Can we predict sputum eosinophilia from clinical assessment in patients referred to an adult asthma clinic?

Asthma Inflammatory Phenotypes: How Can We Distinguish Them?

BACKGROUND AND OBJECTIVES

induced sputum is used to assess different inflammatory phenotypes in asthma, but is not used routinely. We aimed to determine the proportion of inflammatory asthma phenotypes based on induced sputum, to find biomarkers that can discriminate between phenotypes, and to evaluate biomarkers in patients with and without biological therapy in different inflammatory asthma phenotypes.

MATERIALS AND METHODS

this cross-sectional study investigated clinical characteristics, asthma control tests, skin prick test, impulse oscillometry (IOS), spirometry, induced sputum, biomarkers (IgE, eosinophils, fractional exhaled nitric oxide (FeNO), serum periostin, IL-5, IL-6, IL-8, IL-17A, IL-33) in 80 asthmatics. A total of 17/80 patients were treated with biologics (10 with omalizumab, 7 with benralizumab).

RESULTS

a total of 31% of patients had eosinophilic asthma (EA), 30% had mixed granulocytic asthma (MGA), 24% had paucigranulocytic asthma (PGA), and 15% had neutrophilic asthma (NA). The difference was found in blood eosinophils (p = 0.002), the highest observed in EA. The cut-off ≥ 240/μL eosinophils, with 64% sensitivity and 72.7% specificity, identified EA (AUC = 0.743, p = 0.001). A higher IL-8 level was associated with NA (p = 0.025). In 63 non-biologic asthma group, eosinophils were higher in EA than in NA, MGA, and PGA (p = 0.012, p = 0.028, and p = 0.049, respectively). A higher IL-17A was associated with EA without biologics (p = 0.004). A significantly higher IL-5 was found in EA treated with biologics, in comparison with EA without biologics (p = 0.043). The number of leucocytes and neutrophils was higher in MGA without biologics (p = 0.049, p = 0.019), while IL-5, IL-6, and IL-8 levels were higher in MGA treated with biologics (p = 0.012, p = 0.032, p = 0.038, respectively).

CONCLUSIONS

EA and MGA were the most prevalent asthma phenotypes. Blood eosinophils can identify EA, both in patients with and without biologics. Apart from the clinical profile, a broad spectrum of biomarkers for assessing inflammatory phenotypes is necessary for an adequate therapy approach to patients with asthma.

Diagnostic accuracy of blood eosinophils in comparison to other common biomarkers for identifying sputum eosinophilia in patients with chronic cough

Background

Sputum eosinophilia is a treatable trait for chronic cough. It is currently not clear whether the blood eosinophil counts could be used to identify sputum eosinophilia in patients with chronic cough. This study aimed to evaluate the diagnostic accuracy of blood eosinophils in comparison to other common type 2 biomarkers for identifying sputum eosinophilia in patients with chronic cough.

Methods

In this prospective study, a total of 658 patients with chronic cough were enrolled. Induced-sputum test, routine blood test, total immunoglobulin E (TIgE), and fractional exhaled nitric oxide (FeNO) level were measured. The percentage of sputum eosinophils (Eos%) ≥ 2.5% was defined as sputum eosinophilia. The area under the curve (AUC) of blood eosinophil counts, TIgE, and FeNO alone or in combination for predicting sputum eosinophilia were analyzed.

Results

The AUC of blood eosinophil counts for predicting sputum eosinophilia in chronic cough patients was moderate [0.826 (0.767-0.885)], as compared to that of FeNO [0.784 (0.720-0.849), P = 0.280] and TIgE [0.686 (0.613-0.760), P = 0.001]. When combining blood eosinophil counts and FeNO for detecting sputum eosinophilia, a significantly larger AUC [0.868 (0.814-0.923), with a sensitivity of 84.2% and a specificity of 82.8%] was yielded, as compared to each single marker alone (all P < 0.05).

Conclusions

Blood eosinophil counts have a moderate diagnostic value for identifying sputum eosinophilia in patients with chronic cough, while a combination of blood eosinophil counts and FeNO measurement can provide additional predictive value.

Eosinophilic Asthma, Phenotypes-Endotypes and Current Biomarkers of Choice

Asthma phenotyping and endotyping are constantly evolving. Currently, several biologic agents have been developed towards a personalized approach to asthma management. This review will focus on different eosinophilic phenotypes and Th2-associated endotypes with eosinophilic inflammation. Additionally, airway remodeling is analyzed as a key feature of asthmatic eosinophilic endotypes. In addition, evidence of biomarkers is examined with a predictive value to identify patients with severe, uncontrolled asthma who may benefit from new treatment options. Finally, there will be a discussion on the results from clinical trials regarding severe eosinophilic asthma and how the inhibition of the eosinophilic pathway by targeted treatments has led to the reduction of recurrent exacerbations.

