Dupilumab improves the small airway dysfunction in children with moderate to severe asthma: A retrospective analysis

Dupilumab improves the small airway dysfunction in children with moderate to severe asthma: A retrospective analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dupilumab improves the small airway dysfunction in children with moderate to severe asthma: A retrospective analysis Lihong Sun, Lijun Zeng, Lanying Cheng, Kaijia Yang, Yueying Yang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8288806/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: In children with asthma, airway wall inflammation and mucus secretion can obstruct the lumen, causing small airway dysfunction (SAD) which correlates with poor asthma control and frequent acute exacerbations. However, current medications show limited efficacy in improving small-airway function in pediatric patients. Dupilumab effectively suppresses type 2 inflammation in asthma and may represent a novel, effective therapy for children with asthma, although real-world evidence is still lacking in China. This study evaluated the effectiveness of dupilumab on SAD in children with uncontrolled moderate-to-severe asthma. Methods: This retrospective cohort study analyzed 106 children (aged 6-14 years) with moderate-to-severe asthma treated with dupilumab at the Guangzhou Institute of Respiratory Health (January 2022 and March 2025). All participants had uncontrolled asthma despite the treatment with medium-to-high-dose inhaled corticosteroid (ICS) plus long-acting β₂-agonist (LABA) or leukotriene receptor antagonists (LTRA), with type 2 inflammation characteristics. The primary endpoint was the change of the percentage of patients with SAD (defined as at least two of MMEF 25/75 , MEF 25 or MEF 50 below 65% of predicted values) at 6 months after dupilumab initiation. The secondary endpoints included changes of the percentage of patients with SAD at 3, 9, 12 months and changes in small-airway function indicators at 3, 6, 9, 12 months; changes in type 2 inflammation biomarkers (FeNO, serum total IgE, blood eosinophil count and sputum eosinophil percentage) at 3, 6, 9, 12 months; changes in annualized asthma exacerbation, pulmonary function tests, asthma symptom scores and rescue medication use at 6 months; a multivariable logistic regression model was constructed to identify factors associated with improvement in SAD and baseline characteristics were compared between patients with and without improvement in SAD. Results: In children with asthma (mean age 8.71±2.5), 75.5% had allergic rhinitis and 15.1% had atopic dermatitis, with mean pre-treatment exacerbations of 2.0±1.1 annually. Post-dupilumab, the proportion of SAD patients significantly decreased from 63.2% to 16.0% at 6 months. All small airway indicators improved significantly ( p < 0.001). MMEF 25/75 % predicted increased from 57.2±21.3% to 75.8±20.3%, MEF 25 % predicted from 48.3±21.1% to 66.4±20.0%, and MEF 50 % predicted from 58.7±21.7% to 76.1±20.2% at 6 months. All type 2 inflammation biomarkers declined significantly: FeNO from 26.00 (13.00, 46.5) to 10.00 (8.00, 16.25) ppb, serum total IgE from 721.34 (294.75, 1330.94) to 162.81 (90.33, 297.70) IU/mL, blood eosinophil count from 610.00 (400.00, 840.00)×10 6 /L to 385.00 (260.00, 675.00)×10 6 /L, and sputum eosinophil percentage from 6.00 (2.50, 21.50)% to 0.50 (0.00, 1.50)% at 6 months. Dupilumab also significantly reduced asthma exacerbation rates, improved pre-BD FEV 1 and asthma symptom scores, and decreased the medication requirement. Multivariable logistic regression model showed that SAD improvement was independently associated with greater increases in pre-BD FEV₁/FVC% predicted (OR 1.27, 95% CI 1.09–1.51) and larger reductions in FeNO (OR 1.02, 95% CI 1.00–1.06). Children who improved in SAD had better baseline asthma control and less impaired lung function. Conclusion: Dupilumab effectively ameliorates SAD in children with moderate-to-severe asthma, probably through suppression of type 2 inflammation. Dupilumab children asthma small airway dysfunction real-world study type 2 inflammation Figures Figure 1 Figure 2 Introduction Asthma is a chronic airway inflammatory disease affecting the entire respiratory tract, from the central to peripheral airway[1]. Inflammation, mucus hypersecretion, and structural remodeling in the distal bronchioles contribute to small airway dysfunction (SAD) [2]. SAD is closely associated with poor asthma control, increased exacerbation risk, reduced quality of life[3] and is prevalent even in mild asthma[4]. Despite its clinical relevance, SAD is often insufficiently managed because conventional inhaled therapies—primarily inhaled corticosteroids (ICS) combined with long-acting β₂-agonists (LABA) or leukotriene receptor antagonists (LTRA)—achieve limited drug deposition in the small airways and incompletely suppress distal airway inflammation[1]. To better understand the pathological changes in small airways, the key assessment indicators of SAD include MMEF 25/75 % predicted, MEF 25 % predicted and MEF 50 % predicted. Reduced MMEF 25/75 % predicted serves as an independent biomarker for severe asthma, correlated with biomarkers of type 2 inflammation, including blood eosinophilia and FeNO, and is associated with severe phenotypes and enhanced bronchial hyperreactivity[5]. Increasing evidence indicates that SAD is not merely a mechanical phenomenon but is strongly driven by type 2 inflammation. Cytokines such as interleukin (IL)-4, IL-5, and IL-13 promote eosinophilic infiltration, mucus plugging, goblet-cell metaplasia, epithelial damage, airway wall edema, and subepithelial fibrosis in the distal airways. These type 2 inflammation -driven pathological processes narrow the small airway lumen, reduce airway compliance, and contribute to persistent reductions in expiratory flow—hallmark features of SAD. Furthermore, type 2 biomarkers, including blood eosinophils, sputum eosinophils, serum immunoglobulin E (IgE), and fractional exhaled nitric oxide (FeNO), are associated with small-airway physiological indices. These biomarkers are increasingly applied in clinical practice to aid in identifying T2-high phenotypes, estimating exacerbation risk, and informing biologic therapy selection.