Diagnostic value of fractional exhaled nitric oxide for asthma-chronic obstructive pulmonary disease overlap syndrome

Clinical Indicators for Asthma-COPD Overlap: A Systematic Review and Meta-Analysis

Background

Some clinical indicators have been reported to be useful in differentiating asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) from pure asthma/COPD, but the results were inconsistent. This study aims to evaluate the diagnostic value of these indicators for ACO.

Methods

Databases of PubMed, EMBASE, Ovid and Web of Science were retrieved. Pooled standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated in random-effects models.

Results

48 eligible studies were included. The pooled results indicated, compared with pure asthma, ACO patients had lower levels of forced expiratory volume in the first second (FEV₁)% predicted (pred) (SMD=−1.09, 95% CI −1.3 to −0.87), diffusion lung capacity for carbon monoxide (DLCO)% pred (SMD=−0.83, 95% CI −1.24 to −0.42), fractional exhaled nitric oxide (FeNO) (SMD=−0.23, 95% CI −0.36 to −0.11), and higher levels of induced sputum neutrophil (SMD = 0.51, 95% CI 0.21 to 0.81), circulating YKL-40 (SMD = 0.96, 95% CI 0.27 to 1.64). However, relative to COPD alone, ACO patients had higher levels of FEV₁% pred (SMD = 0.15, 95% CI 0.05 to 0.26), DLCO% pred (SMD = 0.38, 95% CI 0.16 to 0.6), FeNO (SMD = 0.59, 95% CI 0.40 to 0.78), serum total immunoglobulin (Ig)E (SMD = 0.42, 95% CI 0.1 to 0.75), blood eosinophil (SMD = 0.44, 95% CI 0.29 to 0.59), induced sputum eosinophil (SMD = 0.62, 95% CI 0.42 to 0.83), and lower levels of induced sputum neutrophil (SMD=−0.48, 95% CI −0.7 to −0.27), circulating YKL-40 (SMD=−1.09, 95% CI −1.92 to −0.26).

Conclusion

Compared with pure asthma/COPD, ACO patients have different levels of FEV₁% pred, DLCO% pred, FeNO, serum total IgE, blood eosinophil, induced sputum eosinophil/neutrophil, and circulating YKL-40, which could be helpful to establish a clinical diagnosis of ACO.

Diagnostic value of fractional exhaled nitric oxide in differentiating the asthma-COPD overlap from COPD: a systematic review and meta-analysis

BACKGROUND

Patients with asthma-COPD overlap (ACO) account for 15-20% of chronic obstructive pulmonary disease (COPD), and the incidence increases with age. Patients with ACO have worse outcomes without proper treatment than those with COPD alone. However, the current diagnostic criteria of ACO are mainly based on symptom features and lack of objective indicators. Recently, several studies have demonstrated that fractional exhaled nitric oxide (FeNO) was higher in ACO than in COPD alone. Thus, this study aims to determine the diagnostic value of FeNO in differentiating ACO from COPD and assisting clinical decision-making.

METHODS

We conducted searches in the databases including PubMed, Web of Science, Cochrane Library, and Embase to extract original studies.

RESULTS

In all, 10 studies involving 1335 participants were included in this meta-analysis. FeNO level was significantly higher in ACO patients than in patients with COPD alone (WMD = 11.15ppb, 95%CI = 9.01‒13.28; I² = 18.0%, p = 0.000). The sensitivity and specificity of FeNO in distinguishing ACO from COPD were both 0.71, and the area under the receiver-operating characteristic curve (AUC) was 0.76, indicating that FeNO has moderate diagnostic accuracy in differentiating ACO from COPD.

CONCLUSION

FeNO as an inflammatory biomarker is effective in differentiating ACO from COPD and assisting in clinical decision-making.