Characteristics of inflammatory phenotypes among patients with asthma: relationships of blood count parameters with sputum cellular phenotypes

BACKGROUND

There is a need to identify the asthma inflammatory phenotypes of patients to facilitate personalized asthma treatment. Sputum induction is time-consuming and requires expert clinical technique. This study aimed to assess the distribution and characteristics of asthma inflammatory phenotypes in Jilin Province, China; it also aimed to identify an easier method for characterization of an asthma phenotype, rather than sputum cellular analysis.

METHODS

In this study, 232 asthma patients underwent sputum induction following clinical assessment and blood collection. Inflammatory cell counts in sputum were used to classify asthma inflammatory phenotypes. Receiver operating characteristic curve and Spearman correlation coefficient analyses were used to identify correlations between clinical parameters.

RESULTS

Among the included patients, there had 52.1% paucigranulocytic, 38.4% eosinophilic, 4.3% neutrophilic, and 5.2% mixed granulocytic asthma phenotypes, respectively. In total, 129 (55.6%) patients had asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO); these patients had higher proportion of smokers, higher sputum neutrophil count, worse lung function, and worse asthma control, compared with patients who had asthma alone (p < 0.05). Sputum eosinophil/neutrophil counts were positively correlated with blood eosinophil/neutrophil counts (p < 0.01). To identify the presence of sputum eosinophil proportion ≥ 3%, optimal cut-off values for blood eosinophil count and fractional exhaled nitric oxide (FeNO) were 0.2 × 10⁹/L and 30.25 ppd (area under the curve (AUC) = 0.744; AUC = 0.653, p < 0.001). AUCs did not significantly differ between FeNO and blood eosinophil count (p = 0.162), but both exhibited poor specificity (57% and 49%, respectively). To identify the presence of sputum neutrophil proportion ≥ 61%, the optimal cut-off value for blood neutrophil proportion was 69.3% (AUC = 0.691, p = 0.0003); however, this exhibited poor sensitivity (50%).

CONCLUSIONS

Paucigranulocytic asthma was the most common phenotype, followed by eosinophilic asthma. Higher proportion of smokers, poor patient compliance, insufficient treatment, and poor asthma control may have been the main causes of high ACO proportion among patients in this study. Blood eosinophil/neutrophil counts exhibited poor specificity and sensitivity for prediction of airway eosinophilic/neutrophilic inflammation.

Blood Eosinophils and Clinical Outcome of Acute Exacerbations of Chronic Obstructive Pulmonary Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Numerous studies have shown the association between eosinophilia and clinical outcomes of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). But the evidences are lack of consensus.

OBJECTIVE

The aim of this meta-analysis was to conduct a pooled analysis of outcome comparing eosinophilic (EOS) AECOPD and non-EOS AECOPD patients.

METHODS

We included PubMed, EMBASE, Web of Science, and Cochrane databases up to 2020 to retrieve articles. Randomized controlled trials and quasi-experimental studies about patients with and without EOS AECOPD in terms of in-hospital mortality, length of hospital stay, comorbidities, forced expiratory volume in 1 s (FEV1), gender, and BMI were included preclinical studies, review articles, editorials, commentaries, conference abstracts, and book chapters were excluded. The methodologic assessment of studies was performed with the Newcastle-Ottawa Scale and Cochran scale. Comprehensive Rev Man 5 was used for the statistical analysis.

RESULTS

Twenty-one studies with 18,041 patients fulfilled the inclusion criteria and were used in this meta-analysis. Comparing to the non-EOS group, those with EOS AECOPD patients had a lower risk for in-hospital mortality (odds ratio (OR) = 0.59, 95% confidence interval [CI] 0.36-0.95, p = 0.03), shorter length of hospital stay (OR = -0.72, 95% CI -1.44 to -0.00, p = 0.05), better FEV1 (mean difference = 0.14, 95% CI 0.08-0.20, p < 0.00001), and a lower risk of arrhythmias (OR = 1.50, 95% CI 1.01-2.21, p = 0.04). In addition, the non-EOS group had a higher percentage of male (OR = 1.34, 95% CI 1.15-1.56, p = 0.0002) than EOS group. The rate of steroid use (OR = 0.82, 95% CI 0.47-1.42, p = 0.48) and BMI (mean difference = 0.43, 95% CI -0.18 to 1.05, p = 0.17] had no difference between 2 groups.

CONCLUSION

The results of our meta-analysis suggest that EOS AECOPD patients have a better clinical outcome than non-EOS AECOPD patients in terms of length of hospital stay, in-hospital mortality, FEV1, and risk of arrhythmias. In addition, the non-EOS AECOPD patients have higher percentage of male than EOS AECOPD patients.