[6, 7]. This growing recognition of small airway inflammation as a therapeutic target has spurred interest in biologics with potential distal airway effects. Growing recognition of the contribution of type 2 inflammation to distal airway pathology has spurred interest in biologics capable of modulating these pathways. Dupilumab, a fully human monoclonal antibody targeting IL-4 receptor α, inhibits both IL-4 and IL-13 signaling[8, 9], thereby suppressing multiple components of type 2 inflammation relevant to SAD. Unlike ICS-based therapy, whose anti-inflammatory effect in the small airways is limited by particle size and deposition characteristics, dupilumab exerts systemic and airway-wide immunomodulatory effects that extend to the peripheral bronchioles. Clinical trials have demonstrated its efficacy in reducing exacerbations and improving lung function in moderate-to-severe asthma [10], and study in adult patients have suggest a beneficial effect on SAD specifically[11]. However, evidence in pediatric patients—particularly within real-world settings—remain insufficiently characterized. This retrospective study aimed to assess dupilumab’s effect on small airway function in Chinese children with uncontrolled moderate-to-severe asthma. Methods Study Population This retrospective study analyzed electronic medical record data from the Guangzhou Institute of Respiratory Health for patients who started dupilumab treatment between January 2022 and March 2025. Included patients were aged 6–14 with uncontrolled asthma despite medium-to-high dose ICS treatment and type 2 inflammation characteristics. Exclusion criteria included dupilumab use for non-asthma conditions, concurrent biologic therapies, and sublingual or subcutaneous desensitization treatments. The Institutional Ethical Review Board of the First Affiliated Hospital of Guangzhou Medical University approved the study (No. ES-2024-001-01). Since it was an anonymized and retrospective research, written informed consent was waived in accordance with the Declaration of Helsink. Clinical trial number: not applicable. Data collection The date of the first dupilumab injection was designated the index date. The observation period spanned from the index date to each patient's final visit. Data extracted from the routine medical care included demographics, clinical characteristics, pulmonary function test results (including small airway function indicators MMEF 25/75 % predicted, MEF 25 % predicted and MEF 50 % predicted), serum biochemical indicators, asthma scale scores, treatment patterns. All data came from the Hospital Information System/Laboratory Information System. The Children-Asthma Control Test (c-ACT) and Asthma Control Questionnaire 7 Interviewer-Administered (ACQ-7-IA) measure asthma control on a 0–6 scale (totally controlled to severely uncontrolled), with a 0.5 change considered clinically significant. We got the permission to use ACQ-7-IA form from the author via http://www.qoltech.co.uk/index.htm . The c-ACT scores form was obtained from https://eprovide.mapi-trust.org/instruments/childhood-asthma-control-test . The Ethics Committee of the Guangzhou Institute of Respiratory Health approved the study protocol (Ethics Number: ES-2024-001-01). Study Endpoints The primary endpoint of this study was the change in the percentage of patients with SAD (defined as at least two of MMEF 25/75 , MEF 25 or MEF 50 below 65% of predicted values)[12] from baseline to 6 months. Secondary endpoints encompassed several domains, including: 1) The change of the percentage of patients with SAD from baseline to different follow-up timepoints (3, 9 and 12 months) and changes in small-airway function indicators (MMEF 25/75 % predicted, MEF 25 % predicted and MEF 50 % predicted) from baseline to different follow-up timepoints (3, 6, 9 and 12 months); 2) Changes in type 2 inflammation biomarkers (FeNO, serum total IgE, blood eosinophil count, and sputum eosinophil percentage) from baseline to different follow-up timepoints (3, 6, 9 and 12 months); 3) Changes in annualized asthma exacerbation rate (calculated as the total number of exacerbations divided by total person-years of follow-up), prebronchodilator forced expiratory volume in 1 second (pre-BD FEV 1 ), percentage of predicted prebronchodilator FEV 1 (pre-BD FEV 1 % predicted), asthma symptom scores (c-ACT and ACQ-7-IA) and rescue medication use from baseline to 6 months; 4) Factors influencing the SAD improvement; 5) Comparison in characteristics at baseline between patients with improvement in small airway function and those without improvement in small airway function. Statistical Analysis All statistical analyses were conducted using R version 4.2.3 (R Foundation for Statistical Computing, Vienna, Austria). Continuous variables with a normal distribution are reported as mean ± standard deviation (SD), whereas non-normally distributed variables are presented as median and interquartile range (IQR; Q1–Q3). Between-group differences were assessed using Student’s t-test for normally distributed variables and the Wilcoxon rank-sum test for non-normally distributed variables. For comparisons across