https://orcid.org/0000-0001-7662-7115
Figures
Abstract
Background
The association between blood eosinophils and COPD exacerbation has been controversial. This study aims to investigate whether high blood eosinophils predict the risk of COPD exacerbation across different thresholds and subgroups.
Methods
PubMed, Embase and Web of science were searched for randomized controlled trial (RCT) and observational studies regarding the relationship between blood eosinophils and COPD exacerbation. Pooled risk ratio (RR) for COPD exacerbation was calculated using the Mantel-Haenszel method with a random-effects model.
Results
A total of 21 studies (1 RCT and 20 observational studies) with 79868 participants were included. Thresholds of high blood eosinophils including absolute counts (200, 300 and 400 cell/μL) and percentages (2%, 3% and 4%) were analyzed respectively. Pooled analyses suggested that high blood eosinophils were significantly associated with increased risk of COPD exacerbation when using the thresholds of 300 cells/μL (RR 1.21, 95%CI 1.12–1.30, P <0.001, 16 studies), 400 cells/μL (RR 1.79, 95%CI 1.41–2.28, P <0.001, 3 studies), 2% (RR 1.26, 95%CI 1.02–1.55, P = 0.030, 10 studies) and 4% (RR 1.44, 95%CI 1.05–1.96, P = 0.022, 4 studies), but not 200 cells/μL and 3% (P>0.05). Moreover, high blood eosinophils contributed to moderate-severe exacerbation of COPD by the cutoffs of 300 cells/μL (RR 1.30, 95%CI 1.16–1.45, P<0.001, 11 studies) and 2% (RR 1.33, 95%CI 1.02–1.76, P = 0.037, 8 studies). In subgroup analyses, the pooled results further showed a significant association between high blood eosinophils (especially over 300 cells/μL) and risk of COPD exacerbation among patients from Europe and Asia, and whether with stable or exacerbation phase at baseline, and regardless of the follow-up time (≤ or > 1year).
Citation: Chen F, Yang M, Wang H, Liu L, Shen Y, Chen L (2024) High blood eosinophils predict the risk of COPD exacerbation: A systematic review and meta-analysis. PLoS ONE 19(10): e0302318. https://doi.org/10.1371/journal.pone.0302318
Editor: Victor Abiola Adepoju, Jhpiego Nigeria, NIGERIA
Received: May 17, 2023; Accepted: April 2, 2024; Published: October 3, 2024
Copyright: © 2024 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data are all contained within the manuscript.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: AECOPD, Acute exacerbation of COPD; CI, confidence interval; COPD, chronic obstructive pulmonary disease; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; GOLD, Global Initiative for Chronic Obstructive Lung Disease; ICS, inhaled corticosteroids; Jadad, Jadad scale; NOS, Newcastle-Ottawa Scale; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; RCT, randomized controlled trial; RR, risk ratio; WHO, World Health Organization
Introduction
Chronic obstructive pulmonary disease (COPD) is a heterogeneous airway disease with significant morbidity and mortality [1]. According to the World Health Organization (WHO), COPD has been the third leading cause of death worldwide, putting a huge burden on global health-care systems [2]. Acute exacerbation of COPD (AECOPD) is the major cause of disease progression, increased hospitalization rate, prolonged hospital stay, poor quality of life and prognosis [3,4], contributing to the largest part of the total COPD burden [5]. The effective prediction and prevention of acute exacerbation has been key measures for COPD management, which depends on the investigation and controlling of risk factors. Currently, prediction for future risk of AECOPD mainly depends on the history of exacerbations in the prior year [6]. Specific and reliable indicators are still lacking.
Evidence has suggested that eosinophil plays a significant role in COPD. An unbiased cluster analysis revealed that 28% of acute exacerbation was associated with sputum eosinophilia, and the cut-off value of 2% blood eosinophils having a sensitivity of 90% and specificity of 60% for identifying sputum eosinophilia [7]. The 2024 Global Initiative for Chronic Obstructive Lung Disease (GOLD) guideline further underscores the importance of blood eosinophil count in guiding inhaled corticosteroids (ICS) therapy, and its association with airway pathogenic bacterial species [6]. Therefore, blood eosinophils could be potential biomarkers for predicting COPD progression and treatment effect.