Longitudinal Outcomes of Severe Asthma: Real-World Evidence of Multidimensional Analyses

BACKGROUND

There have been few studies assessing long-term outcomes of asthma based on regular follow-up data.

OBJECTIVE

We aimed to demonstrate clinical outcomes of asthma by multidimensional analyses of a long-term real-world database and a prediction model of severe asthma using machine learning.

METHODS

The database included 567 severe and 1337 nonsevere adult asthmatics, who had been monitored during a follow-up of up to 10 years. We evaluated longitudinal changes in eosinophilic inflammation, lung function, and the annual number of asthma exacerbations (AEs) using a linear mixed effects model. Least absolute shrinkage and selection operator logistic regression was used to develop a prediction model for severe asthma. Model performance was evaluated and validated.

RESULTS

Severe asthmatics had higher blood eosinophil (P = .02) and neutrophil (P < .001) counts at baseline than nonsevere asthmatics; blood eosinophil counts showed significantly slower declines in severe asthmatics than nonsevere asthmatics throughout the follow-up (P = .009). Severe asthmatics had a lower level of forced expiratory volume in 1 second (P < .001), which declined faster than nonsevere asthmatics (P = .033). Severe asthmatics showed a higher annual number of severe AEs than nonsevere asthmatics. The prediction model for severe asthma consisted of 17 variables, including novel biomarkers.

CONCLUSIONS

Severe asthma is a distinct phenotype of asthma with persistent eosinophilia, progressive lung function decline, and frequent severe AEs even on regular asthma medication. We suggest a useful prediction model of severe asthma for research and clinical purposes.

A high blood eosinophil count may be a risk factor for incident asthma in population at risk

BACKGROUND

Eosinophilia is considered to be associated with allergic disease and may predict asthma exacerbation. Eosinophils contribute to the pathophysiology and pathogenesis of asthma. However, studies on high blood eosinophil counts (BECs) and incident asthma remain scarce.

OBJECTIVE

To examine whether high BECs are positively associated with incident asthma in adults.

METHODS

Our study included 57975 participants aged from 20 to 79 years from the Shandong multi-center health check-up longitudinal study for Health Management. All patients with determined baseline BECs were ≥20 years old and free from asthma. We defined incident asthma as self-reported new-onset asthma occurring during the 10-year follow-up period. Multivariate modeling employed Poisson regression and Cox proportional hazards models to verify the association between BEC and incident asthma by adjusting demographics and some relevant comorbidities (rhinitis, nasal polyps, pneumonia, bronchitis, and chronic obstructive pulmonary disease).

RESULTS

A BEC ≥110 cells/μL was a risk factor for incident asthma (adjusted IRR = 1.62, 95% CI: 1.05-2.50, P = .028) in the Poisson regression. In the Cox proportional hazards model, the BEC cutoff point for incident asthma was also determined to be 110 cells/μL (HR = 1.59, 95% CI: 1.01-2.51, P = .045).

CONCLUSION

A high BEC is a risk factor for incident asthma, especially when the BEC exceeds 110 cells/μL. This suggests that adults with high BECs are more likely to develop asthma.

Eosinophilic asthma, according to a blood eosinophil criterion, is associated with disease severity and lack of control among underprivileged urban Brazilians

BACKGROUND

Asthma is a syndrome with multiple phenotypes. Peripheral blood eosinophil counts might be the ideal biomarker to identify subjects with eosinophilic asthma. It is available, inexpensive, and it is associated with eosinophilia in sputum.

OBJECTIVE

The aim of this study was to evaluate whether blood eosinophilia is associated with asthma severity and to evaluate whether blood eosinophilia is associated with lack of control of asthma symptoms and airway obstruction.

METHODS

Case control study. The cases were subjects recruited from a cohort of patients with severe asthma, in Salvador-BR, demanding continuous inhaled corticosteroids and LABA. There were two control groups: 1) subjects with mild/moderate asthma, 2) subjects with no asthma. Subjects enrolled in the study answered questionnaires, had their blood and stool samples collected, performed spirometry and SPT. We established a cutoff ≥ 260 cells/mm3 for blood eosinophilia.

RESULTS

We evaluated 544 subjects in the case group, 452 subjects with mild to moderate asthma and 450 subjects with no asthma. The subjects of the case group had higher odds of presenting the eosinophilic phenotype in comparison to subjects with mild to moderate asthma [OR 1.60 95CI(1.19-2.16)] and no asthma [OR 3.93; 95CI(2.90-5.33)]. The eosinophilic phenotype, according to blood count, is associated with uncontrolled asthma [OR 1.56; 95CI(1.06-2.28)], but it is not associated with airway obstruction [OR 0.87; 95CI(0.61-1.24)].

