Skip to main content
Download PDF

Airway inflammation, bronchial hyperresponsiveness, and anti-asthma therapy responses in cough variant asthma and classic asthma with FEV1% ≥80% predicted

BMC Pulmonary Medicine volume 25, Article number: 166 (2025) Cite this article

Abstract

Objective

To explore the differentiation of airway inflammation, bronchial hyperresponsiveness and anti-asthma therapy responses between the cough variant asthma (CVA) and classic asthma (CA) patients with FEV1% ≥80% predicted.

Methods

In the first monocentre retrospective cross-sectional study, 402 patients with suspicion of CA and 544 patients with chronic cough were enrolled. Further prospective monocentre study was conducted and 66 patients of suspected asthma with negative bronchial dilation test (BDT) but positive bronchial challenge (BCT) test were enrolled and followed up for 4 weeks.

Results

CA patients had higher fractional exhaled nitric oxide (FENO) values than CVA patients (36.0 ppb vs. 24.0 ppb, p < 0.0001). The predictive value of FENO for positive BCT was significantly lower in chronic cough patients compared to those with suspicion of CA (AUC = 0.603 vs. 0.728). Following four weeks anti-asthma therapy, both the CVA and CA groups showed significant improvement in both the large and small airway function and symptom relief. There was no significant difference between the respective groups. The two most valuable spirometric variables for predicting a positive response to anti-asthma treatment were the improvements of FEV1 (ΔFEV1, cut-off values = 90 ml for CA and 110 ml for CVA) and FEV1% (ΔFEV1%, cut-off values = 3.49% for CA and 2.59% for CVA) after BDT in baseline of CA and CVA patients, respectively.

Conclusion

Patients with CVA exhibited lower levels of airway eosinophilic inflammation compared to those with mild CA. Most patients with mild CA and CVA could benefit promptly from anti-asthma treatment. Additionally, an improvement in FEV1 and FEV1% during BDT can potentially predict positive responses to anti-asthma therapy in both groups.

Peer Review reports

Introduction

Mild classic asthma (CA) is the most prevalent type of asthma and typically exhibits a normal forced expiratory volume in one second (FEV1), affecting around 50–75% of patients with CA [8]. Unfortunately, the mild symptoms and near-normal FEV1 levels associated with mild asthma create substantial diagnostic challenges in clinical practice [18].

Cough-variant asthma (CVA), a distinct phenotype presenting with chronic cough as the cardinal symptom, shares similar diagnostic dilemmas despite its association with bronchial hyperreactivity (BHR) [4, 19, 23]. However, it is still unclear regarding phenotypic differentiation between CA and CVA in patients with FEV1% ≥80% predicted, particularly in airway inflammation, large- and small-airway function, bronchial hyperresponsiveness, and anti-asthma therapy responsiveness.

Currently, BHR is used to detect variable expiratory airflow limitation of asthma, which is often reflected by the bronchial challenge test (BCT) [9]. However, as BCT is time-consuming, expensive, and carries bronchospasm risk, it is poorly applied in all hospitals, especially in primary hospitals [26]. Furthermore, for CA and CVA patients with FEV1 ≥ 80% predicted, due to mild and atypical symptoms, primary hospitals are often the first choice [5]. Because of the limited diagnostic utility of BCT test, many CA or CVA patients with FEV1% ≥ 80% predicted were undiagnosed and untreated. As such, it is imperative to identify cost-effective, less hazardous, and straightforward approaches to evaluate BHR at the earliest, whether it be singularly or jointly.

Studies have shown that forced expiratory flow between 25% and 75% (MMEF), forced expiratory flow at 50% of forced vital capacity (MEF50), and forced expiratory flow at 75% of forced vital capacity (MEF25) are linked to the functional evaluation of small airway and asthma exacerbations [21, 36, 37].

Fractional exhaled nitric oxide (FENO) is a non-invasive and well-accepted biomarker of type 2 (T2) airway inflammation [22, 29]. FENO levels increase in asthma and correlate with eosinophilic inflammation [22]. Our previous investigation discovered that CVA patients exhibited elevated FENO levels, increased EOS% in blood, and reduced MMEF [1]. The combination of FENO and either MEF50 or MMEF can be used to predict BHR in asthmatic patients with normal FEV1 [2]. However, the differences in airway inflammation characteristics and large/small airway function, along with the predictive values of such combined parameters in predicting BHR of CA and CVA, are still inconclusive, especially for asthmatic populations with FEV1 ≥ 80% predicted.

Early initiation of long-term inhaled corticosteroids (ICS) after the onset of asthma is beneficial in enhancing lung function and reducing BHR [10, 11]. The Global Initiative for Asthma (GINA) guideline recommends a diagnostic criterion for asthma as an increase in FEV1 greater than 200 mL and more than 12% following anti-asthma therapy for a duration of one to three months [14]. In our previous study, following four weeks of anti-asthma therapy, 54.9% of suspected CA patients achieved an improvement of FEV1 > 200 mL [16]. However, there is a dearth of evidence verifying which patients can benefit from diagnostic treatment. Consequently, presenting an efficient method to predict the response to anti-asthma therapy is necessary.

The aim of this study was to examine the differences in the function of central and small airways, BHR, FENO, and EOS between CVA and CA patients with FEV1 ≥ 80% predicted. In addition, we intended to compare the predictive values of small airway function variables and FENO on BHR. The secondary objective was to investigate the differences and predictive value of the response to anti-asthma therapy between CVA and CA with FEV1 ≥ 80% predicted.

Methods

Participants and study design

Part I

This monocenter retrospective cohort study was approved by the Institutional Review Board (no. [2020]30) and a waiver of informed consent was given for our study (no. 2017KY159). We included 544 patients with chronic cough who fulfilled the eligibility criteria [24], including age range of 18–75 years, normal chest CT results, and the presence of chronic cough as the main or solitary symptom for at least 8 weeks, and FEV1% ≥ 80% predicted. We also enrolled 402 individuals with suspected classic asthma who fulfilled the same eligibility requirements as the chronic cough group, with the addition of variable respiratory symptoms including wheezing, chest tightness, and shortness of breath, with or without cough.