Meanwhile, the relationship between blood eosinophils and risk of COPD exacerbation has attracted attention, but remains controversial [8–10]. During a three-year follow up, the COPDGene and ECLIPSE cohort studies indicated that high blood eosinophils (≥300 cells/μL) predicted future exacerbation outcome [9], while this finding was not repeated in some other reports [10,11]. Study on the CHAIN and BODE cohorts showed that blood eosinophils ≥300 cells/μL persisting over 2 years was not correlated with higher risk of AECOPD, although better survival was observed in this subgroup [10]. It is worth noting that, many previous studies included distinct subgroups, applied different thresholds, or failed to exclude patients with asthma, which cause potential confounding. Consequently, recent meta-analyses have examined the role of blood eosinophils in predicting the risk of acute exacerbation in COPD, but with uncertain conclusions [12,13]. Lately, it was reported AECOPD patients with blood EOS (≥ 2%) had higher readmission rates compared to those patients with no eosinophilia, indicating high blood EOS count could predict the risk of AECOPD [14].
To provide more comprehensive evidence, we systematically reviewed the current literature, to investigate whether high blood eosinophils predict increased risk of future COPD exacerbation. Given the cut-off value defining high blood eosinophils was undetermined, we analyzed the effects of different absolute (200, 300, 400 cells/μL) and relative (2%, 3%, 4%) thresholds respectively, which were widely used in previous studies or recommended by the guideline [11,15].
Methods
Searching strategy and selection criteria
This systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline (PRISMA 2020) [16]. PubMed, Embase and Web of Science were searched for reports regarding the relationship between blood eosinophils and AECOPD, from inception to October 01, 2023. Medical Subject Heading and Title/Abstract keywords were applied with the following search terms (using every possible combination): eosinophil, eosinophilia, chronic obstructive pulmonary disease and COPD. The search strategy was list in S1 Table. For the purpose of rapid review, the language was restricted to English [17]. Studies meeting the following criteria were included: 1) participants: adult patients (aged ≥18 years) with COPD, diagnosed according to the GOLD spirometry guideline (forced expiratory volume in 1 second (FEV1) / forced vital capacity(FVC)<0.7, post-bronchodilation) [6]; 2) exposure: providing data on baseline blood eosinophils of patients, and using at least one of the following cut-off values to define high blood eosinophils: 2%, 3%, 4%, 200 cells/μL, 300 cells/μL and 400 cells/μL; 3) outcome: exacerbation of COPD; 4) design: randomized controlled trials (RCTs) and observational studies (prospective or retrospective cohort studies, longitudinal studies). We excluded studies enrolling patients with asthma or other reported allergic diseases. Brief description of some excluded studies and the reasons for their exclusion were presented in S2 Table.
According to the selection criteria, two investigators (FC and MY) performed the initial search, independently screened titles and abstracts for studies and excluded duplicate or irrelevant records. For articles requiring further assessment, the full text was reviewed, and the references were manually checked to identify additional eligible studies. Disagreements were resolved by discussion between the two reviewers or with the help of the third investigator (LC).
Data extraction and quality assessment
Two investigators (FC and MY) independently extracted data from each study using a standardized Excel file. The following information was picked up: first author (year of publication), country, study design, number of participants, demographic characteristics of patients, phases of COPD at baseline, maintenance treatment for COPD, thresholds of high blood eosinophils, follow-up time, definition of AECOPD and the outcome data. For the missing data, special effort was made to contact the corresponding authors of the original studies. Studies without available outcome data were not included in the quantitative analysis. The primary outcome was exacerbation of COPD. The secondary outcome was moderate-severe exacerbation. The quality of RCTs was evaluated with the Jadad Scale [18,19]. The 5-point Jadad Scale contains three items: randomization (0–2), blinding (0–2), and withdrawals/dropouts (0–1). Studies that scored over 3 points on the Jadad Scale were considered to be of high quality. The Newcastle-Ottawa Scale (NOS) was used to rate the risk of bias for observational studies [20], with a maximum score of 9 and a score of ≥6 indicating a low risk. Two investigators (MY and HW) independently assessed the quality of studies. Discrepancies were resolved through discussion with the third investigator (LL).
Statistical analysis
Pooled effect estimates were expressed as RR with 95% confidence interval (CI). Statistical heterogeneity across studies was evaluated with the I2 statistic. I2 ≥ 50% indicated significant heterogeneity [21]. The Mantel-Haenszel method with a random-effects model was used to calculate pooled RRs and 95% CIs.