CONCLUSION

We conclude that the blood eosinophilia is a biomarker associated with asthma severity and poor symptom control, but we found no association with reduced lung function.

Blood eosinophils and inhaled corticosteroids in patients with COPD: systematic review and meta-analysis

Background

COPD is a highly heterogeneous disease. Potential biomarkers to identify patients with COPD who will derive the greatest benefit from inhaled corticosteroid (ICS) treatment are needed. Blood eosinophil count can serve as a predictive biomarker for the efficacy of ICS treatment. The aim of this systematic review and meta-analysis was to assess whether a blood eosinophil count of ≥2% in patients undergoing ICS therapy was associated with a greater reduction in COPD exacerbation rate and pneumonia incidence.

Materials and methods

An electronic search was performed using the keywords "COPD", "eosinophil", and "clinical trial" in the PubMed and EMBASE databases to retrieve articles, up to 2017, relevant to our focus. Data were extracted, and a meta-analysis was conducted using RevMan 5 (version 5.3.5).

Results

Five studies comprising 12,496 patients with moderate-to-very severe COPD were included. At baseline, 60% of the patients had ≥2% blood eosinophils. Our meta-analysis showed a 17% reduction in exacerbation of moderate/severe COPD in patients with ≥2% blood eosinophils undergoing ICS therapy compared to the non-ICS/ICS withdrawal/placebo group. The difference between the two types of treatment was significant (risk ratio [RR], 0.816; 95% CI, 0.67-0.99; P=0.03). Furthermore, the risk of pneumonia-related events was significantly increased in the subgroup with eosinophil count ≥2% undergoing ICS-containing treatments (RR, 1.969; 95% CI, 1.369-2.833; P<0.001). There was no significant difference in the subgroup with eosinophil count <2% (RR, 1.29; 95% CI, 0.888-1.879; P<0.181).

Conclusion

The results of our meta-analysis suggest that the 2% threshold for blood eosinophils could accurately predict ICS treatment response in patients with COPD, but increased the risk of pneumonia.

Associations between blood eosinophils and decline in lung function among adults with and without asthma

Eosinophilic inflammation and airway remodelling are characteristic features of asthma, but the association between them is unclear. We assessed associations between blood eosinophils and lung function decline in a population-based cohort of young adults.We used linear mixed models to analyse associations between blood eosinophils and spirometry at 21, 26, 32 and 38 years adjusting for sex, smoking, asthma and spirometry at age 18 years. We further analysed associations between mean eosinophil counts and changes in spirometry from ages 21 to 38 years.Higher eosinophils were associated with lower forced expiratory volume in 1 s (FEV₁)/forced vital capacity (FVC) ratios and lower FEV₁ % predicted values for both pre- and post-bronchodilator spirometry (all p-values ≤0.048). Although eosinophil counts were higher in participants with asthma, the associations between eosinophils and spirometry were similar among participants without asthma or wheeze. Participants with mean eosinophil counts >0.4×10⁹ cells·L^-1 between 21 and 38 years had greater declines in FEV₁/FVC ratios (difference 1.8%, 95% CI 0.7-2.9%; p=0.001) and FEV₁ values (difference 3.4% pred, 95% CI 1.5-5.4% pred); p=0.001) than those with lower counts.Blood eosinophils are associated with airflow obstruction and enhanced decline in lung function, independently of asthma and smoking. Eosinophilia is a risk factor for airflow obstruction even in those without symptoms.

Diagnosing eosinophilic asthma using a multivariate prediction model based on blood granulocyte responsiveness

BACKGROUND

The identification of inflammatory asthma phenotypes, using sputum analysis, has proven its value in diagnosis and disease monitoring. However due to technical limitations of sputum analysis, there is a strong need for fast and noninvasive diagnostics. This study included the activation state of eosinophils and neutrophils in peripheral blood to phenotype and monitor asthma.

OBJECTIVES

To (i) construct a multivariable model using the activation state of blood granulocytes, (ii) compare its diagnostic value with sputum eosinophilia as gold standard and (iii) validate the model in an independent patient cohort.

METHODS

Clinical parameters, activation of blood granulocytes and sputum characteristics were assessed in 115 adult patients with asthma (training cohort/Utrecht) and 34 patients (validation cohort/Oxford).

RESULTS

The combination of blood eosinophil count, fractional exhaled nitric oxide, Asthma Control Questionnaire, medication use, nasal polyposis, aspirin sensitivity and neutrophil/eosinophil responsiveness upon stimulation with formyl-methionyl-leucyl phenylalanine was found to identify sputum eosinophilia with 90.5% sensitivity and 91.5% specificity in the training cohort and with 77% sensitivity and 71% specificity in the validation cohort (relatively high percentage on oral corticosteroids [OCS]).