All patients had a detailed medical history (including allergic rhinitis and smoking history records), physical examination, and anti-asthmatic therapy responses recorded in a standardized outpatient electronic medical record system. All patients underwent spirometry, BCT, and FENO measurements.

The exclusion criteria were as follows: current smoking or > 10 pack-year smoking history; recent respiratory infection (≤ 8 weeks) or abnormal HRCT scan; concomitant severe systemic disorders; COPD/asthma-COPD overlap; chronic rhinosinusitis with nasal polyps (CRSwNP, confirmed by paranasal sinus CT); gastroesophageal reflux disease (GERD) with typical reflux symptoms; recent (≤ 4 weeks) use of montelukast, long-acting β2-agonists (LABA), theophylline, anticholinergic agents, or inhaled or oral corticosteroids. Pregnant subjects were also excluded.

Based on the BCT results, suspected classic asthma patients and chronic cough patients were grouped as follows: CVA group vs. BCT (-) group; CA group vs. BCT (-) group.

Part II

Another monocenter prospective study was approved by the Institutional Review Board (no. [2020]30) and registered on chictr.org.cn (No. ChiCTR2000029065). Informed consent was obtained for all subjects. FENO was the main outcome index observed in this study. The difference between the test group and the control group was 15.5 ppb, and the standard deviation was 19.0 ppb. Set alpha = 0.05 on both sides, the degree of assurance (1-β) was 0.9, and the sample size ratio of the two groups was 1:1. The sample size of the CA group and CVA group was both 32 cases calculated by R language. Considering the 10% loss of follow-up rate, at least 35 cases in each group are ultimately required, with a total sample size of at least 70 cases.

A total of 118 participants were consecutively recruited via the Pulmonary Outpatient Clinic of Shanghai General Hospital (Shanghai, China) from April 1, 2020, to January 30, 2021. Patients with negative bronchodilation test (BDT) were included in this study, and the other inclusion criteria were the same as those in Part I. Correspondingly, the exclusion criteria were also those described in Part I.

  • Patients who had negative BDT but had a high risk of asthma were performed asthma control test (ACT), or cough evaluation test (CET) before subjecting to BCT on the second day between 8:00–10:00 am. From the initial cohort of 118 participants, 52 demonstrating negative BDT and BCT results were excluded. The remaining 66 patients (31 CA and 35 CVA) meeting FEV1 ≥ 80% predicted, BCT-positive, and BDT-negative) underwent a standardized 4-week ICS/LABA regimen using budesonide/formoterol (160/4.5 µg per actuation, Symbicort Turbuhaler™, AstraZeneca) administered twice daily. After four weeks of treatment, follow-up measures including spirometry, ACT, or CET were performed at the same time as the initial visit (8:00–10:00 am). To ensure protocol compliance, systematic weekly monitoring (including symptom recovery time) was conducted via telephone consultations and WeChat-based communication (a widely used Chinese social media platform). It was defined as the duration from treatment initiation to improvement of symptoms, where symptom advancement was confirmed through a decrease in ACT score or an increase in CET score. Following 4-week ICS/LABA therapy, patients were stratified by spirometric response into three groups: (1) improvement-FEV1 > 200 mL and improvement-FEV1% >12%; (2) improvement-FEV1 > 200 mL and improvement-FEV1% ≤ 12%; (3) improvement-FEV1 < 200 mL and improvement-FEV1% < 12% (Among the 66 patients analyzed, none demonstrated concurrent spirometric improvements of FEV1 < 200 mL with FEV1% ≥12%).

Spirometry, FENO, IOS measurements, BDT, BCT, peripheral blood tests, the assessment of asthma control, cough evaluation, and symptom improvement were performed in accordance with guidelines. Details on the above measurements are provided in Supplementary Methods.

Symptom improvement was defined as an improvement of ACT or CET (∆ACT or ∆CET) of 3 or greater from baseline to 4 weeks of treatment [32].

Small-airway dysfunction (SAD) was defined as the presence of two measurements, MEF50, MEF25 or MMEF, with values lower than 65%.

∆FEV1 and ∆FEV1% indicate large airway function improvement in BDT at baseline and ∆MEF25, ∆MEF50 and ∆MMEF indicate small airway function improvement in BDT at baseline.

A positive anti-asthma treatment was defined as improved symptoms and an increase of more than 200 mL in FEV1 after ICS/LABA treatment.

Statistical analysis

Analysis was conducted with GraphPad Prism version 9.0 (GraphPad Software, San Diego, CA, USA). Descriptive statistics were used to present baseline data. The Kolmogorov-Smirnov test was applied to verify the normality of the distribution. The mean and standard deviation (SD) were used to indicate the normally distributed data, while the median and interquartile range (IQR) were used to indicate non-normally distributed data. Independent samples were compared using either the Student’s t-test (2-tailed) or Mann-Whitney U test. Additionally, count data were expressed as percentages, and between-group comparisons were executed using the chi-squared test (χ2).

The performance of each variable in predicting the outcome was assessed by measuring its area under the receiver-operating characteristic (ROC) curve. The resulting AUC of multiple logistic models of the 2 variables was used as a measure of the joint prediction performance. The Delong test was used to determine whether the multiple logistic models would significantly improve the prediction performance. We set the threshold for statistical significance at p < 0.05 for all analyses conducted.

Results

Part I

Baseline characteristics

Of all 946 adults with FEV1% ≥ 80% predicted, 544 patients were suspected CVA patients (278 BCT-positive and 266 BCT-negative) and 402 patients were suspected CA patients (202 BCT-positive and 200 BCT-negative). There were no significant differences in age, height, weight, body mass index (BMI), smoking history, and allergic rhinitis in the CA with FEV1 ≥ 80% predicted vs. BCT (-) groups, and CVA vs. BCT (-) groups (Table S1). Most demographic data and clinical features did not differ between the CA and CVA groups at baseline (Table 1).