Because of undetermined cut-off value of high blood eosinophils currently, we chose to analyze the thresholds of 2%, 3%, 4%, 200, 300 and 400 cells/μL separately, which have been widely used and reported, especially 300 cells/μL and 2%. Moreover, based on the cut-offs of 300 cells/μL and 2%, subgroup analyses regarding region (Europe vs Asia vs North America vs Middle East), phase of COPD at baseline (stable vs exacerbation phase) and follow-up time (≤1 year vs >1 year) were conducted. We also performed the meta-regression to evaluate the effect of moderator variables (region, phase of COPD at baseline and follow-up time) on meta-analysis results. For sensitivity analysis, the influence of a single study on the overall pooled estimate was investigated by omitting one study in each turn. Publication bias was visually assessed with a funnel plot and evaluated by the Egger’s and Begg’s test [22]. P value <0.05 was considered statistically significant. Statistical analysis was performed using Stata 12.0 (Stata, College Station, TX, USA).
Results
Study selection
The initial search yielded 5963 records. Based on the title and abstract, 4141 were removed for duplicates and 1751 were excluded for irrelevant data or ineligible study design (review, meta-analysis or letter). The remaining 71 full-text articles were screened for eligibility and 50 were excluded because of non-English literature (n = 4), included asthma (n = 15), invalid grouping (n = 12) or no relative data (n = 19). Finally, 21 articles were included in the meta-analysis [10,11,23–41]. The selection process is shown in Fig 1.
Study characteristics and quality assessment
The characteristics of the 21 included studies are presented in Table 1. These studies were published between 2015 and 2022. The sample size ranged from 145 to 32693. Among these articles, 16 were cohort studies (13 retrospective [23–25,27,29–31,33–36,38,39], three prospective studies [10,37,41]), four were post-hoc analysis of RCTs [11,26,28,40] and only one was RCT [32]. Besides, 11 studies were conducted in Europe [10,11,25–28,32–36], six studies in Asia [29,37–41], two studies in the North America [24,31], and two studies in Middle East [23,30]. 15 studies [10,23–26,30,31,33–39,41] reported the outcome of moderate-severe exacerbation, defined as aggravation of respiratory symptoms that required treatment of systematic corticosteroids or/and antibiotics, hospitalization or visiting the emergency room. The remaining four studies did not specify the severity of exacerbation, which was defined as acute change of respiratory symptoms, warranting a change in therapy.
A total of 79868 participants were included in this meta-analysis. The mean age ranged from 63 to 77 years. The proportion of male subjects was between 41% and 96%. The mean FEV1% predicted of patients was above 30%, and more than 44.7% of them were receiving ICS-containing therapies.
Quality assessment of included studies are presented in S3 Table. The RCT described the generation of a randomized sequence, a double-blind design, and reported the numbers and reasons of withdrawal or dropout in detail, indicating a low risk of bias [32]. According to the NOS, 14 observational studies were considered at low risk of bias (scored ≥6) and 6 studies [24,25,31,32,34,38] were rated a score of 5.
Association between high blood eosinophils and risk of AECOPD according to different thresholds
A total of 17 studies [10,11,24,26–32,34–36,39–42] applied thresholds of absolute counts (200, 300 and 400 cells/μL) to define high blood eosinophils. As shown in Fig 2A, pooled analysis showed that high blood eosinophils were significantly associated with increased risk of future COPD exacerbation when using the thresholds of 300 cells/μL (RR 1.21, 95%CI 1.12–1.30, P <0.001, I2 = 68.1, 16 studies) and 400 cells/μL (RR 1.79, 95%CI 1.41–2.28, P <0.001, I2 = 0%, 3 studies). However, no significant association was observed when applying the cut-off of 200 cells/μL (RR 1.19, 95%CI 0.82–1.73, P = 0.366, I2 = 44.1%, 3 studies).
(A) High blood eosinophil was defined using the thresholds of 200, 300 and 400 cells/μL respectively. (B) High blood eosinophil was defined using the thresholds of 2%, 3% and 4% respectively. (Note: Song(A), participants using ICS/LABA during the study; Song(B), participants not using ICS/LABA during the study. Pavord (SCO40036), participants from the RCT SCO40036; Pavord (SCP30002), participants from the RCT SCP30002).
Besides, 11 studies [23,25–28,30–33,38,40] reported data on thresholds of percentages (2%, 3% and 4%). As shown in Fig 2B, pooled analysis revealed high blood eosinophils statistically significantly correlated with increased risk of AECOPD when applying the thresholds of 2% (RR 1.26, 95%CI 1.02–1.55, P = 0.030, I2 = 94.8%, 10 studies) and 4% (RR 1.44, 95%CI 1.05–1.96, P = 0.022, I2 = 83.1%, 4 studies), but not 3% (RR 1.18, 95%CI 0.94–1.49, P = 0.152, I2 = 85.9%, 4 studies), with apparent heterogeneity across studies.