CONCLUSIONS

The proposed prediction model identifies eosinophilic asthma without the need for sputum induction. The model forms a noninvasive and externally validated test to assess eosinophilic asthma in patients not on OCS.

Effectiveness using higher inhaled corticosteroid dosage in patients with COPD by different blood eosinophilic counts

BACKGROUND

Blood eosinophil counts have been documented as a good biomarker for patients with chronic obstructive pulmonary disease (COPD) using inhaled corticosteroid (ICS) therapy. However, the effectiveness and safety of prescribing high or medium dose of ICS for patients with different eosinophil counts are unknown.

METHODS

A post hoc analysis of a previous prospective randomized study was performed for COPD patients using higher dose (HD: Fluticasone 1,000 μg/day) or medium dose (MD: Fluticasone 500 μg/day) of ICS combined with Salmeterol (100 μg/day). Patients were classified into two groups: those with high eosinophil counts (HE ≥3%) and those with low eosinophil counts (LE <3%). Lung function was evaluated with forced expiratory volume in 1 second, forced vital capacity, and COPD assessment test. Frequencies of acute exacerbation and pneumonia were also measured.

RESULTS

Two hundred and forty-eight patients were studied and classified into higher eosinophil (HE) (n=85, 34.3%) and lower eosinophil (LE) groups (n=163, 65.7%). The levels of forced expiratory volume in 1 second were significantly increased in patients of HE group treated with HD therapy, compared with the other groups (HE/HD: 125.9±27.2 mL vs HE/MD: 94.3±23.7 mL, vs LE/HD: 70.4±20.5 mL, vs LE/MD: 49.8±16.7 mL; P<0.05) at the end of the study. Quality of life (COPD assessment test) markedly improved in HE/HD group than in MD/LE group (HE/HD: 9±5 vs LE/MD: 16±7, P=0.02). The frequency of acute exacerbation was more decreased in HE/HD group patients, compared with that in LE/MD group (HE/HD: 13.5% vs LE/MD: 28.7%, P<0.01). Pneumonia incidence was similar in the treatment groups (HE/HD: 3.2%, HE/MD: 2.6%, LE/HD: 3.5%, LE/MD 2.8%; P=0.38).

CONCLUSION

The study results support using blood eosinophil counts as a biomarker of ICS response and show the benefits of greater improvement of lung function, quality of life, and decreased exacerbation frequency in COPD patients with blood eosinophil counts higher than 3%, especially treated with higher dose of ICS.

Peripheral blood eosinophils: a surrogate marker for airway eosinophilia in stable COPD

Introduction

Sputum eosinophilia occurs in approximately one-third of stable chronic obstructive pulmonary disease (COPD) patients and can predict exacerbation risk and response to corticosteroid treatments. Sputum induction, however, requires expertise, may not always be successful, and does not provide point-of-care results. Easily applicable diagnostic markers that can predict sputum eosinophilia in stable COPD patients have the potential to progress COPD management. This study investigated the correlation and predictive relationship between peripheral blood and sputum eosinophils. It also examined the repeatability of blood eosinophil counts.

Methods

Stable COPD patients (n=141) were classified as eosinophilic or noneosinophilic based on their sputum cell counts (≥3%), and a cross-sectional analysis was conducted comparing their demographics, clinical characteristics, and blood cell counts. Receiver operating characteristic curve analysis was used to assess the predictive ability of blood eosinophils for sputum eosinophilia. Intraclass correlation coefficient was used to examine the repeatability of blood eosinophil counts.

Results

Blood eosinophil counts were significantly higher in patients with sputum eosinophilia (n=45) compared to those without (0.3×10⁹/L vs 0.15×10⁹/L; P<0.0001). Blood eosinophils correlated with both the percentage (ρ=0.535; P<0.0001) and number of sputum eosinophils (ρ=0.473; P<0.0001). Absolute blood eosinophil count was predictive of sputum eosinophilia (area under the curve =0.76, 95% confidence interval [CI] =0.67–0.84; P<0.0001). At a threshold of ≥0.3×10⁹/L (specificity =76%, sensitivity =60%, and positive likelihood ratio =2.5), peripheral blood eosinophil counts enabled identification of the presence or absence of sputum eosinophilia in 71% of the cases. A threshold of ≥0.4×10⁹/L had similar classifying ability but better specificity (91.7%) and higher positive likelihood ratio (3.7). In contrast, ≥0.2×10⁹/L offered a better sensitivity (91.1%) for ruling out sputum eosinophilia. There was a good agreement between two measurements of blood eosinophil count over a median of 28 days (intraclass correlation coefficient =0.8; 95% CI =0.66–0.88; P<0.0001).

Conclusion

Peripheral blood eosinophil counts can help identify the presence or absence of sputum eosinophilia in stable COPD patients with a reasonable degree of accuracy.