Table 1 Demographic data, spirometric variables, and values for FENO and peripheral eosinophils of patients with positive or negative bronchial provocation tests
Full size table

Compared with the BCT (-) group, FEV1 (%pred), FEV1/FVC, and PEF (%pred) were lower in the CA group (p < 0.0001 respectively, Table 1), although still within the normal range. As expected, MEF50 (%pred), MEF25 (%pred), and MMEF (%pred) in the CA group were lower than those in BCT (-) group (p < 0.0001 for all comparisons, Table 1). Similarly, a higher percentage of small airway dysfunction was found in the CA group (46.04%), compared with the BCT (-) group (13.0%) (p < 0.0001, Table 1). FENO was significantly elevated in the CA group compared with the BCT (-) group (p < 0.0001, Table 1). EOS% in peripheral blood in the CA group was higher than that in the BCT (-) group (p < 0.0001, Table 1).

Lower FEV1/FVC, PEF (%pred), MEF50 (%pred), MEF25 (%pred), MMEF (%pred), and a higher ratio of small airway dysfunction were observed in the CVA group compared with the BCT (-) group (p < 0.001 for all). Furthermore, FENO and EOS% in peripheral blood were also dramatically increased in the CVA group compared with the BCT (-) group (p < 0.0001 for all) (Table 1).

Differences in lung function and FENO values between CA and CVA patients with FEV1% ≥ 80% predicted

Baseline data (age, height, weight, BMI, smoking history, and history of allergic rhinitis) were matched between CA and CVA patients. Although there were no statistically significant inter-group differences in FVC (%pred), FEV1 (%pred), PEF (%pred), MEF75 (%pred), MEF50 (%pred), MEF25 (%pred), and MMEF (%pred), a high ratio of small airway dysfunction was found in the CA group (13%). Interestingly, we found that the value of FEV1/FVC was slightly lower in CA subjects compared to that of CVA patients (p = 0.049). FENO was significantly elevated in the CA group compared with the CVA group (p < 0.001), while EOS and EOS% did not differ between the two groups. Although BHR degree, which was reflected by PD20, did not differ between the two groups, it showed an elevated trend in the CA group (p = 0.231).

Differences in diagnostic accuracy of small airway function variables and FENO used for predicting BCT between suspected CA and chronic cough patients with FEV1% ≥ 80% predicted

ROC curves were used to evaluate the ability of the variables to predict positive BCT.

For small airway function variables, the AUCs for a positive BCT diagnosis were 0.734 (95% CI 0.688–0.776) for MEF50, 0.715 (95% CI 0.668–0.758) for MMEF, with cut-off values of 76.2% and 78.8%, respectively, in suspected CA patients with FEV1% ≥ 80% predicted (Table 2; Fig. 1). The AUCs for a positive BCT diagnosis were 0.738 (95% CI 0.699–0.775) for MEF50, 0.716 (95% CI 0.677–0.754) for MMEF, with cut-off values of 87.1% and 73.7%, respectively, in chronic cough patients with FEV1% ≥ 80% predicted (Table 3; Fig. 2), indicating that MEF50 and MMEF have predictive value both in CA and CVA patients with different cut-off values.

Table 2 Optimal cut-off values and other measures of usefulness for predicting bronchial hyperresponsiveness in suspected classic asthma patients with FEV1% ≥ 80%
Full size table
Fig. 1
figure 1

ROC curves for the models of FEFs combined with FENO for predicting positive bronchial provocation tests in suspected classic asthma patients with FEV1% ≥ 80%. (A) MEF50 combined with FENO. AUCModel = 0.834 (95% CI, 0.794 to 0.869); AUCFENO = 0.728 (95% CI, 0.682 to 0.771; p < 0.001, compared with the model); AUCMEF50 = 0.734 (95% CI, 0.688 to 0.776; p < 0.001, compared with the model) (B) MMEF combined with FENO. AUCModel = 0.824 (95% CI, 0.783 to 0.860); AUCFENO =0.728 (95% CI, 0.682 to 0.771; p < 0.001, compared with the model); AUCMMEF = 0.715 (95% CI, 0.668 to 0.758; p < 0.001, compared with the model). Abbreviations: ROC, receiver operating characteristic; FENO, fractional exhaled nitric oxide; AUC, area under the curve; MEF50: forced expiratory flow at 50% of forced vital capacity; MEF25: forced expiratory flow at 75% of forced vital capacity; MMEF: maximum mid-expiratory flow

Full size image
Table 3 Optimal cut-off values and other measures of usefulness for predicting bronchial hyperresponsiveness in chronic cough patients
Full size table
Fig. 2
figure 2

ROC curves for the models of FEFs combined with FENO for predicting positive bronchial provocation tests in chronic cough patients. (A) MEF50 combined with FENO. AUCModel = 0.782 (95% CI, 0.745 to 0.816); AUCFENO = 0.603 (95% CI, 0.560 to 0.644; p < 0.001, compared with the model); AUCMEF50 = 0.738 (95% CI, 0.699 to 0.775; p < 0.001, compared with the model) (B) MMEF combined with FENO. AUCModel = 0.767 (95% CI, 0.730 to 0.802); AUCFENO =0.603 (95% CI, 0.560 to 0.644; p < 0.001, compared with the model); AUCMMEF = 0.716 (95% CI, 0.677 to 0.754; p < 0.001, compared with the model). Abbreviations: ROC, receiver operating characteristic; FENO, fractional exhaled nitric oxide; AUC, area under the curve; MEF50: forced expiratory flow at 50% of forced vital capacity; MEF25: forced expiratory flow at 75% of forced vital capacity; MMEF: maximum mid-expiratory flow

Full size image

For FENO, a noninvasive biomarker of eosinophilic airway inflammation, the predictive value for BCT in chronic cough patients was much lower than that in suspected CA patients (AUC = 0.603 (95% CI 0.560–0.644) in chronic cough patients and AUC = 0.728 (95% CI 0.682–0.771) in suspected CA patients), with cut-off values of 27 ppb and 30 ppb, respectively (Tables 2 and 3; Figs. 1 and 2).