Among studies reporting the outcome of moderate-severe exacerbation, the majority applied the thresholds of 300 cells/μL [10,24,26,30,31,34–37,41] and 2% [23,25,26,30,31,33,38]. As shown in Fig 3, elevated blood eosinophils were markedly correlated with increased risk of moderate-severe exacerbation when using 300 cells/μL (RR 1.30, 95%CI 1.16–1.45, P <0.001, I2 = 69.7%, 11 studies) and 2% (RR 1.33, 95%CI 1.02–1.75, P = 0.037, I2 = 95.5%, 7 studies) respectively, but also with apparent heterogeneity.
(A) High blood eosinophil was defined as ≥300 cells/μL. (B) High blood eosinophil was defined as ≥ 2%.
Subgroup analyses and meta-regression
Subgroup analyses using the thresholds of 300 cells/μL and 2% were shown in Table 2 and S1–S3 Figs. As results, the association between high blood eosinophils and risk of COPD exacerbation were inconsistent across different regions and follow-up time. Results on the threshold of 300 cells/μL appeared more stable than the 2%, which revealed that the association between high blood eosinophils and exacerbation risk was statistically significant in participants from Asia (RR 1.13, 95%CI 1.10–1.15, P = 0.025, I2 = 49.7%, 4 studies), Europe (RR 1.14, 95%CI 1.03–1.26, P = 0.009, I2 = 51.8%, 9 studies) or Middle East (RR 1.95, 95%CI 1.50–2.54, P <0.001, 1 study) (S1 Fig), whether with stable (RR 1.49, 95%CI 1.07–2.09, P = 0.018, I2 = 80.5%, 5 studies) or exacerbation phase (RR 1.15, 95%CI 1.09–1.20, P <0.001, I2 = 8.8%, 8 studies) at baseline (S2 Fig), or the follow-up time less (RR 1.23, 95%CI 1.13–1.34, P <0.001, I2 = 74.1%, 13 studies) or more than (RR 1.12, 95%CI 1.00–1.25, P = 0.043, I2 = 0.0%, 3 studies)1 year (S3 Fig). However, significant heterogeneity was also observed and the meta-regression suggested that region, phase of COPD at baseline and follow-up time did not markedly contributed to the heterogeneity (P>0.05) (S4 Table).
Sensitivity analysis and publication bias
Further exclusion of any single study did not materially alter the pooled RRs, whether using the cutoff of 300 cells/μL or 2% (S4 Fig). Based on the funnel plot and statistical tests, no significant publication bias was found with the cutoff of 300 cells/μL(Egger’s test, p = 0.099; Begg’s test, p = 0.115) (S5 Fig).
Discussion
This study conducted a comprehensive investigation to examine the association between high blood eosinophils and the risk of exacerbation in patients with COPD. The findings revealed that this association varied across different thresholds (200, 300, 400 cells/μL and 2%, 3%, 4%) and factors (including different regions, phases of COPD, and follow-up time). However, it was observed that high blood eosinophils (exceeding 300 cells/μL and 2%) may potentially predict the risk of moderate-to-severe exacerbation of COPD in specific subgroups.
Considering the burden of AECOPD, effective prevention strategies are urgently required. Further interpretation on the predictors or risk factors of AECOPD could optimize the disease prevention and control. Currently, although the number of self-reported previous exacerbation could help predict future risk, it is ineffective for most patients with uncertain history of exacerbation, for whom a specific biomarker is always needed. The potential of eosinophils has been suggested. As a part of leukocytes, eosinophil plays a prominent role in immune homeostasis and inflammatory diseases [42]. Zhu et al. revealed that Cysteinyl leukotriene 1 receptor protein, whose ligand was released by eosinophils, was apparently greater in COPD patients with severe exacerbation than those in stable phase [43]. The gene expression metric of Th2-high asthma was also elevated in patients with COPD, and further associated with decreased lung function, increased airway and blood eosinophils [44]. The eosinophil-associated phenotype of AECOPD was also indicated [7]. These suggested that eosinophil could play an important part in the development and progression of COPD. There is a potential link between elevated blood eosinophils and exacerbation of COPD. Exacerbations of chronic bronchitis are often accompanied by significant airway eosinophilia [45], characterized by the release of inflammatory mediators including interleukin-4 (IL-4), interleukin-5 (IL-5), and interleukin-13 (IL-13). These mediators can induce airway inflammation and remodeling, contributing to the deterioration of COPD [46]. Besides, blood eosinophils have been suggested as biomarkers for guiding ICS therapy. The debated association between high blood eosinophils and risk of COPD exacerbation has been reported, as cut-off value defining high blood eosinophils always controversial. The cut-off value could depend on the median count of blood eosinophils in patients with COPD, which also varied across subgroups [47]. Using different thresholds, we found that results on the 300 cells/μL appeared more stable than other thresholds and 300 cells/μL of blood eosinophil count was also the cut-off value recommended by the GOLD guideline when considering ICS therapy. In the IMPACT analysis, the magnitude of benefit of ICS-containing treatment in reducing moderate-severe exacerbation significantly increased when blood eosinophil count more than 300 cells/μL [48]. These findings may underscore potential value of this threshold in AECOPD.