Full blood count parameters for the detection of asthma inflammatory phenotypes

BACKGROUND

In asthma, the airway inflammatory phenotype influences clinical characteristics and treatment response. Although induced sputum is the gold standard test for phenotyping asthma, a more accessible method is needed for clinical practice.

OBJECTIVE

To investigate whether white blood cell counts and/or their derived ratios can predict sputum eosinophils or neutrophils in uncontrolled asthma.

METHODS

This cross-sectional study evaluated 164 treated but uncontrolled asthmatic patients with sputum induction and blood collection. Receiver-operating characteristic (ROC) curves were used to assess the relationship between blood and sputum parameters.

RESULTS

There was a significant positive relationship between blood eosinophil parameters and the percentage of sputum eosinophil count. A weak but significant correlation was found between sputum neutrophil percentage and blood neutrophil percentage (r = 0.219, P = 0.005). ROC curve analysis identified that blood eosinophil percentage count was the best predictor for eosinophilic asthma, with an area under the curve (AUC) of 0.907 (P < 0.001). The optimum cut-point for blood eosinophil percentage was 2.7%, and this yielded a sensitivity of 92.2% and a specificity of 75.8%. The absolute blood eosinophil count was also highly predictive with an AUC of 0.898 (P < 0.0001) at a blood eosinophil cut-off of 0.26 × 10(9) /L. The blood eosinophil/lymphocyte ratio (ELR) and eosinophil/neutrophil ratio (ENR) were increased in eosinophilic asthma, and the neutrophil/lymphocyte ratio (NLR) was increased in neutrophilic asthma. Neutrophilic asthma could also be detected by blood neutrophil percentages and NLR, but with less accuracy.

CONCLUSIONS AND CLINICAL RELEVANCE

Blood eosinophil counts and derived ratios (ELR and ENR) can accurately predict eosinophilic asthma in patients with persistent uncontrolled asthma despite treatment. Blood neutrophil parameters are poor surrogates for the proportion of sputum neutrophils. Blood counts may be a useful aid in the monitoring of uncontrolled asthma.

Diagnostic accuracy of minimally invasive markers for detection of airway eosinophilia in asthma: a systematic review and meta-analysis

BACKGROUND

Eosinophilic airway inflammation is associated with increased corticosteroid responsiveness in asthma, but direct airway sampling methods are invasive or laborious. Minimally invasive markers for airway eosinophilia could present an alternative method, but estimates of their accuracy vary.

METHODS

We did a systematic review and searched Medline, Embase, and PubMed for studies assessing the diagnostic accuracy of markers against a reference standard of induced sputum, bronchoalveolar lavage, or endobronchial biopsy in patients with asthma or suspected asthma (for inception to Aug 1, 2014). Unpublished results were obtained by contacting authors of studies that did not report on diagnostic accuracy, but had data from which estimates could be calculated. We assessed risk of bias with QUADAS-2. We used meta-analysis to produce summary estimates of accuracy.

FINDINGS

We included 32 studies: 24 in adults and eight in children. Of these, 26 (81%) showed risk of bias in at least one domain. In adults, three markers had extensively been investigated: fraction of exhaled nitric oxide (FeNO) (17 studies; 3216 patients; summary area under the receiver operator curve [AUC] 0·75 [95% CI 0·72-0·78]); blood eosinophils (14 studies; 2405 patients; 0·78 [0·74-0·82]); total IgE (seven studies; 942 patients; 0·65 [0·61-0·69]). In children, only FeNO (six studies; 349 patients; summary AUC 0·81 [0·72-0·89]) and blood eosinophils (three studies; 192 patients; 0·78 [0·71-0·85]) had been investigated in more than one study. Induced sputum was most frequently used as the reference standard. Summary estimates of sensitivity and specificity in detecting sputum eosinophils of 3% or more in adults were: 0·66 (0·57-0·75) and 0·76 (0·65-0·85) for FeNO; 0·71 (0·65-0·76) and 0·77 (0·70-0·83) for blood eosinophils; and 0·64 (0·42-0·81) and 0·71 (0·42-0·89) for IgE.

INTERPRETATION

FeNO, blood eosinophils, and IgE have moderate diagnostic accuracy. Their use as a single surrogate marker for airway eosinophilia in patients with asthma will lead to a substantial number of false positives or false negatives.

FUNDING

None.