multiple time points, one-way analysis of variance (ANOVA) was applied to normally distributed data, while the Kruskal–Wallis H test was used for non-normally distributed data. Categorical variables are summarized as frequencies and percentages, with group comparisons performed using the Chi-square test or Fisher’s exact test, as appropriate. All statistical tests were two-sided, and p < 0.05 was considered indicative of statistical significance. Missing data were not imputed; analyses were restricted to cases with complete information for the variables of interest. Multivariable logistic regression was used to assess the association between SAD improvement and type 2 inflammation biomarkers, asthma symptom scores, or lung function parameters. SAD improvement was defined as the first follow-up visit at which the patient no longer met the SAD diagnostic criteria. Patients who did not meet the improvement criteria at their final study visit were classified as non-improvement cases. For changes in test indicators, the follow-up data of patients in the improvement group were taken from the results of the last test before the improvement of small airway dysfunction; data of the last follow-up test during the observation period of the study were used for patients in the non-improvement group. The association between SAD improvement and these changes was analyzed using the difference between follow-up and baseline values (Δ = follow-up value - baseline value). For the frequency of asthma exacerbations, C-ACT scores, and ACQ-7-IA scores, which reflected asthma severity, the association with SAD improvement was examined both for baseline values and for changes from baseline to follow-up. Baseline covariates included age, sex and BMI. Association strength was estimated using odds ratios (ORs) with 95% confidence intervals (CIs). Results Baseline characteristics Of 106 enrolled children with moderate-to-severe asthma (mean age 8.7 ± 2.6 years; 74.5% male), 75.5% had comorbid allergic rhinitis and 15.1% had atopic dermatitis. Mean c-ACT was 19.61 ± 2.4, ACQ-7-IA score was 2.72 ± 1.54, and pre-BD FEV 1 was 1.54 ± 0.54 L at baseline. Patients averaged 2.0 ± 1.1 asthma exacerbations in the previous year (Table 1 ). Table 1 Demographic and Clinical Characteristics of the study cohort at baseline Characteristic All patients N = 106 General Characteristic Male, n (%) 79 (74.53%) Age, years, mean ± SD 8.71 ± 2.57 BMI, kg/m², mean ± SD 17.17 ± 3.50 Comorbidities, n (%) Atopic dermatitis 16 (15.09%) Allergic rhinitis 80 (75.47%) Asthma duration, months, median (IQR) 39.00 (24.00, 72.00) c-ACT score, points, mean ± SD 19.61 ± 2.40 ACQ-7-IA score, points, mean ± SD 2.72 ± 1.54 Asthma exacerbations in past year, times, mean ± SD 2.03 ± 1.10 ≥ 1 hospitalization for exacerbation, n (%) 27 (25.47%) Pulmonary function test Pre-BD FEV 1 , L, mean ± SD 1.54 ± 0.54 Pre-BD FEV 1 % predicted, %, mean ± SD Pre-BD FEV 1 /FVC, %, mean ± SD 85.93 ± 13.38 76.01 ± 9.75 Pre-BD FEV 1 /FVC% predicted, %, mean ± SD 88.96 ± 11.13 Small airway function MMEF 25/75 , L/s, mean ± SD 1.30 ± 0.60 MMEF 25/75 % predicted, %, mean ± SD 57.20 ± 21.31 MEF 25 , L/s, mean ± SD 0.64 ± 0.35 MEF 25 % predicted, %, mean ± SD 48.28 ± 21.05 MEF 50 , L/s, mean ± SD 1.53 ± 0.67 MEF 50 % predicted, %, mean ± SD 58.68 ± 21.66 Small airway dysfunction, n (%) 67 (63.21%) Type 2 inflammation biomarkers FeNO, ppb, median (IQR) 26.00 (13.00, 46.50) Serum total IgE, IU/mL, median (IQR) 721.34 (294.75, 1,330.94) Blood eosinophil count, ×10 6 /L, median (IQR) 610.00 (400.00, 840.00) Sputum eosinophil percentage, %, median (IQR) 6.00 (2.50, 21.50) Changes of the percentage of SAD and Changes in small airway function indicators Following dupilumab initiation, the proportion of SAD patients significantly decreased from 63.2% to 36.8% at 3 months ( p < 0.001) and continued to decline progressively to 16.0%, 9.4% and 3.8% at 6, 9, and 12 months (all p -values < 0.001) (Fig. 1 a). All small airway indicators improved significantly from baseline (all p -values < 0.001). MMEF 25/75 % predicted improved from 57.2 ± 21.3% to 72.6 ± 22.1%, 75.8 ± 20.3%, 76.1 ± 18.0%, and 77.9 ± 19.1% at 3, 6, 9, and 12 months respectively. MEF 25 % predicted rose from 48.3 ± 21.1% from to 62.9 ± 21.8%, 66.4 ± 20.0%, 66.4 ± 19.2%, and 69.7 ± 25.8%. And MEF 50 % predicted increased from 58.7 ± 21.7% to 72.8 ± 23.6%, 76.1 ± 20.2%, 77.5 ± 19.2%, and 76.8 ± 19.6% (Fig. 1 b-d). Changes in type 2 inflammation biomarkers All type 2 inflammation biomarkers declined significantly after treatment. FeNO decreased from 26.00 (13.00, 46.50) ppb at baseline to 12.00 (8.00, 19.00) ppb at 3 months, then stabilized between 10.00-12.50 ppb through 12 months. Serum total IgE fell from 721.34 (294.75, 1330.94) IU/mL to 317.00 (115.16, 706.96) IU/mL, 162.81 (90.33, 297.70) IU/mL, 135.07 (52.59, 249.87) IU/mL and 118.09 (60.56, 201.60) IU/mL at 3, 6, 9 and 12 months. Blood eosinophil count dropped from 610.00 (400.00, 840.00) × 10 6 /L to 500.00 (270.00, 700.00) ×10 6 /L, 385.00 (260.00, 675.00) ×10 6 /L, 350.00 (170.00, 550.00) ×10 6 /L and 375.00 (285.00, 570.00) ×10 6 /L. And sputum eosinophil percentage declined from 6.00 (2.50, 21.50) % to 1.25 (0.50, 3.56) %, 1.00 (0.00, 2.00) %, 0.50 (0.00, 1.50) % and 1.00 (0.02, 3.13) %. Most improvements occurred within three months and maintained thereafter (Fig. 2 ). Changes in annualized asthma exacerbation, pre-BD FEV 1 , asthma symptom score and rescue medication use Following dupilumab initiation, the annualized asthma exacerbation rate significantly decreased from 2.03 ± 1.10 at baseline to 0.37 ± 1.32 at 6 months ( p < 0.001), with hospitalization rates decreasing from 25.5% to ≤ 1%. Pre-BD FEV 1 improved from 