Based on the threshold of 300 cells/μL, we found a 1.21 folds increase in the risk ratios of exacerbation and a 1.30 folds increase in risk of moderate-severe exacerbation in patients with high blood eosinophils. It is well known that moderate-severe exacerbation is frequently associated with bacterial infection. A recent study indicates that blood eosinophils count is positively linked with the percent of Firmicutes and streptococcus, which are the common pathogens of AECOPD [49]. The multi-omics analyses further proposed the airway host-microbe interactions achieved through inflammatory cells, including eosinophils [50]. These interactions may play key roles in the development of COPD. Meanwhile, when using the threshold of 300 cells/μL in subgroup analyses, similar mild association was revealed in participants from Asia or Europe, with stable or exacerbation phase, or with follow-up time less than one year. No significant correlation was observed in patients from North America or with follow-up time more than one year. These findings seem to be consistent with previous evidence. Blood eosinophil count has been reported to be higher in patients from North America than Asia. The NHANES 2007–2008 and NHANES 2009–2010 study revealed a median blood eosinophil count of 200 cell/μL [51], while the Nagahama study indicated a median count of 120 cells/μL among Japanese participants [52]. This might explain the opposite results between patients from Asia and North America in the present study. Additionally, the reproducibility of blood eosinophils ≥300 cells/μL in two years was reported lower than 20%, contrasting with the good reproducibility within one year [10], suggesting a good short-term stability of this cut-off value, which might explain the opposite findings between follow-up times (≤1 year vs >1 year). However, given the significant heterogeneity across studies and population-related variance of blood eosinophil counts, the mild association revealed in the present study needs to be interpreted with caution.
Studies on blood eosinophils and AECOPD have presented significant heterogeneity. Using the meta-regression, we found that different regions, phases of COPD at baseline and follow-up time were not the main sources of variance. Instead, we infer different thresholds of high blood eosinophils could contribute to the heterogeneity, based on the controversial results on these thresholds. Therefore, the larger and well-designed studies with distinct subgroups categorized by different thresholds are warranted.
This study has several limitations. First, only one RCT was included while others were observational studies. The limitations of observational study design may weaken the reliability of study results. Second, significant heterogeneity observed across studies and the limited number of studies in subgroup analyses may affect the robustness of study results. Third, given the English-language restriction in study searching, studies in non-English languages with negative results were not included. Thus, publication bias may exist and also weaken the robustness of our findings, although the Egger’s and Begg’s test revealed no significant bias. Fourth, other factors could influence the relationship between blood eosinophils and risk of AECOPD, such as smoking, history of exacerbations and ICS, which we failed to analyze because of limited data. To promote a better interpretation regarding this relationship, adjusting confounding by these factors is particularly important in future studies.
In conclusion, this study suggests that high blood eosinophil counts, particularly over 300 cells/μL or 2%, could serve as a prognostic indicator for moderate-to-severe exacerbations of COPD in specific subgroups. However, large sample-sized, prospective, and well-designed studies are required to validate the present findings.
Supporting information
S1 Table. Literature online search strategies.
https://doi.org/10.1371/journal.pone.0302318.s001
(DOCX)
S2 Table. Brief description of some excluded studies and the reasons for their exclusion.
https://doi.org/10.1371/journal.pone.0302318.s002
(DOCX)
S3 Table. Quality assessment of the included studies.
https://doi.org/10.1371/journal.pone.0302318.s003
(DOCX)
S4 Table. Results of regression analysis with 2% and 300 cells /μL threshold.
https://doi.org/10.1371/journal.pone.0302318.s004
(DOCX)
S1 Fig. Risk of COPD exacerbation in relation to high blood eosinophils across different regions, based on the thresholds of 300 cells/μL and 2%.
(A) High blood eosinophil was defined as ≥300 cells/μL. (B) High blood eosinophil was defined as ≥2%.
https://doi.org/10.1371/journal.pone.0302318.s005
(DOCX)
S2 Fig. Risk of COPD exacerbation in relation to high blood eosinophils in different phases of COPD at baseline, based on the thresholds of 300 cells/μL and 2%.