Inhaled corticosteroids in COPD: the clinical evidence

In this article, we focus on the scientific evidence from randomised trials supporting treatment with inhaled corticosteroids (ICS) in chronic obstructive pulmonary disease (COPD), including treatment with combinations of long-acting β-agonist (LABA) bronchodilators and ICS. Our emphasis is on the methodological strengths and limitations that guide the conclusions that may be drawn. The evidence of benefit of ICS and, therefore, of the LABA/ICS combinations in COPD is limited by major methodological problems. From the data reviewed herein, we conclude that there is no survival benefit independent of the effect of long-acting bronchodilation and no effect on FEV1 decline, and that the possible benefit on reducing severe exacerbations is unclear. Our interpretation of the data is that there are substantial adverse effects from the use of ICS in patients with COPD, most notably severe pneumonia resulting in excess deaths. Currently, the most reliable predictor of response to ICS in COPD is the presence of eosinophilic inflammation in the sputum. There is an urgent need for better markers of benefit and risk that can be tested in randomised trials for use in routine specialist practice. Given the overall safety and effectiveness of long-acting bronchodilators in subjects without an asthma component to their COPD, we believe use of such agents without an associated ICS should be favoured.

High blood eosinophil count is associated with more frequent asthma attacks in asthma patients

BACKGROUND

The clinical importance of eosinophils in asthma has been shown by the observation of frequent exacerbation in patients with high sputum eosinophil counts and a corresponding decrease in exacerbations when anti-inflammatory therapy was adjusted to maintain low sputum eosinophil percentages. However, less is known of the relation between blood eosinophilia and asthma exacerbation.

OBJECTIVE

To examine whether patients with asthma and a higher blood eosinophil count have more asthma attacks than those with a lower count.

METHODS

The authors analyzed data from the National Health and Nutrition Examination Survey, an annual cross-sectional survey of the US general population. Patients with asthma and asthma attacks were identified based on participants' self-report or parental report. A high blood eosinophil count was defined using 200, 300, or 400 cells/μL as cutoffs. The primary analysis used data from 2001 through 2010 after adjusting for demographic variables, obesity, smoking, neutrophil level, and past treatment for wheezing. A secondary analysis used data from 2007 through 2010 and included recent treatment for asthma and fraction of exhaled nitric oxide level as additional adjustment variables.

RESULTS

In survey years 2001 through 2010, 3,162 patients with asthma had blood eosinophil data and approximately half (54% of children and 52% of adults) reported an asthma attack in the previous year. In the primary analysis, higher blood eosinophil counts were associated with more asthma attacks in children but not in adults. The secondary analysis suggested an association in both children and adults.

CONCLUSION

Patients with asthma with higher blood eosinophil counts experienced more asthma attacks than those with lower eosinophil counts.

Biomarker surrogates do not accurately predict sputum eosinophil and neutrophil percentages in asthmatic subjects

BACKGROUND

Sputum eosinophil percentages are a strong predictor of airway inflammation and exacerbations and aid asthma management, whereas sputum neutrophil percentages indicate a different severe asthma phenotype that is potentially less responsive to TH2-targeted therapy. Variables, such as blood eosinophil counts, total IgE levels, fraction of exhaled nitric oxide (Feno) levels, or FEV1 percent predicted, might predict airway eosinophil percentages, whereas age, FEV1 percent predicted, or blood neutrophil counts might predict sputum neutrophil percentages. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway eosinophil and neutrophil percentages either individually or combined is not established.

OBJECTIVES

We sought to determine whether blood eosinophil counts, Feno levels, and IgE levels accurately predict sputum eosinophil percentages and whether age, FEV1 percent predicted, and blood neutrophil counts accurately predict sputum neutrophil percentages.

METHODS

Subjects in the Wake Forest Severe Asthma Research Program (n = 328) were characterized by blood and sputum cell counts, health care use, lung function, Feno levels, and IgE levels. Multiple analytic techniques were used.

RESULTS

Despite significant association with sputum eosinophil percentages, blood eosinophil counts, Feno levels, and total IgE levels did not accurately predict sputum eosinophil percentages, and combinations of these variables did not improve prediction. Age, FEV1 percent predicted, and blood neutrophil counts were similarly unsatisfactory for the prediction of sputum neutrophil percentages. Factor analysis and stepwise selection found Feno levels, IgE levels, and FEV1 percent predicted, but not blood eosinophil counts, correctly predicted 69% of sputum eosinophil percentages of less than 2% or 2% and greater. Likewise, age, asthma duration, and blood neutrophil counts correctly predicted 64% of sputum neutrophil percentages of less than 40% or 40% and greater. A model to predict both sputum eosinophil and neutrophil percentages accurately assigned only 41% of samples.

CONCLUSION

Despite statistically significant associations, Feno levels, IgE levels, blood eosinophil and neutrophil counts, FEV1 percent predicted, and age are poor surrogates, both separately and combined, for accurately predicting sputum eosinophil and neutrophil percentages.

Distribution of sputum cellular phenotype in a large asthma cohort: predicting factors for eosinophilic vs neutrophilic inflammation

Background

Phenotyping asthma according to airway inflammation allows identification of responders to targeted therapy. Induced sputum is technically demanding. We aimed to identify predictors of sputum inflammatory phenotypes according to easily available clinical characteristics.