85.9% to 97.6% predicted at 6 months ( p < 0.001). Disease control also showed sustained improvement: C-ACT scores increased from 19.61 ± 2.40 to 26.32 ± 1.39, while ACQ-7-IA scores decreased from 2.72 ± 1.54 to 1.58 ± 0.67, indicating fewer patients with poor control ( p < 0.001) (Table 2 ). Furthermore, rescue medication use reduced substantially: SABA from 31.1% to 4.0%, SAMA from 18.9% to 1.0%, and oral corticosteroid (OCS) from 10.4% to 0.0% at 6 months. Table 2 Changes in annualized asthma exacerbation, pre-BD FEV 1 and asthma symptom score and rescue medication use Characteristic Baseline 6 months p -value 1 Annualized asthma exacerbation Annualized asthma exacerbation, times, mean ± SD 2.03 ± 1.10 0.37 ± 1.32 < 0.001 Pre-BD FEV 1 Pre-BD FEV1, L, mean ± SD 1.54 ± 0.54 1.92 ± 0.57 < 0.001 Pre-BD FEV1% predicted, %, mean ± SD 85.93 ± 13.38 97.64 ± 10.51 < 0.001 Asthma symptom score C-ACT, mean ± SD 19.61 ± 2.40 26.32 ± 1.39 < 0.001 ACQ-7-IA, mean ± SD 2.72 ± 1.54 1.58 ± 0.67 < 0.001 1 Wilcoxon rank-sum test; Chi-square test of independence. Factors influencing SAD improvement Multivariable analysis showed that among the indicators (Δ) with significant changes during follow-up, Δ Pre-BD FEV₁/FVC predicted (OR = 1.27, 95% CI: 1.09–1.51, p = 0.003) and Δ FeNO (OR = 1.02, 95% CI: 1.00-1.06, p = 0.049) were statistically significantly positively associated with improvement in small airway dysfunction. In addition, the higher the baseline value of c-ACT score, the higher the probability of SAD improvement at follow-up (OR = 1.52, 95% CI: 1.19–2.05, p < 0.001), and the lower the baseline value of ACQ-7-IA score, the higher the probability of SAD improvement at follow-up (OR = 0.69, 95% CI: 0.50–0.91, p = 0.010). (Table 3 ). Table 3 Factors influencing SAD improvement Variable OR 95% CI p -value 1 Type 2 inflammation biomarkers Δ FeNO, ppb 1.02 1.00, 1.06 0.049 Δ Serum total IgE, IU/mL 1.00 0.99, 1.00 0.157 Δ Blood eosinophil count, ×10 6 /L 1.00 0.98, 1.01 0.576 Δ Sputum eosinophil percentage, % 1.01 0.97, 1.07 0.640 Annualized asthma exacerbation Annualized asthma exacerbation, times 1.02 0.67, 1.62 0.913 Δ Annualized asthma exacerbation, times 0.81 0.55, 1.18 0.281 Pulmonary function test Δ Pre-BD FEV 1 , L 0.99 0.97, 1.01 0.297 Δ Pre-BD FEV 1 % predicted, % 0.98 0.94, 1.02 0.292 Δ Pre-BD FEV 1 /FVC, % 0.96 0.90, 1.03 0.204 Δ Pre-BD FEV 1 /FVC% predicted, % 1.27 1.09, 1.51 0.003 Asthma symptom score c-ACT score, points 1.52 1.19, 2.05 < 0.001 Δ c-ACT score, points 1.02 0.66, 1.47 0.905 ACQ-7-IA score, points 0.69 0.50, 0.91 0.010 Δ ACQ-7-IA score, points 1.76 0.44, 7.49 0.416 1 Wald test. Δ indicates the change in each marker during follow-up Characteristics of patients with improvement in small airway function and those without improvement in small airway function In this study, we further compared baseline characteristics between patients who demonstrated SAD improvement and those who did not (Table 4 ). Overall, patients in the “improved” group exhibited a more favorable baseline clinical profile. They had better asthma control, reflected by higher c-ACT scores ( p < 0.001) and lower ACQ-7-IA scores ( p = 0.004). Baseline pulmonary function was also less impaired in this group, with higher values for pre-BD FEV₁% predicted ( p < 0.001) and FEV₁/FVC ( p < 0.001), as well as consistently better small-airway indicators including MMEF 25/75 % predicted, MEF 25 % predicted, and MEF 50 % predicted (all p < 0.001). These differences suggest that children with milder baseline airflow limitation and better controlled type 2–driven asthma symptoms were more likely to experience subsequent recovery of small-airway function under dupilumab treatment. Table 4 Baseline clinical characteristics of patients with improvement in small airway function and those without improvement in small airway function Characteristic Improved N = 82 1 Not improved N = 24 1 p -value 2 General Characteristic Male, n (%) 61 (74.39%) 18 (75.00%) 0.952 Age, years, mean ± SD 8.55 ± 2.65 9.25 ± 2.21 0.208 BMI, kg/m², mean ± SD 16.85 ± 2.87 18.26 ± 5.04 0.637 Comorbidities, n (%) Atopic dermatitis 11 (13.41%) 5 (20.83%) 0.352 Allergic rhinitis 66 (80.49%) 14 (58.33%) 0.027 Asthma duration, months, median (IQR) 36.00 (12.00, 72.00) 48.00 (31.5, 79.00) 0.095 c-ACT score, points, mean ± SD 20.09 ± 1.86 18.00 ± 3.27 < 0.001 ACQ-7-IA score, points, mean ± SD 2.50 ± 1.45 3.46 ± 1.64 0.004 Asthma exacerbations in past year, times, mean ± SD 2.05 ± 1.15 1.96 ± 0.91 0.981 \(\:\ge\:\) 1 hospitalization for exacerbation, n (%) 1.09 ± 0.29 1.00 ± 0.00 0.599 Pulmonary function test Pre-BD FEV1, L, mean ± SD 1.56 ± 0.55 1.49 ± 0.49 0.853 Pre-BD FEV1% predicted, %, mean ± SD 88.70 ± 12.55 76.47 ± 11.90 < 0.001 Pre-BD FEV1/FVC, %, mean ± SD 78.38 ± 8.73 67.90 ± 8.78 < 0.001 Pre-BD FEV1/FVC% predicted, %, mean ± SD 91.63 ± 10.03 79.83 ± 9.97 < 0.001 Small airway function MMEF 25/75 , L/s, mean ± SD 1.39 ± 0.62 0.96 ± 0.36 0.001 MMEF 25/75 % predicted, %, mean ± SD 62.34 ± 20.81 39.65 ± 11.44 < 0.001 MEF 25 , L/s, mean ± SD 0.70 ± 0.37 0.45 ± 0.17 < 0.001 MEF 25 % predicted, %, mean ± SD 53.09 ± 20.96 31.84 ± 10.52 < 0.001 MEF 50 , L/s, mean ± SD 1.64 ± 0.69 1.15 ± 0.44 0.002 MEF 50 % predicted, %, mean ± SD 63.75 ± 21.37 41.35 ± 11.36 < 0.001 Type 2 inflammation biomarkers FeNO, ppb, median (IQR) 26.00 (13.00, 49.00) 26.00 (11.50, 43.00) 0.706 Serum total IgE, IU/mL, median (IQR) 743.89 (292.67, 1,303.00) 506.29 (285.00, 1,525.13) 0.766 Blood eosinophil count, ×10 6 /L, median (IQR) 625.00 (400.00, 850.00) 535.00 (405.00, 770.00) 0.394 Sputum eosinophil percentage%, median (IQR) 7.25 (3.50, 25.75) 4.50 (1.50, 13.00) 0.121 1 n (%) 2 Chi-square test for independence; Wilcoxon rank-sum test; Fisher's