(A) High blood eosinophil was defined as ≥300 cells/μL. (B) High blood eosinophil was defined as ≥2%. (Note: The study of Adir (2018) included two subgroups, with AECOPD and stable COPD at baseline respectively).
https://doi.org/10.1371/journal.pone.0302318.s006
(DOCX)
S3 Fig. Risk of COPD exacerbation in relation to high blood eosinophils with different follow-up time, based on the thresholds of 300 cells/μL and 2%.
(A) High blood eosinophil was defined as ≥300 cells/μL. (B) High blood eosinophil was defined as ≥2%.
https://doi.org/10.1371/journal.pone.0302318.s007
(DOCX)
S4 Fig. Sensitivity analysis, based on the thresholds of 300 cells/μL (A) and 2% (B).
Further exclusion of any single study did not materially alter the pooled RRs.
https://doi.org/10.1371/journal.pone.0302318.s008
(DOCX)
S5 Fig. Publication bias, based on the threshold of 300 cells/μL.
(A) Funnel plot. (B) Egger’s publication bias plot.
https://doi.org/10.1371/journal.pone.0302318.s009
(DOCX)
References
- 1. Rabe KF, Watz H. Chronic obstructive pulmonary disease. Lancet (London, England). 2017;389(10082):1931–40. pmid:28513453
- 2.
World Health Organization. The top 10 causes of death, 2020. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death (accessed 20 March 2023).
- 3. MacDonald MI, Osadnik CR, Bulfin L, et al. Low and High Blood Eosinophil Counts as Biomarkers in Hospitalized Acute Exacerbations of COPD. Chest. 2019;156(1):92–100. pmid:30978330
- 4. Montagnani A, Mathieu G, Pomero F, et al. Hospitalization and mortality for acute exacerbation of chronic obstructive pulmonary disease (COPD): an Italian population-based study. European review for medical and pharmacological sciences. 2020;24(12):6899–907. pmid:32633383
- 5. Ko FW, Chan KP, Hui DS, et al. Acute exacerbation of COPD. Respirology (Carlton, Vic.). 2016;21(7):1152–65. pmid:27028990
- 6.
Global Initiative for Chronic Obstructive Lung Disease. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease, 2023. www.goldcopd.org.
- 7. Bafadhel M, McKenna S, Terry S, et al. Acute exacerbations of chronic obstructive pulmonary disease: identification of biologic clusters and their biomarkers. American journal of respiratory and critical care medicine. 2011;184(6):662–71. pmid:21680942
- 8. Vedel-Krogh S, Nielsen SF, Lange P, Vestbo J, Nordestgaard BG. Blood Eosinophils and Exacerbations in Chronic Obstructive Pulmonary Disease. The Copenhagen General Population Study. American journal of respiratory and critical care medicine. 2016;193(9):965–74. pmid:26641631
- 9. Yun JH, Lamb A, Chase R, et al. Blood eosinophil count thresholds and exacerbations in patients with chronic obstructive pulmonary disease. The Journal of allergy and clinical immunology. 2018;141(6):2037–47.e10. pmid:29709670
- 10. Casanova C, Celli BR, de-Torres JP, et al. Prevalence of persistent blood eosinophilia: relation to outcomes in patients with COPD. The European respiratory journal. 2017;50(5). pmid:29167301
- 11. Singh D, Wedzicha JA, Siddiqui S, et al. Blood eosinophils as a biomarker of future COPD exacerbation risk: pooled data from 11 clinical trials. Respiratory research. 2020;21(1):240. pmid:32943047
- 12. Ho J, He W, Chan MTV, et al. Eosinophilia and clinical outcome of chronic obstructive pulmonary disease: a meta-analysis. Scientific reports. 2017;7(1):13451. pmid:29044160
- 13. Liu T, Xiang ZJ, Hou XM, Chai JJ, Yang YL, Zhang XT. Blood eosinophil count-guided corticosteroid therapy and as a prognostic biomarker of exacerbations of chronic obstructive pulmonary disease: a systematic review and meta-analysis. Therapeutic advances in chronic disease. 2021;12:20406223211028768. pmid:34285789
- 14. Liu H, Xie Y, Huang Y, et al. The association between blood eosinophils and clinical outcome of acute exacerbations of chronic obstructive pulmonary disease: A systematic review and meta-analysis. Respiratory medicine. 2024;222:107501. pmid:38104787
- 15. Disantostefano RL, Hinds D, Van Le H, Barnes NC. Relationship between blood eosinophils and clinical characteristics in a cross-sectional study of a US population-based COPD cohort. Respiratory medicine. 2016;112:88–96. pmid:26872700
- 16. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical research ed.). 2021;372:n71. pmid:33782057
- 17. Nussbaumer-Streit B, Klerings I, Dobrescu AI, et al. Excluding non-English publications from evidence-syntheses did not change conclusions: a meta-epidemiological study. Journal of clinical epidemiology. 2020;118:42–54. pmid:31698064
- 18. Jadad AR, Moore RA, Carroll D, et al. Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials. 1996;17(1):1–12. pmid:8721797
- 19. Farag S, Tsang C, Murphy PN. Polyphenol supplementation and executive functioning in overweight and obese adults at risk of cognitive impairment: A systematic review and meta-analysis. PloS one. 2023;18(5):e0286143. pmid:37228106
- 20.