We investigated if predicting BCT could be improved by combining spirometry measurements with FENO by repeating the ROC analyses. The AUCs of MEF50 and MMEF joined with FENO in patients with CVA (AUCs = 0.834 and 0.824, respectively) were also lower than those in patients with CA (AUCs = 0.782 and 0.767, respectively), which were dramatically higher than the AUCs of single MEF50 and MMEF (p < 0.0001 for all) (Table S2).

Part II

Demographic and clinical characteristic data of CA patients and CVA patients with FEV1% ≥ 80% predicted and positive BCT before ICS/LABA treatment

A total of 31 CA patients and 35 CVA patients with FEV1 ≥ 80% predicted, positive BCT, and negative BDT underwent spirometry after ICS/LABA for 4 weeks. As shown in Table 4, demographic variables did not differ at baseline between the CA and CVA groups. Compared with the CVA group, FENO and R5-R20 were higher in the CA group at baseline (p = 0.031 for FENO and = 0.043 for R5-R20), although EOS% in peripheral blood, PD20, symptom duration, and improvement times did not differ between the two groups. In addition, there were no statistically significant inter-group differences in ΔFEV1%, ΔMEF25%, and ΔMMEF%, which were still higher in the CVA group than in the CA group at baseline.

Table 4 Demographic data, spirometric variables, FENO values, PD20 values, and peripheral eosinophils values of CA patients and CVA patients before ICS/LABA treatment
Full size table

Demographic and clinical characteristic data of CA patients and CVA patients with positive BCT

Overall, both central airway (FEV1, PEF, and MEF75) and small airway indices (MEF50, MEF25, and MMEF) were dramatically improved in both CA and CVA groups after the 4-week treatment (Table 5). All patients with CA (n = 31) or CVA (n = 35) showed no exacerbation of asthma during the 4-week follow-up period. There were 26 patients with CA and 24 patients with CVA treated with ICS/LABA that improved clinically (Δ ACT/ Δ CET > 3). Collectively, 14 subjects (45.16%) in the CA group and 18 subjects (51.43%) in the CVA group displayed an FEV1 improvement > 200 ml and > 12%, while 26 subjects (83.87%) in the CA group and 28 subjects (80%) in the CVA group displayed an FEV1 improvement > 200 ml.

Table 5 Demographic data, spirometric variables, FENO values, peripheral eosinophils values, improvement of clinical symptoms and lung function of CA patients and CVA patients
Full size table

As shown in Table 5, among CA subjects, there were 14 patients with an improvement of FEV1 > 200 ml and > 12%, 12 patients with an improvement of FEV1 > 200 ml, and 5 patients with an improvement of FEV1 < 200 ml and < 12%. After the 4-week treatment, the ΔACT score was higher in patients with an improvement of FEV1 > 200 ml than in patients with an improvement of FEV1 < 200 ml and < 12%, while symptom recovery time was shorter in patients with an improvement of FEV1 > 200 ml (p = 0.013). However, FENO and small airway indices were not significantly different among the three groups at baseline.

Among CVA subjects, there were 18 patients with an improvement of FEV1 > 200 ml and > 12%, 10 patients with an improvement of FEV1 > 200 ml, and 7 patients with an improvement of FEV1 < 200 ml and < 12%. Moreover, there were significant inter-group differences in FENO, ΔFEV1, and ΔFEV1% before ICS/LABA treatment (p = 0.004 for FENO, 0.010 for ΔFEV1, and 0.014 for ΔFEV1%, respectively), which indicated that higher ΔFEV1 or ΔFEV1% predicted a better anti-asthma response. Similarly, compared with patients with an improvement of FEV1 < 200 ml and < 12%, a higher ΔCET score and shorter symptom recovery time were shown in patients with an improvement of FEV1 > 200 ml after ICS/LABA treatment (p = 0.002). However, small airway indices were not significantly different among the three groups at baseline.

Diagnostic accuracy of variables used for predicting anti-asthma therapy response in CA and CVA patients with FEV1% ≥ 80% predicted

The prognostic value of these variables for predicting the efficacy of anti-asthma therapy was assessed by calculating the AUC (Table S3, Fig. 3). The largest AUCs in mild CA patients were the ΔFEV1 (0.827, 95% CI 0.649 to 0.938), ΔFEV1% (0.823, 95% CI 0.644 to 0.936), ΔMEF50 (0.812, 95% CI 0.631 to 0.929), and ΔMEF50% (0.800, 95% CI 0.618 to 0.921), taking the optimal cut-off values of 90 ml, 3.49%, 310 ml and 8.48%, respectively. The AUCs of FENO, ∆FEV1, and ΔFEV1% in CVA patients were 0.911, 0.842, and 0.806 with cut-off values of 19 ppb, 110 ml, and 2.59%, respectively.

Fig. 3
figure 3

ROC curves for predicting anti-asthma response in mild CA patients (A) and CVA patients (B). (A) AUCΔFEV1 = 0.827 (95% CI, 0.649 to 0.938; p < 0.001, compared with AUC0.5); AUCΔFEV1% = 0.823 (95% CI, 0.644 to 0.936; p < 0.001, compared with AUC0.5). AUCΔMEF50 = 0.812 (95% CI, 0.631 to 0.929; p < 0.01, compared with AUC0.5); AUCΔMEF50% = 0.800 (95% CI, 0.618 to 0.921; p < 0.01, compared with AUC0.5)(B) AUCFENO = 0.911 (95% CI, 0.765 to 0.980; p < 0.001, compared with AUC0.5); AUCΔFEV1 = 0.842 (95% CI, 0.679 to 0.943; p < 0.001, compared with AUC0.5); AUCΔFEV1% = 0.806 (95% CI, 0.638 to 0.920; p < 0.001, compared with AUC0.5). Abbreviations: ROC, receiver operating characteristic; AUC, area under the curve; ΔMEF50: increase of forced expiratory flow at 50% of forced vital capacity in one second in BDT; ΔMEF50%: increase of forced expiratory flow at 75% of forced vital capacity as a percentage of baseline value in BDT; FENO, fractional exhaled nitric oxide; ∆FEV1: increase of forced expiratory volume in one second in BDT; ∆FEV1%: increase of forced expiratory volume in one second as a percentage of baseline value in BDT

Full size image

Discussion

In clinical settings, clinicians are often face distinct clinical profiles between CA and CVA, particularly regarding eosinophilic inflammation, BHR and anti-asthma therapy. To understand the etiology of these asthmatic patients, we compared patients of diagnosed CVA and CA with FEV1 ≥ 80% predicted in baseline clinical characteristics, pulmonary function, FENO, eosinophilic inflammation, BCT prediction, and anti-asthma therapy responseness. Compared with CA, CVA exhibited lower FENO values (reflecting airway eosinophilic inflammation), lower EOS and EOS% in blood (reflecting systemic eosinophilic inflammation), and milder BCT response (reflected by a lower PD20 of positive BCT).