exact test Discussion In this study, dupilumab significantly reduces the percentage of pediatric asthma patients with SAD and improves small airway function indicators. This result aligns with previous studies. In the VESTIGE study, dupilumab significantly reduced SAD prevalence in adult patients with moderate-to-severe asthma[11]. While another study with 25 pediatric patients showed similar trends in lung function parameters including small airways[13]. Our real-world data, derived from a larger pediatric cohort of patients with asthma, corroborated significant improvements in SAD. After adding dupilumab to the baseline ICS–LABA therapy in children with asthma, beyond the reduction in SAD prevalence, all small-airway function indicators—including MMEF 25/75 % predicted, MEF 25 % predicted, and MEF 50 % predicted—showed substantial and sustained improvement. These findings corroborate and expand upon the limited existing pediatric data on dupilumab and small-airway function. In the phase-III VOYAGE trial, MMEF 25/75 significantly improved by 0.60–0.65 L/s in children (6–11 years) with uncontrolled moderate-to-severe asthma after 52 weeks of dupilumab treatment versus placebo[10]. Improvement in small-airway function has clinical significance, as reduced MMEF 25/75 independently predicts future exacerbations regardless of FEV 1 [14]. Our cohort showed halved exacerbation rates and decreased rescue medication use, suggesting that early restoration of peripheral airway function translates into concrete disease-modifying benefits. Moreover, enhanced small-airflow may also enhance inhaled-drug deep delivery, creating a positive cycle that improves asthma control and reduces systemic therapy needs. Type 2 inflammation biomarkers also declined significantly following treatment. The rapid reduction in FeNO, together with decreases in serum IgE, blood eosinophils, and sputum eosinophils, aligns with the known pharmacologic mechanism of dupilumab. Blockade of IL-4Rα inhibits both IL-4- and IL-13-mediated processes, reducing eosinophilic inflammation, mucus hypersecretion, and airway epithelial nitric oxide production—factors intricately linked to small-airway narrowing and remodeling[15, 16]. Notably, sputum eosinophil percentage, an important indicator that had been less reported in other pediatric asthma studies, was systematically reported in this study. The results showed that the sputum eosinophil percentage significantly decreased after the treatment with dupilumab from 6.00 (2.50, 21.50) % at baseline to 1.00 (0.02, 3.13) % at 12 months, with a highly significant extent and speed of the decrease, and was maintained at a low level after 3 months. Compared with the blood eosinophil count, sputum eosinophils can more directly reflect the local airway type 2 inflammatory state. Although the decrease in sputum eosinophils in this study was consistent with the downward trend in blood eosinophil count, the sputum eosinophil percentage decreased rapidly to near normal levels (< 2.5%) after treatment, whereas the blood eosinophil count tended to decrease more slowly after treatment, suggesting that dupilumab might preferentially and effectively inhibit local inflammatory cell infiltration in the airways[17]. Multivariable logistic regression model found that the rapid and sustained increases in MMEF 25/75 % predicted, MEF 25 % predicted and MEF 50 % predicted values corresponded with the sharp reduction in FeNO. This aligns with recent findings showing negative correlations between MMEF 25/75 % predicted, MEF 25 % predicted, MEF 50 % predicted and FeNO 200 in 248 asthmatic children (r = − 0.46 to − 0.49, p < 0.001)[18].Besides, another study observed a significant positive correlation between increases in FeNO and SAD (r = 0.52, p < 0.0001)[19]. These results implicate an IL-4/IL-13–driven type 2 inflammation axis as the primary therapeutic target. Dupilumab also attenuates IL-13–driven sub-epithelial fibrosis and airway smooth-muscle hypertrophy, key components of small-airway remodeling[20]. The observed association between FeNO reduction and MMEF 25/75 improvement (OR 1.02 per 1-ppb decrease, 95% CI 1.00–1.06) is consistent with the hypothesis that reduced epithelial nitric-oxide synthase activity—potentially through attenuated IL-13–STAT6 signaling—may contribute to improved peripheral airway function[21]. Emerging evidence further suggests a neuro-immune interface: IL-4 and IL-13 enhance transient receptor potential vanilloid-1 (TRPV1) expression on airway sensory nerves, causing bronchial hyper-reactivity[22]. By inhibiting these pathways, dupilumab may indirectly improve small-airway compliance and reduce dynamic collapse during forced expiration, achieving comprehensive improvement across all indicators. In addition, it was found by comparing baseline characteristics of patients with improvement in small airway function and those without improvement in small airway function in this study that patients in the improvement group showed better asthma symptom control (higher c-ACT scores, and lower ACQ-7-IA scores) and a relatively milder degree of lung function impairment (higher Pre-BD FEV₁% predicted, Pre-BD FEV₁/FVC, etc.) at baseline. These findings strongly suggest that dupilumab may achieve a better therapeutic effect by intervening in the early stage of the disease, i.e., before irreversible structural remodeling occurred in the small airways. In patients with mild baseline symptoms and mild airway obstruction, the pathological changes of small airways may still be in a stage dominated by inflammation and reversible dysfunction rather than remodeling stage of serious fibrosis or smooth muscle hyperplasia. Therefore, the response to the