ACO (Asthma-COPD Overlap) Is Independent from COPD, a Case in Favor: A Systematic Review

Asthma and chronic obstructive pulmonary disease (COPD) are now recognized to be able to co-exist as asthma-COPD overlap (ACO). It is clinically relevant to evaluate whether patients with COPD concurrently have components of asthma in primary care. This is because: (i) ACO is a relatively common condition among asthma (over 40 years of age) or COPD irrespective of its diagnosis criteria; (ii) patients with ACO can have higher frequency of exacerbation and more rapid decline in lung function than those with asthma or COPD; and (iii) asthmatic features such as eosinophilic airway inflammation are promising indicators for prediction of inhaled corticosteroid-responsiveness in COPD. The aim of this review to evaluate diagnostic markers for ACO. We searched PubMed for articles related to ACO published until 2020. Articles associated with diagnostic biomarkers were included. We identified a total of 25 studies, some of which have revealed that a combination of biomarkers such as fractional exhaled nitric oxide and serum immunoglobulin E is useful to discern type 2 inflammation in the airways of COPD. Here, we review the current understanding of the clinical characteristics, biomarkers and molecular pathophysiology of ACO in the context of how ACO can be differentiated from COPD.

The Value of Inflammatory Biomarkers in Differentiating Asthma-COPD Overlap from COPD

Purpose

To evaluate the accuracy of inflammatory biomarkers in differentiating patients with asthma-COPD overlap (ACO) from those with COPD alone.

Methods

Clinical data of 134 patients with COPD and 48 patients with ACO admitted to the First Affiliated Hospital of Xi'an Jiaotong University from January 2016 to June 2019 were retrospectively analyzed. Receiver operating characteristic (ROC) curve analysis was performed to determine the best cut-off values of fractional exhaled nitric oxide (FeNO), blood eosinophil counts (EOS), and neutrophil to lymphocyte ratio (NLR) for differentiating between ACO and COPD alone. Spearman correlation analysis was conducted to evaluate the relationships between these inflammatory biomarkers and the forced expiratory volume in one second/prediction (FEV₁%pred).

Results

FeNO and EOS in the ACO patients were significantly higher than those in the COPD patients (FeNO: median 37.50 vs 24.50 ppb, P < 0.001; EOS: median 0.20 vs 0.10 ×10⁹/L, P = 0.004). FeNO was positively correlated with FEV₁%pred (r = 0.314, P = 0.030), while NLR was negatively correlated with FEV₁%pred (r = -0.372, P = 0.009) in patients with ACO. In addition, a positive correlation between FeNO and EOS was also found in ACO, especially in patients without history of inhaled corticosteroids (ICS) use (r = 0.682, P < 0.001). The optimal cut-off value of FeNO was 31.5 ppb (AUC = 0.758, 95% CI = 0.631-0.886) in patients with smoking history, with 70.0% sensitivity and 89.9% specificity for differentiating ACO from COPD. In patients without history of ICS use, the best cut-off value of FeNO was 39.5 ppb (AUC = 0.740, 95% CI = 0.610-0.870), with 58.3% sensitivity and 84.9% specificity. Among patients without history of ICS use and smoking, 27.5 ppb was optimal cut-off level for FeNO (AUC = 0.744, 95% CI = 0.579-0.908) to diagnose ACO, with 81.8% sensitivity and 60.7% specificity, and the sensitivity was improved to 91.7% when FeNO was combined with EOS.

Conclusion

The inflammatory biomarkers FeNO and EOS can be used as indicators for differentiating between ACO and COPD alone.

The Effects of Indoor Pollutants Exposure on Allergy and Lung Inflammation: An Activation State of Neutrophils and Eosinophils in Sputum

BACKGROUND

To explore the inflammation phenotypes following indoor pollutants exposure based on marker expression on eosinophils and neutrophils with the application of chemometric analysis approaches.

METHODS

A cross-sectional study was undertaken among secondary school students in eight suburban and urban schools in the district of Hulu Langat, Selangor, Malaysia. The survey was completed by 96 students at the age of 14 by using the International Study of Asthma and Allergies in Children (ISAAC) and European Community Respiratory Health Survey (ECRHS) questionnaires. The fractional exhaled nitric oxide (FeNO) was measured, and an allergic skin prick test and sputum induction were performed for all students. Induced sputum samples were analysed for the expression of CD11b, CD35, CD63, and CD66b on eosinophils and neutrophils by flow cytometry. The particulate matter (PM2.5 and PM10), NO2, CO2, and formaldehyde were measured inside the classrooms.