Eosinophilic airway inflammation is a critical characteristic of asthma. CVA exhibits similar levels of eosinophilic airway inflammation to CA, but with less severe airway remodeling [27, 31]. Measuring EOS count and EOS% in the blood is an evidence-based standard measure of airway inflammation, as recommended by relevant guidelines [15]. EOS% were also related to asthma exacerbations and control. Similar to some previous studies [12], EOS% was increased in CVA and CA patients, compared with those in corresponding subjects negative for BCT. Our results also indicated that there was a higher EOS% and a lower PD20 values in CA patients. These suggested that the levels of eosinophil counts in blood might be a risk factor with an increased degree of BHR for the future development of asthma.

FENO is widely acknowledged as a biomarker for eosinophilic airway inflammation in the central airways, commonly elevated in asthma [20, 28]. Nevertheless, it has limited utility in detecting inflammation in the peripheral airways. Similar to previous studies [33, 35], our findings also indicated that FENO was elevated in the BCT-positive group of both chronic cough patients and suspected CA patients with FEV1 ≥ 80% predicted. On the other hand, FENO levels was obviously elevated in CA patients compared to CVA patients, which corresponds to eosinophilic airway inflammation being significantly milder in CVA than in CA.

Guidelines stipulate that spirometry and BHR are the fundamental diagnostic criteria for both CVA and CA [5]. FEV1% predicted may reflect asthma control or symptoms of different types of asthma. In our present study, although FEV1% predicted was normal in CA and CVA patients, it was still lower than that of corresponding subjects negative for BCT. This might indicate that declined FEV1 existed in positive BCT patients. In addition, lower FEV1/FVC in CA patients indicated that there was severe airflow limitation in CA rather than CVA, which is the reason that wheezing, not cough, occupied clinical symptoms in CA.

The pathobiology of asthma involves small airways, which have a significant role in certain asthmatic phenotypes. In particular, SAD is associated with a higher probability of BHR [6, 7]. Measurements of MMEF, MEF25, and MEF50 are also simpler diagnostic tools to detect SAD in asthma [34]. Here, we confirmed that MMEF, MEF25, and MEF50 in CA and CVA patients were lower than those of corresponding subjects negative for BCT, which suggested the presence of small airway injury in asthmatic subjects with FEV1 ≥ 80% predicted. However, as a previous study reported [13], MEFs did not differ between the CA and CVA groups, although there is a high ratio of SAD in CA. This suggests that while small airways cannot effectively differentiate patients with CVA from those with CA, milder SAD is more prevalent in CVA.

BHR is not only the key feature of CVA but also the main criterion for CVA diagnosis [3]. Previous studies have also suggested that the development of wheezing during the course of CVA may be induced by increasing BHR [30], and about 30% of CVA cases were likely to develop into CA [27]. While CVA shares similarities with CA in terms of BHR and eosinophilic airway inflammation, several studies have reported that CVA exhibits milder BHR and airway inflammation [33]. As expected, higher BHR and milder PD20 were observed in CA patients compared with those in CVA patients. However, the broad applicability of BCT to diagnose BHR is limited due to its disadvantages.

Our previous study reported that FENO and small airway indices are predictive markers, instead of BCT, in BHR of chronic cough [1]. The improvement of FEV1% in BDR also have predictive value on CVA diagnosis and response to anti-asthma treatment in patients with chronic cough [17]. In this study, we continued to analyze the predictive value of positive BCT in CA and CVA. At first, we confirmed that FENO > 30 ppb (PPV, 76%) with an AUC of 0.728 could predict BCT of CA. However, FENO alone did not result in high AUC values for positive BCT diagnosis of CVA. This suggested that eosinophilic airway inflammation in CVA was not severe enough to predict BCT. Then, we found that the two most valuable spirometry variables for predicting BCT were MEF50 (AUCs = 0.734 and 0.738) and MMEF (AUCs = 0.715 and 0.716) in CA and CVA patients, respectively.

Since all the generated AUC values were below 0.80, utilizing only these parameters would be inadequate to foretell BHR among patients with CA or CVA. Therefore, we combined the MEFs with FENO or EOS counts to enhance their predictive value for BCT diagnosis. Here, we verified that positive BCT in CA was associated with FENO > 30 ppb and MMEF%predicted < 78.8% or MEF50%predicted < 76.2%. On the other hand, the joint model of FENO > 27 ppb and MMEF%predicted < 73.7% or MEF50%predicted < 87.1% predicted positive BCT in CVA. Correspondingly, the AUCs of MEFs combined with FENO were much higher than those of single AUCs, both in CA and CVA. Therefore, similar to our previous study [2], MEF50 and MMEF predicted BCT in patients with CA or CVA, but whether FENO has a predictive value depends on the type of asthma. In addition, our finding that the PPV of MEFs combined with FENO was higher in CA patients than in CVA patients suggested that MEFs combined with FENO were more likely to improve the prediction of BCT diagnosis in CA. Such measurement may provide economic substitutes for predicting BCT in suspected CA patients with FEV1 ≥ 80% predicted, especially in primary hospitals.