treatment with dupilumab was more significant. Conversely, in patients in the non-improvement group with severe baseline symptoms and poor lung function, the small airways may have undergone a longer remodeling process, making functional recovery more difficult even after effective suppression of type 2 inflammation. This emphasizes the importance of early biomarker assessment and consideration of early intervention with biologics such as dupilumab in the management of asthma in children with moderate-to-severe asthma, in order to maximize preservation and recovery of small airway function before irreversible airway remodeling occurs, thereby altering the long-term prognosis of the disease. This study has some limitations. The retrospective design and limited sample size may introduce bias. Prospective, further multicenter studies with larger pediatric populations and extended follow-up are needed to validate these findings and to explore dupilumab’s role in combination therapies and younger populations. Conclusion Dupilumab substantially improves SAD in children with moderate-to-severe asthma by rapidly reducing type 2 inflammation biomarkers. A decrease in FeNO may serve as a potential predictive indicator for reflecting improvements in small airway function. Declarations Acknowledgments The authors acknowledge the investigators, study coordinators and most of all the patients who are participated in this study. Authors’ contributions Study design and hypothesis generation: LS, LZ. Data acquisition, analysis, or interpretation: LS, LC, KY, YY, and FG. Chart review and manuscript preparation: LS, LZ, and JZ. Critical revision: NZ and JZ. Funding was obtained by LS. All authors read and approved the final manuscript. Funding This study was supported by State Key Laboratory of Respiratory Disease (Special Project for Clinical and Epidemiological Research, Project No. SKLRD-L-202603). Data availability The datasets analyzed for the current study are available from the corresponding author on reasonable request. Declarations Ethics approval and consent to participate The Institutional Ethical Review Board of the First Affiliated Hospital of Guangzhou Medical University approved the study (No. ES-2024-001-01). Consent for publication Not applicable. Competing interests None. Clinical trial number Not applicable. References Venkatesan, P., 2025 GINA report for asthma. Lancet Respir Med, 2025. Dunican, E.M., et al., Mucus plugs in patients with asthma linked to eosinophilia and airflow obstruction. J Clin Invest, 2018. 128 (3): p. 997-1009. Gao, F., et al., Small airway dysfunction links asthma exacerbations with asthma control and health-related quality of life. Respir Res, 2024. 25 (1): p. 306. Usmani, O.S., et al., The prevalence of small airways disease in adult asthma: A systematic literature review. Respir Med, 2016. 116 : p. 19-27. Riley, C.M., 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): p. e0145476. Long, J.W. and Y.L. Jiang, Association of Small Airway Functional Indices With Respiratory Symptoms and Comorbidity in Asthmatics: A National Cross-Sectional Study. J Clin Med Res, 2024. 16 (5): p. 220-231. Tamura, K., et al., Mucus Plugs and Small Airway Dysfunction in Asthma, COPD, and Asthma-COPD Overlap. Allergy Asthma Immunol Res, 2022. 14 (2): p. 196-209. Le Floc'h, A., et al., Dual blockade of IL-4 and IL-13 with dupilumab, an IL-4Rα antibody, is required to broadly inhibit type 2 inflammation. Allergy, 2020. 75 (5): p. 1188-1204. Gandhi, N.A., G. Pirozzi, and N.M.H. Graham, Commonality of the IL-4/IL-13 pathway in atopic diseases. Expert Rev Clin Immunol, 2017. 13 (5): p. 425-437. Bacharier, L.B., et al., Dupilumab in Children with Uncontrolled Moderate-to-Severe Asthma. N Engl J Med, 2021. 385 (24): p. 2230-2240. Washko, G.R., et al., Effect of dupilumab on small airways measured by airway oscillometry in VESTIGE. J Allergy Clin Immunol, 2025. 156 (5): p. 1209-1218. Xiao, D., et al., Prevalence and risk factors of small airway dysfunction, and association with smoking, in China: findings from a national cross-sectional study. Lancet Respir Med, 2020. 8 (11): p. 1081-1093. Shi, T., et al., The assessment of dupilumab in children with moderate-to-severe asthma and comorbid type 2 inflammatory diseases. BMC Pulm Med, 2024. 24 (1): p. 607. Lazova, S., et al., MMEF(25-75) may predict significant BDR and future risk of exacerbations in asthmatic children with normal baseline FEV(1). Int J Physiol Pathophysiol Pharmacol, 2022. 14 (1): p. 33-47. LaPorte, S.L., et al., Molecular and structural basis of cytokine receptor pleiotropy in the interleukin-4/13 system. Cell, 2008. 132 (2): p. 259-72. Gandhi, N.A., et al., Targeting key proximal drivers of type 2 inflammation in disease. Nat Rev Drug Discov, 2016. 15 (1): p. 35-50. Peltrini, R., et al., Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma. Am J Respir Crit Care Med, 2024. 210 (9): p. 1101-1112. Zhang, L., et al., Identification and treatment of persistent small airway dysfunction in paediatric patients with asthma: a retrospective cohort study. BMC Pulm Med, 2024. 24 (1): p. 94. Cottini, M., et al., Small airway dysfunction mediates the relationship between Fractional Exhaled Nitric Oxide and asthma control. Ann Allergy Asthma Immunol, 2025. 134 (5): p. 548-555.e4. Nakagome, K. and M. Nagata, The Possible Roles of IL-4/IL-13 in the Development of Eosinophil-Predominant Severe Asthma. Biomolecules, 2024. 14 (5). Escamilla-Gil, J.M., M. Fernandez-Nieto, and N. Acevedo, Understanding the Cellular Sources of the Fractional Exhaled Nitric Oxide (FeNO) and Its Role as a Biomarker of Type 2 Inflammation in Asthma. Biomed Res Int, 2022. 