RESULTS

Chemometric and regression results have clustered the expression of CD63 with PM2.5, CD11b with NO2, CD66b with FeNO levels, and CO2 with eosinophils, with the prediction accuracy of the models being 71.88%, 76.04%, and 76.04%, respectively. Meanwhile, for neutrophils, the CD63 and CD66b clustering with PM2.5 and CD11b with FeNO levels showed a model prediction accuracy of 72.92% and 71.88%, respectively.

CONCLUSION

The findings indicated that the exposure to PM2.5 and NO2 was likely associated with the degranulation of eosinophils and neutrophils, following the activation mechanisms that led to the inflammatory reactions.

Nanomaterial-based gas sensors used for breath diagnosis

Gas-sensing applications commonly use nanomaterials (NMs) because of their unique physicochemical properties, including a high surface-to-volume ratio, enormous number of active sites, controllable morphology, and potential for miniaturisation.

Fractional Exhaled Nitric Oxide Testing: Diagnostic Utility in Asthma, Chronic Obstructive Pulmonary Disease, or Asthma-chronic Obstructive Pulmonary Disease Overlap Syndrome

Asthma and chronic obstructive pulmonary disease (COPD) can present as unique conditions or as a combination known as asthma-chronic obstructive pulmonary disease overlap syndrome (ACOS). These condition(s) can be categorized as obstructive conditions, causing inflammation of small airways leading to decrease airflow, mucus production, and bronchoconstriction. Asthma and COPD affect every age, gender, ethnicity, and socioeconomic status, thus increasing mortality and morbidity burden in our society. Fractional exhaled nitric oxide (FeNO) is an endogenous gaseous molecule which can be measured in the human breath test because of airway inflammation. It has been studied extensively as a marker of inflammation and has been incorporated into an algorithm for asthma management. The purpose of this study was to investigate whether FeNO testing can lead to a change in the diagnosis. A retrospective chart review of 95 patients with asthma, COPD, and ACOS was performed, and FeNO levels were recorded. Out of 95 patients, 36%, 24%, and 22% of the patients had an initial diagnosis of asthma, COPD, and ACOS, respectively. After the FeNO testing, the number of patients with the final diagnosis of asthma and ACOS increased, and COPD decreased. Our results support the utility of FeNO as a viable marker in diagnosing and managing complex cases of asthma, COPD, and ACOS.

Predictive and Diagnostic Value of Fractional Exhaled Nitric Oxide in Patients with Chronic Rhinosinusitis

Background

Fractional exhaled nitric oxide (FeNO) participates in the local defense of the upper respiratory tract. Abnormal FeNO level is directly related to the occurrence of nasal diseases. However, the clinical value of FeNO in the upper airway is limited, which greatly impedes the diagnosis and treatment of nasal diseases. Here, we assessed the level of FeNO and evaluated the diagnostic accuracy of FeNO for chronic rhinosinusitis.

Material/Methods

We enrolled 35 patients with confirmed nasal inflammation and 30 healthy subjects from December 2016 and June 2017. The FeNO level was measured using a fractional exhaled nitric oxide detector. The level of FeNO in patients with different clinicopathological factors was compared. The diagnostic potential of FeNO for chronic rhinosinusitis was evaluated by receiver operating characteristic (ROC) curve analysis.

Results

FeNO level was significantly lower in patients with nasal inflammation than in healthy subjects (P<0.05). For nasal inflammation diagnosis, FeNO had the highest area under the curve (AUC) at 0.760, with a sensitivity of 93.30% and a specificity of 68.60%. FeNO level was significantly downregulated in chronic rhinosinusitis patients relative to chronic rhinitis patients (P<0.05). FeNO had a good ability to discriminate between chronic rhinosinusitis patients and chronic rhinitis patients, with higher AUC, sensitivity, and specificity of 0.760, 93.30%, and 68.60%, respectively. However, FeNO levels were not significantly different between different histological types of chronic rhinosinusitis (P>0.05).

Conclusions

Our results show that FeNO is a useful marker for discriminating chronic rhinosinusitis, and has potential to provide valuable information in the early diagnosis of chronic rhinosinusitis.