ICS is regarded as the first-line therapy for CVA, which not only alleviates cough but also minimizes the likelihood of advancing to CA [10]. Patients administering ICS showed a decline in CA onset rate, providing evidence that long-term ICS use can act as an intervention against CA originating from CVA [11]. In addition, long-term ICS attenuated BHR to inhaled methacholine in patients with CVA. Here, we selected patients with BCT of CA and CVA to assess anti-asthma response after four weeks of ICS/LABA treatment. We also observed that all patients showed improvement in central and small airway function after four weeks of ICS/LABA therapy, while there were no significant differences between the two groups. Thereby, this finding verified that both CA patients and CVA patients were likely to benefit from initial anti-asthma therapy. Our findings, showing that patients with a higher improvement of FEV1 in BDT were more likely to achieve a better response to anti-asthma therapy and shorter time of symptom recovery, confirmed that patients with lower improvements of FEV1 in BDT were less likely to achieve an anti-asthmatic response. In brief, this finding, which indicated that BCT has a high false-negative rate, confirmed that even if BDT has a high ratio of being negative, it has a better anti-asthma response predictive value. On the other hand, previous studies reported that both MMEF value and FENO can predict the anti-asthma course or response in CA and CVA [25]. However, in our present study, FENO > 19 ppb (PPV, 100%) with an AUC of 0.911 could only predict CA, while ΔMEF50 > 310 ml (PPV, 95.5%) with an AUC of 0.812 only predicted CVA. Furthermore, the two most valuable spirometric variables for predicting better anti-asthma responses were ΔFEV1 (AUC = 90 ml and 110 ml) and ΔFEV1% (AUC = 3.49% and 2.59%) in CA and CVA patients, respectively. Such results implied that ΔFEV1 and ΔFEV1% at baseline were the most stable parameters in predicting anti-asthma response, both in CA patients and CVA patients. Consequently, we are able to carry out on-demand anti-asthma therapy according to different asthma subtypes, FEV1%, MMEF%, or FENO. This idea needs to be further verified in the near future.

There are some limitations to our current study. First, due to the difficulty of clinical operation, the sample size of CA and CVA patients with 4 weeks of ICS/LABA treatment was small, the follow-up time was relatively short, and the single inhaled device/molecular may also be a limitation of our study. Our finding’s credibility should be affirmed by conducting additional national multicenter clinical research with a larger sample size, longer follow-up period, and various inhaled devices. Second, the history of atopy was important for asthma diagnosis, but only allergic rhinitis history was collected in this retrospective study. Therefore, the inquiry of atopy needed to be followed up in our study. Third, sputum eosinophil count is a better assessment of airway inflammation rather than eosinophils in blood. Further data on sputum eosinophils will be applied in the evaluation of airway inflammation in our future research.

Conclusions

In conclusion, CVA patients show less airway eosinophilic inflammation (FENO) values than CA patients with FEV1 ≥ 80% predicted. FENO combined with MEF50% or MMEF% could be an economically favorable method to forecast hyperresponsiveness in CA patients with normal FEV1. Moreover, both CA and CVA patients with FEV1% ≥ 80% predicted were likely to benefit promptly from anti-asthma therapy, and improvement of FEV1 and FEV1% in BDT predicted a better anti-asthma response in asthmatic patients.

Data availability

The data that support the fundings of this study are available from corresponding author upon reasonable request.

Abbreviations

ACT:

Asthma control test

ACT1 :

Asthma control test at the first visit

ACT2 :

Asthma control test at the second visit

ATS:

American Thoracic Society

AUC:

Area under the curve

BHR:

Bronchial hyperresponsiveness

BCT:

Bronchial challenge tests

BDT:

Bronchodilation test

BMI:

Body Mass Index

CA:

Classic asthma

CRSwNP:

Chronic rhinosinusitis with nasal polyps

CVA:

Cough variant asthma

EOS:

Eosinophils counts in blood

EOS%:

Eosinophils percentages in blood

ERS:

European Respiratory Society

FENO:

Fractional exhaled nitric oxide

FEV1 :

Forced expiratory volume in one second

FEV1/FVC:

Ratio of the FEV1 to the forced vital capacity

FVC:

Forced vital capacity

GERD:

Gastroesophageal reflux disease

ICS:

Long-term inhaled corticosteroids

ICS/LABA:

Inhaling corticosteroids and longacting β agonists

IOS:

Impulse oscillometry

ROC:

Receiver-operating characteristic

MEF75:

Forced expiratory flow at 25% of forced vital capacity

MEF50:

Forced expiratory flow at 50% of forced vital capacity

MEF25:

Forced expiratory flow at 75% of forced vital capacity

MMEF:

Forced expiratory flow between 25% and 75%

NO:

Nitric oxide

NPV:

negative predictive values

PEF:

Peak expiratory flow

PPV:

positive predictive values

Pred:

Predictive value

SD:

Standard deviation

VAS:

visual analogue scale

WBC:

White blood cell

References

  1. Bao W, Zhang X, Lv C, Bao L, Yin J, Huang Z, et al. The value of fractional exhaled nitric oxide and forced Mid-Expiratory flow as predictive markers of bronchial hyperresponsiveness in adults with chronic cough. J Allergy Clin Immunol Pract. 2018;6(4):1313–20. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaip.2017.09.026.

    Article  PubMed  Google Scholar 

  2. Bao W, Zhang X, Yin J, Han L, Huang Z, Bao L, et al. Small-Airway function variables in spirometry, fractional exhaled nitric oxide, and Circulating eosinophils predicted airway hyperresponsiveness in patients with mild asthma. J Asthma Allergy. 2021;14:415–26. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/JAA.S295345.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Boulet LP, Reddel HK, Bateman E, Pedersen S, FitzGerald JM. The global initiative for asthma (GINA): 25 years later. Eur Respir J. 2019;54(2). https://doiorg.publicaciones.saludcastillayleon.es/10.1183/13993003.00598-2019.

  4. Chung K, F.Pavord ID. Prevalence, pathogenesis, and causes of chronic cough. Lancet. 2008;371(9621):1364–74. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0140-6736(08)60595-4.

    Article  PubMed  Google Scholar 

  5. Coates AL, Wanger J, Cockcroft DW, Culver BH, Force BTT, Kai-Hakon C, Diamant Z, et al. ERS technical standard on bronchial challenge testing: general considerations and performance of methacholine challenge tests. Eur Respir J. 2017;49(5). https://doiorg.publicaciones.saludcastillayleon.es/10.1183/13993003.01526-2016.