GA Wells BS, D O’Connell, J Peterson, V Welch, M Losos, P Tugwell. The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomized Studies in Meta-analysis. 2020.
- 21. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ (Clinical research ed.). 2003;327(7414):557–60. pmid:12958120
- 22. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ (Clinical research ed.). 1997;315(7109):629–34. pmid:9310563
- 23. Duman D, Aksoy E, Agca MC, et al. The utility of inflammatory markers to predict readmissions and mortality in COPD cases with or without eosinophilia. International journal of chronic obstructive pulmonary disease. 2015;10:2469–78. pmid:26648709
- 24. Hasegawa K, Camargo CA Jr.. Prevalence of blood eosinophilia in hospitalized patients with acute exacerbation of COPD. Respirology (Carlton, Vic.). 2016;21(4):761–4. pmid:26699685
- 25. Pavord ID, Lettis S, Locantore N, et al. Blood eosinophils and inhaled corticosteroid/long-acting beta-2 agonist efficacy in COPD. Thorax. 2016;71(2):118–25. pmid:26585525
- 26. Watz H, Tetzlaff K, Wouters EFM, et al. Blood eosinophil count and exacerbations in severe chronic obstructive pulmonary disease after withdrawal of inhaled corticosteroids: A post-hoc analysis of the WISDOM trial. The Lancet Respiratory Medicine. 2016;4(5):390–8. pmid:27066739
- 27. Prins HJ, Duijkers R, Lutter R, et al. Blood eosinophilia as a marker of early and late treatment failure in severe acute exacerbations of COPD. Respiratory medicine. 2017;131:118–24. pmid:28947018
- 28. Roche N, Chapman KR, Vogelmeier CF, et al. Blood Eosinophils and Response to Maintenance Chronic Obstructive Pulmonary Disease Treatment. Data from the FLAME Trial. American journal of respiratory and critical care medicine. 2017;195(9):1189–97. pmid:28278391
- 29. Song JH, Lee CH, Kim JW, et al. Clinical implications of blood eosinophil count in patients with non-asthma-COPD overlap syndrome COPD. International journal of chronic obstructive pulmonary disease. 2017;12:2455–64. pmid:28860740
- 30. Adir Y, Hakrush O, Shteinberg M, Schneer S, Agusti A. Circulating eosinophil levels do not predict severe exacerbations in COPD: a retrospective study. ERJ open research. 2018;4(3).