2022 : p. 5753524. Choi, J.Y., et al., TRPV1 Blocking Alleviates Airway Inflammation and Remodeling in a Chronic Asthma Murine Model. Allergy Asthma Immunol Res, 2018. 10 (3): p. 216-224. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8288806","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":558831804,"identity":"6b0b2e7e-5c7f-4f06-8da9-e54e59dbbe79","order_by":0,"name":"Lihong Sun","email":"","orcid":"","institution":"First Affiliated Hospital of Guangzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lihong","middleName":"","lastName":"Sun","suffix":""},{"id":558831805,"identity":"4ef49101-d70d-4f3c-998c-8432c4146f3e","order_by":1,"name":"Lijun Zeng","email":"","orcid":"","institution":"First Affiliated Hospital of Guangzhou 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14:11:20","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":91214,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8288806/v1/1cff215b1f859f8eeabdd270.html"},{"id":98322452,"identity":"9c9435d6-d2f2-494d-a591-098247a75e10","added_by":"auto","created_at":"2025-12-16 14:11:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84271,"visible":true,"origin":"","legend":"\u003cp\u003eLongitudinal changes of percentage of patients with small airway dysfunction and changes in small airway function indicators following dupilumab intervention over a 12-month period. a) Percentage of patients with small airway dysfunction b) MMEF\u003csub\u003e25-75\u003c/sub\u003e% predicted, maximum mid-expiratory flow (between 25% and 75% of FVC) of the predicted value, c) MEF\u003csub\u003e25\u003c/sub\u003e% predicted, maximal expiratory flow at 75% of FVC of the predicted value, d) MEF\u003csub\u003e50\u003c/sub\u003e% predicted, maximal expiratory flow at 50% of FVC of the predicted value. M, months.\u003c/p\u003e\n\u003cp\u003e*All values represent mean percent predicted (± error bars). The consistent upward trend across all parameters demonstrates significant improvement in small airway function over time, with the most pronounced gains occurring within the first 3-6 months of intervention.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8288806/v1/aa032165d3a0be208b00ea1d.png"},{"id":98322454,"identity":"9e4dd8df-b9ea-4af8-b320-2e4747d51474","added_by":"auto","created_at":"2025-12-16 14:11:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":71009,"visible":true,"origin":"","legend":"\u003cp\u003eLongitudinal changes in type 2 inflammation biomarkers following dupilumab intervention. The box plots (a-d) demonstrate the temporal evolution of four key type 2 inflammation biomarkers over 12 months of treatment. a) Fractional exhaled nitric oxide (FeNO) levels (ppb). b) Serum total immunoglobulin E (IgE) concentrations (IU/mL). c) Blood eosinophil counts (×10\u003csup\u003e6\u003c/sup\u003e/L). d) Sputum eosinophil percentage (%). M, months.\u003c/p\u003e\n\u003cp\u003e*All four biomarkers showed significant reduction from baseline at all follow-up time points (3, 6, 9, and 12 months). Statistical significance is indicated as follows: ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01. Boxes represent interquartile range (25th-75th percentile), horizontal lines within boxes indicate median values, and whiskers extend to 1.5× interquartile range. Outliers are shown as individual points.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8288806/v1/434fb56a57d278bc7db9381a.png"},{"id":102295110,"identity":"c95a3794-e4f6-4a69-8511-e18c395f175c","added_by":"auto","created_at":"2026-02-10 10:08:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1348673,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8288806/v1/4bc06dc5-0030-45f2-846c-7fbd44de849d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dupilumab improves the small airway dysfunction in children with moderate to severe asthma: A retrospective analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAsthma is a chronic airway inflammatory disease affecting the entire respiratory tract, from the central to peripheral airway[1]. Inflammation, mucus hypersecretion, and structural remodeling in the distal bronchioles contribute to small airway dysfunction (SAD) [2]. SAD is closely associated with poor asthma control, increased exacerbation risk, reduced quality of life[3] and is prevalent even in mild asthma[4]. Despite its clinical relevance, SAD is often insufficiently managed because conventional inhaled therapies\u0026mdash;primarily inhaled corticosteroids (ICS) combined with long-acting β₂-agonists (LABA) or leukotriene receptor antagonists (LTRA)\u0026mdash;achieve limited drug deposition in the small airways and incompletely suppress distal airway inflammation[1].\u003c/p\u003e \u003cp\u003eTo better understand the pathological changes in small airways, the key assessment indicators of SAD include MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, MEF\u003csub\u003e25\u003c/sub\u003e% predicted and MEF\u003csub\u003e50\u003c/sub\u003e% predicted. Reduced MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted serves as an independent biomarker for severe asthma, correlated with biomarkers of type 2 inflammation, including blood eosinophilia and FeNO, and is associated with severe phenotypes and enhanced bronchial hyperreactivity[5]. Increasing evidence indicates that SAD is not merely a mechanical phenomenon but is strongly driven by type 2 inflammation. Cytokines such as interleukin (IL)-4, IL-5, and IL-13 promote eosinophilic infiltration, mucus plugging, goblet-cell metaplasia, epithelial damage, airway wall edema, and subepithelial fibrosis in the distal airways. These type 2 inflammation -driven pathological processes narrow the small airway lumen, reduce airway compliance, and contribute to persistent reductions in expiratory flow\u0026mdash;hallmark features of SAD. Furthermore, type 2 biomarkers, including blood eosinophils, sputum eosinophils, serum immunoglobulin E (IgE), and fractional exhaled nitric oxide (FeNO), are associated with small-airway physiological indices. These biomarkers are increasingly applied in clinical practice to aid in identifying T2-high phenotypes, estimating exacerbation risk, and informing biologic therapy selection.