in line with the principles of the Declaration of Helsinki. The ethics approval was granted by the Medical Ethics Committee of People’s hospital of Guilin (No. 2022-011KY).

Acknowledgments

The authors thank all the medical staff for providing us more or less help in the collection of clinical parameter data.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

Author Ke-Wei Zhu was employed by GuangZhou BaiYunShan Pharmaceutical Holdings CO.,LTD. BaiYunShan Pharmaceutical General Factory, Guangzhou, People’s Republic of China. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Additional information

Funding

This work was supported by the Guilin Municipal Science and Technology Bureau [grant number 20190218-7-8].