  6. Currie GP, Jackson CM, Lee DK. Determinants of airway hyperresponsiveness in mild asthma. Ann Allergy Asthma Immunol. 2003;90(5):560–3. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S1081-1206(10)61851-0.

    Article  PubMed  Google Scholar 

  7. Drewek R, Garber E, Stanclik S, Simpson P, Nugent M. The FEF25-75 and its decline as a predictor of methacholine responsiveness in children. J Asthma. 2009;46(4):375–81. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/02770900802492079.

    Article  CAS  PubMed  Google Scholar 

  8. Dusser D, Montani D, Chanez P, de Blic J, Delacourt C, Deschildre A, et al. Mild asthma: an expert review on epidemiology, clinical characteristics and treatment recommendations. Allergy. 2007;62(6):591–604. https://doiorg.publicaciones.saludcastillayleon.es/10.1111/j.1398-9995.2007.01394.x.

    Article  CAS  PubMed  Google Scholar 

  9. Fujimura M. [Pathophysiology, diagnosis and treatment of cough variant asthma]. Rinsho Byori. 2014;62(5):464–70.

    PubMed  Google Scholar 

  10. Fujimura M, Hara J. Change in bronchial responsiveness and cough reflex sensitivity in patients with cough variant asthma: effect of inhaled corticosteroids. Cough. 2005;1:5. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1745-9974-1-5.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Fujimura M, Ogawa H, Nishizawa Y. Comparison of atopic cough with cough variant asthma: is atopic cough a precursor of asthma? Thorax. 2003;58(1):14–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1136/thorax.58.1.14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Gao J, Wu F, Wu S. Inflammatory subtypes in classic asthma and cough variant asthma. J Inflamm Res. 2020;13:1167–73. https://doiorg.publicaciones.saludcastillayleon.es/10.2147/JIR.S269795.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Gao J, Wu H. Small airway dysfunction in patients with cough variant asthma: a retrospective cohort study. BMC Pulm Med. 2021;21(1):49. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-021-01419-4.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Ghosh MC, Gorantla V, Makena PS, Luellen C, Sinclair SE, Schwingshackl A, et al. Insulin-like growth factor-I stimulates differentiation of ATII cells to ATI-like cells through activation of Wnt5a. Am J Physiol Lung Cell Mol Physiol. 2013;305(3):L222–228. https://doiorg.publicaciones.saludcastillayleon.es/10.1152/ajplung.00014.2013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Hamada K, Oishi K, Chikumoto A, Murakawa K, Ohteru Y, Matsuda K, et al. Impact of sinus surgery on type 2 airway and systemic inflammation in asthma. J Asthma. 2021;58(6):750–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1080/02770903.2020.1729380.

    Article  CAS  PubMed  Google Scholar 

  16. Hao H, Bao W, Xue Y, Zhou Y, Huang Z, Yin D, et al. Spirometric changes in bronchodilation tests as predictors of asthma diagnosis and treatment response in patients with FEV1 >/= 80% predicted. J Allergy Clin Immunol Pract. 2021;9(8):3098–e31083094. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaip.2021.03.015.

    Article  CAS  PubMed  Google Scholar 

  17. Hao H, Pan Y, Xu Z, Xu Z, Bao W, Xue Y, et al. Prediction of bronchodilation test in adults with chronic cough suspected of cough variant asthma. Front Med (Lausanne). 2022;9:987887. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fmed.2022.987887.

    Article  PubMed  Google Scholar 

  18. Huang K, Yang T, Xu J, Yang L, Zhao J, Zhang X, et al. Prevalence, risk factors, and management of asthma in China: a National cross-sectional study. Lancet. 2019;394(10196):407–18. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S0140-6736(19)31147-X.

    Article  PubMed  Google Scholar 

  19. Lai K, Chen R, Lin J, Huang K, Shen H, Kong L, et al. A prospective, multicenter survey on causes of chronic cough in China. Chest. 2013;143(3):613–20. https://doiorg.publicaciones.saludcastillayleon.es/10.1378/chest.12-0441.

    Article  PubMed  Google Scholar 

  20. Lipworth B, Manoharan A. Unlocking the quiet zone: the small airway asthma phenotype. Lancet Respir Med. 2014;2(6):497–506. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/S2213-2600(14)70103-1.

    Article  PubMed  Google Scholar 

  21. Malerba M, Radaeli A, Olivini A, Damiani G, Ragnoli B, Sorbello V, et al. Association of FEF25-75% impairment with bronchial hyperresponsiveness and airway inflammation in subjects with Asthma-Like symptoms. Respiration. 2016;91(3):206–14. https://doiorg.publicaciones.saludcastillayleon.es/10.1159/000443797.

    Article  CAS  PubMed  Google Scholar 

  22. Malerba M, Ragnoli B, Radaeli A. Usefulness of exhaled nitric oxide and sputum eosinophils in the long-term control of eosinophilic asthma. Chest. 2008;134(4):733–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1378/chest.08-0763.

    Article  CAS  PubMed  Google Scholar 

  23. Matsumoto H, Niimi A, Takemura M, Ueda T, Yamaguchi M, Matsuoka H, et al. Features of cough variant asthma and classic asthma during methacholine-induced brochoconstriction: a cross-sectional study. Cough. 2009;5:3. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/1745-9974-5-3.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Morice A, Dicpinigaitis P, McGarvey L. Chronic cough: new insights and future prospects. Eur Respir Rev. 2021;30(162). https://doiorg.publicaciones.saludcastillayleon.es/10.1183/16000617.0127-2021.