Methods

This retrospective study was conducted in 508 asthmatics with successful sputum induction recruited from the University Asthma Clinic of Liege. Receiver-operating characteristic (ROC) curve and multiple logistic regression analysis were used to assess the relationship between sputum eosinophil or neutrophil count and a set of covariates. Equations predicting sputum eosinophils and neutrophils were then validated in an independent group of asthmatics.

Results

Eosinophilic (≥3%) and neutrophilic (≥76%) airway inflammation were observed in 46% and 18% of patients respectively. Predictors of sputum eosinophilia ≥3% were high blood eosinophils, FE_NO and IgE level and low FEV₁/FVC. The derived equation was validated with a Cohen’s kappa coefficient of 0.59 (p < 0.0001). ROC curves showed a cut-off value of 220/mm³ (AUC = 0.79, p < 0.0001) or 3% (AUC = 0.81, p < 0.0001) for blood eosinophils to identify sputum eosinophilia ≥3%. Independent predictors of sputum neutrophilia were advanced age and high FRC but not blood neutrophil count.

Conclusion

Eosinophilic and paucigranulocytic asthma are the dominant inflammatory phenotypes. Blood eosinophils provide a practical alternative to predict sputum eosinophilia but sputum neutrophil count is poorly related to blood neutrophils.

IL-13 in asthma and allergic disease: asthma phenotypes and targeted therapies

Decades of research in animal models have provided abundant evidence to show that IL-13 is a key T(H)2 cytokine that directs many of the important features of airway inflammation and remodeling in patients with allergic asthma. Several promising focused therapies for asthma that target the IL-13/IL-4/signal transducer and activator of transcription 6 pathway are in development, including anti-IL-13 mAbs and IL-4 receptor antagonists. The efficacy of these new potential asthma therapies depends on the responsiveness of patients. However, an understanding of how IL-13-directed therapies might benefit asthmatic patients is confounded by the complex heterogeneity of the disease. Recent efforts to classify subphenotypes of asthma have focused on sputum cellular inflammation profiles, as well as cluster analyses of clinical variables and molecular and genetic signatures. Researchers and clinicians can now evaluate biomarkers of T(H)2-driven airway inflammation in asthmatic patients, such as serum IgE levels, sputum eosinophil counts, fraction of exhaled nitric oxide levels, and serum periostin levels, to aid decision making in clinical trials and drug development and to identify subsets of patients who might benefit from therapies. Although it is unlikely that these therapies will benefit all asthmatic patients with this heterogeneous disease, advances in understanding asthma subphenotypes in relation to clinical variables and T(H)2 cytokine responses offer the opportunity to improve the efficacy and safety of proposed therapies for asthma.

Moderate accuracy of peripheral eosinophil count for predicting eosinophilic phenotype in steroid-naïve non-atopic adult asthmatics

BACKGROUND AND AIM

Eosinophilic phenotype, sputum eosinophil count ≥3%, of asthma is a valuable clinical parameter. However, measurement of sputum inflammatory cells is time-consuming and requires specialized personnel. A simpler surrogate, such as peripheral eosinophil count, would be beneficial. The aim of this study was to assess the value of peripheral eosinophil count for predicting the eosinophilic phenotype of adult asthmatics.

MATERIALS AND METHODS

This retrospective study was conducted in 192 adult asthmatics. Sputum and venous blood were collected at the same visit and analyzed for cell differential. Receiver-operating characteristic (ROC) curve analysis was used to assess the relationship between eosinophilic phenotype and peripheral eosinophil count.

RESULTS

Peripheral eosinophil count, derived from the ROC curve, of more than 210 cells/mm(3) yielded 67.7% sensitivity and 66.2% specificity [area under the curve (AUC)=0.698, p=0.0001] for identifying the eosinophilic phenotype in the total patients. Multiple regression analysis revealed that steroid treatment and atopy significantly influenced the peripheral eosinophil count. Within the steroid-naïve subgroup, a peripheral eosinophil count of >190 cells/mm(3) yielded 76.3% sensitivity and 67.4% specificity (AUC=0.730, p<0.0001) for identifying eosinophilic phenotype, while in the steroid treated subgroup, the AUC was 0.554 (p=0.4985). Within the steroid-naïve non-atopic subgroup, a peripheral eosinophil count of >190 cells/mm(3) yielded 73.1% sensitivity and 79.3% specificity (AUC=0.809, p=0.0001) for identifying the eosinophilic phenotype, while in the steroid-naïve atopic subgroup, the AUC was 0.588 (p=0.2723).

CONCLUSION

Peripheral eosinophil count is able to identify the presence of eosinophilic phenotype in steroid-naïve non-atopic adult asthmatics with moderate accuracy.