- 31. Belanger M, Couillard S, Courteau J, et al. Eosinophil counts in first COPD hospitalizations: a comparison of health service utilization. International journal of chronic obstructive pulmonary disease. 2018;13:3045–54. pmid:30319252
- 32. Chapman KR, Hurst JR, Frent SM, et al. Long-Term Triple Therapy De-escalation to Indacaterol/Glycopyrronium in Patients with Chronic Obstructive Pulmonary Disease (SUNSET): A Randomized, Double-Blind, Triple-Dummy Clinical Trial. American journal of respiratory and critical care medicine. 2018;198(3):329–39. pmid:29779416
- 33. Oshagbemi OA, Franssen FME, Braeken DCW, et al. Blood eosinophilia, use of inhaled corticosteroids, and risk of COPD exacerbations and mortality. Pharmacoepidemiology and drug safety. 2018;27(11):1191–9. pmid:30264901
- 34. Gonzalez-Barcala FJ, San-Jose ME, Nieto-Fontarigo JJ, et al. Blood eosinophils could be useful as a biomarker in chronic obstructive pulmonary disease exacerbations. International journal of clinical practice. 2019:e13423. pmid:31573721
- 35. Hakansson KEJ, Ulrik CS, Godtfredsen NS, et al. High suPAR and Low Blood Eosinophil Count are Risk Factors for Hospital Readmission and Mortality in Patients with COPD. International journal of chronic obstructive pulmonary disease. 2020;15:733–43. pmid:32308381
- 36. Jabarkhil A, Moberg M, Janner J, et al. Elevated blood eosinophils in acute COPD exacerbations: better short- and long-term prognosis. European clinical respiratory journal. 2020;7(1):1757274. pmid:32489532
- 37. Juthong S, Kaenmuang P. Association between blood eosinophils with exacerbation and patient-reported outcomes in chronic obstructive pulmonary disease patients in an endemic area for parasitic infections: a prospective study. Journal of thoracic disease. 2020;12(9):4868–76. pmid:33145060
- 38. Wu CW, Lan CC, Hsieh PC, Tzeng IS, Wu YK. Role of peripheral eosinophilia in acute exacerbation of chronic obstructive pulmonary disease. World journal of clinical cases. 2020;8(13):2727–37. pmid:32742983
- 39. Yu S, Zhang J, Fang Q, Tong Z. Blood Eosinophil Levels and Prognosis of Hospitalized Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease. The American journal of the medical sciences. 2021;362(1):56–62. pmid:33617785
- 40. Bradbury T, Di Tanna GL, Scaria A, et al. Blood Eosinophils in Chinese COPD Participants and Response to Treatment with Combination Low-Dose Theophylline and Prednisone: A Post-Hoc Analysis of the TASCS Trial. International journal of chronic obstructive pulmonary disease. 2022;17:273–82. pmid:35153479
- 41. Jo YS, Moon JY, Park YB, et al. Longitudinal changes in forced expiratory volume in 1 s in patients with eosinophilic chronic obstructive pulmonary disease. BMC pulmonary medicine. 2022;22(1):91. pmid:35296272
- 42. Valent P, Degenfeld-Schonburg L, Sadovnik I, et al. Eosinophils and eosinophil-associated disorders: immunological, clinical, and molecular complexity. Semin Immunopathol. 2021;43(3):423–38. pmid:34052871
- 43. Zhu J, Bandi V, Qiu S, et al. Cysteinyl leukotriene 1 receptor expression associated with bronchial inflammation in severe exacerbations of COPD. Chest. 2012;142(2):347–57. pmid:22871757
- 44. Christenson SA, Steiling K, van den Berge M, et al. Asthma-COPD overlap. Clinical relevance of genomic signatures of type 2 inflammation in chronic obstructive pulmonary disease. American journal of respiratory and critical care medicine. 2015;191(7):758–66. pmid:25611785
- 45. Saetta M, Di Stefano A, Maestrelli P, et al. Airway eosinophilia in chronic bronchitis during exacerbations. American journal of respiratory and critical care medicine. 1994;150(6 Pt 1):1646–52. pmid:7952628
- 46. Maspero J, Adir Y, Al-Ahmad M, et al. Type 2 inflammation in asthma and other airway diseases. ERJ open research. 2022;8(3). pmid:35923421
- 47. Benson VS, Hartl S, Barnes N, Galwey N, Van Dyke MK, Kwon N. Blood eosinophil counts in the general population and airways disease: a comprehensive review and meta-analysis. The European respiratory journal. 2021.
- 48. Pascoe S, Barnes N, Brusselle G, et al. Blood eosinophils and treatment response with triple and dual combination therapy in chronic obstructive pulmonary disease: analysis of the IMPACT trial. The Lancet. Respiratory medicine. 2019;7(9):745–56. pmid:31281061
- 49. Dicker AJ, Huang JTJ, Lonergan M, et al. The sputum microbiome, airway inflammation, and mortality in chronic obstructive pulmonary disease. The Journal of allergy and clinical immunology. 2021;147(1):158–67. pmid:32353489
- 50. Yan Z, Chen B, Yang Y, et al. Multi-omics analyses of airway host-microbe interactions in chronic obstructive pulmonary disease identify potential therapeutic interventions. Nature microbiology. 2022;7(9):1361–75. pmid:35995842
- 51. Malinovschi A, Fonseca JA, Jacinto T, Alving K, Janson C. Exhaled nitric oxide levels and blood eosinophil counts independently associate with wheeze and asthma events in National Health and Nutrition Examination Survey subjects. The Journal of allergy and clinical immunology. 2013;132(4):821–7.e1-5. pmid:23890753
- 52. Sunadome H, Sato S, Matsumoto H, et al. Similar distribution of peripheral blood eosinophil counts in European and East Asian populations from investigations of large-scale general population studies: the Nagahama Study. The European respiratory journal. 2021;57(1). pmid:33402375