  25. Neelamegan R, Saka V, Tamilarasu K, Rajaram M, Selvarajan S. Clinical utility of fractional exhaled nitric oxide (FeNO) as a biomarker to predict severity of disease and response to inhaled corticosteroid (ICS) in asthma patients. J Clin Diagn Res. 2016;10(12):FC01–6. https://doiorg.publicaciones.saludcastillayleon.es/10.7860/JCDR/2016/20656.8950.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Ng B, Sadatsafavi M, Safari A, FitzGerald JM. Direct costs of overdiagnosed asthma: a longitudinal, population-based cohort study in British Columbia, Canada. BMJ Open. 2019;9(11):e031306. https://doiorg.publicaciones.saludcastillayleon.es/10.1136/bmjopen-2019-031306.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Niimi A, Amitani R, Suzuki K, Tanaka E, Murayama T. Eosinophilic inflammation in cough variant asthma. Eur Respir J. 1998;11(5):1064–9. https://doiorg.publicaciones.saludcastillayleon.es/10.1183/09031936.98.11051064.

    Article  CAS  PubMed  Google Scholar 

  28. Ricciardolo FL, Sorbello V. FeNO as biomarker for asthma phenotyping and management. Allergy Asthma Proc. 2015;36(1):e1–8. https://doiorg.publicaciones.saludcastillayleon.es/10.2500/aap.2015.36.3805.

    Article  PubMed  Google Scholar 

  29. Riley CM, Wenzel SE, Castro M, Erzurum SC, Chung KF, Fitzpatrick AM, et al. Clinical implications of having reduced mid forced expiratory flow rates (FEF25-75), independently of FEV1, in adult patients with asthma. PLoS ONE. 2015;10(12):e0145476. https://doiorg.publicaciones.saludcastillayleon.es/10.1371/journal.pone.0145476.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Rybka-Fraczek A, Dabrowska M, Grabczak EM, Bialek-Gosk K, Klimowicz K, Truba O, et al. Does bronchial hyperresponsiveness predict a diagnosis of cough variant asthma in adults with chronic cough: a cohort study. Respir Res. 2021;22(1):252. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12931-021-01845-2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Satia I, Watson R, Scime T, Dockry RJ, Sen S, Ford JW, et al. Allergen challenge increases capsaicin-evoked cough responses in patients with allergic asthma. J Allergy Clin Immunol. 2019;144(3):788–e795781. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaci.2018.11.050.

    Article  CAS  PubMed  Google Scholar 

  32. Schatz M, Kosinski M, Yarlas AS, Hanlon J, Watson ME. The minimally important difference of the asthma control test. J Allergy Clin Immunol. 2009;124(4):719–e723711. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaci.2009.06.053.

    Article  PubMed  Google Scholar 

  33. Shimoda T, Obase Y, Kishikawa R, Iwanaga T, Miyatake A. The fractional exhaled nitric oxide and serum high sensitivity C-reactive protein levels in cough variant asthma and typical bronchial asthma. Allergol Int. 2013;62(2):251–7. https://doiorg.publicaciones.saludcastillayleon.es/10.2332/allergolint.12-OA-0515.

    Article  CAS  PubMed  Google Scholar 

  34. Siroux V, Boudier A, Dolgopoloff M, Chanoine S, Bousquet J, Gormand F, et al. Forced midexpiratory flow between 25% and 75% of forced vital capacity is associated with long-term persistence of asthma and poor asthma outcomes. J Allergy Clin Immunol. 2016;137(6):1709–e17161706. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaci.2015.10.029.

    Article  PubMed  Google Scholar 

  35. Tajiri T, Niimi A, Matsumoto H, Ito I, Oguma T, Otsuka K, et al. Prevalence and clinical relevance of allergic rhinitis in patients with classic asthma and cough variant asthma. Respiration. 2014;87(3):211–8. https://doiorg.publicaciones.saludcastillayleon.es/10.1159/000355706.

    Article  CAS  PubMed  Google Scholar 

  36. van der Wiel E, ten Hacken NH, van den Postma DS. Small-airways dysfunction associates with respiratory symptoms and clinical features of asthma: a systematic review. J Allergy Clin Immunol. 2013;131(3):646–57. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.jaci.2012.12.1567.

    Article  PubMed  Google Scholar 

  37. Yuan H, Liu X, Li L, Wang G, Liu C, Zeng Y, et al. Clinical and pulmonary function changes in cough variant asthma with small airway disease. Allergy Asthma Clin Immunol. 2019;15:41. https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13223-019-0354-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the professor MZ for her guidance and support throughout this research.

Funding

This study was supported by the National Natural Science Foundation of China (grant NO. 82270027, MZ), the Characteristic Research Program of Shanghai General Hospital (Grant No. CTCCR-2021B07, MZ) and the Fundamental Research Funds for the Central Universities (Grant No. YG2024QNA31, XZ).

Author information

Author notes

  1. Xue Zhang, Chengjian Lv and Huijuan Hao contributed equally to this work and share first authorship.

Authors and Affiliations

  1. Department of Respiratory and Critical Care Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, No. 100, Haining Road, Shanghai, 200080, China

    Xue Zhang, Chengjian Lv, Huijuan Hao, Jingwang Lin, Min Zhang & Xue Tian

Authors
  1. Xue Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Chengjian Lv
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Huijuan Hao
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Jingwang Lin
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Min Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Xue Tian
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

X.T. and M.Z. conceived of and designed the entire study.X.Z. enrolled the patients.H.H. contributed to data collection.C.L. and J.L. was involved in interpreting spirometric assessments, bronchodilation tests, bronchial challenge tests and FENO data.X.Z and C.L. performed statistical analysis.X.T. wrote the manuscript supervised by M.Z.All authors critically reviewed and approved the final version.All authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Corresponding authors

Correspondence to Min Zhang or Xue Tian.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Institutional Review Board of the Shanghai General Hospital (no. [2020]30). The prospective study in PART II was registered on chictr.org.cn (No. ChiCTR2000029065). Informed consent in PART II was obtained for all subjects. As PART I in our study was a retrospective study, the requirement for obtaining informed consent from participants was waived by the ethics committee (no. 2017KY159). The research was conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, X., Lv, C., Hao, H. et al. Airway inflammation, bronchial hyperresponsiveness, and anti-asthma therapy responses in cough variant asthma and classic asthma with FEV1% ≥80% predicted. BMC Pulm Med 25, 166 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-025-03627-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12890-025-03627-8

Keywords

BMC Pulmonary Medicine

ISSN: 1471-2466

Contact us