[6, 7]. This growing recognition of small airway inflammation as a therapeutic target has spurred interest in biologics with potential distal airway effects.\u003c/p\u003e \u003cp\u003eGrowing recognition of the contribution of type 2 inflammation to distal airway pathology has spurred interest in biologics capable of modulating these pathways. Dupilumab, a fully human monoclonal antibody targeting IL-4 receptor α, inhibits both IL-4 and IL-13 signaling[8, 9], thereby suppressing multiple components of type 2 inflammation relevant to SAD. Unlike ICS-based therapy, whose anti-inflammatory effect in the small airways is limited by particle size and deposition characteristics, dupilumab exerts systemic and airway-wide immunomodulatory effects that extend to the peripheral bronchioles. Clinical trials have demonstrated its efficacy in reducing exacerbations and improving lung function in moderate-to-severe asthma [10], and study in adult patients have suggest a beneficial effect on SAD specifically[11]. However, evidence in pediatric patients\u0026mdash;particularly within real-world settings\u0026mdash;remain insufficiently characterized.\u003c/p\u003e \u003cp\u003eThis retrospective study aimed to assess dupilumab\u0026rsquo;s effect on small airway function in Chinese children with uncontrolled moderate-to-severe asthma.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eThis retrospective study analyzed electronic medical record data from the Guangzhou Institute of Respiratory Health for patients who started dupilumab treatment between January 2022 and March 2025. Included patients were aged 6\u0026ndash;14 with uncontrolled asthma despite medium-to-high dose ICS treatment and type 2 inflammation characteristics. Exclusion criteria included dupilumab use for non-asthma conditions, concurrent biologic therapies, and sublingual or subcutaneous desensitization treatments. The Institutional Ethical Review Board of the First Affiliated Hospital of Guangzhou Medical University approved the study (No. ES-2024-001-01). Since it was an anonymized and retrospective research, written informed consent was waived in accordance with the Declaration of Helsink. Clinical trial number: not applicable.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe date of the first dupilumab injection was designated the index date. The observation period spanned from the index date to each patient's final visit. Data extracted from the routine medical care included demographics, clinical characteristics, pulmonary function test results (including small airway function indicators MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, MEF\u003csub\u003e25\u003c/sub\u003e% predicted and MEF\u003csub\u003e50\u003c/sub\u003e% predicted), serum biochemical indicators, asthma scale scores, treatment patterns. All data came from the Hospital Information System/Laboratory Information System. The Children-Asthma Control Test (c-ACT) and Asthma Control Questionnaire 7 Interviewer-Administered (ACQ-7-IA) measure asthma control on a 0\u0026ndash;6 scale (totally controlled to severely uncontrolled), with a 0.5 change considered clinically significant. We got the permission to use ACQ-7-IA form from the author via \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.qoltech.co.uk/index.htm\u003c/span\u003e\u003cspan address=\"http://www.qoltech.co.uk/index.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The c-ACT scores form was obtained from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://eprovide.mapi-trust.org/instruments/childhood-asthma-control-test\u003c/span\u003e\u003cspan address=\"https://eprovide.mapi-trust.org/instruments/childhood-asthma-control-test\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The Ethics Committee of the Guangzhou Institute of Respiratory Health approved the study protocol (Ethics Number: ES-2024-001-01).\u003c/p\u003e\n\u003ch3\u003eStudy Endpoints\u003c/h3\u003e\n\u003cp\u003eThe primary endpoint of this study was the change in the percentage of patients with SAD (defined as at least two of MMEF\u003csub\u003e25/75\u003c/sub\u003e, MEF\u003csub\u003e25\u003c/sub\u003e or MEF\u003csub\u003e50\u003c/sub\u003e below 65% of predicted values)[12] from baseline to 6 months.\u003c/p\u003e \u003cp\u003eSecondary endpoints encompassed several domains, including: 1) The change of the percentage of patients with SAD from baseline to different follow-up timepoints (3, 9 and 12 months) and changes in small-airway function indicators (MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, MEF\u003csub\u003e25\u003c/sub\u003e% predicted and MEF\u003csub\u003e50\u003c/sub\u003e% predicted) from baseline to different follow-up timepoints (3, 6, 9 and 12 months); 2) Changes in type 2 inflammation biomarkers (FeNO, serum total IgE, blood eosinophil count, and sputum eosinophil percentage) from baseline to different follow-up timepoints (3, 6, 9 and 12 months); 3) Changes in annualized asthma exacerbation rate (calculated as the total number of exacerbations divided by total person-years of follow-up), prebronchodilator forced expiratory volume in 1 second (pre-BD FEV\u003csub\u003e1\u003c/sub\u003e), percentage of predicted prebronchodilator FEV\u003csub\u003e1\u003c/sub\u003e (pre-BD FEV\u003csub\u003e1\u003c/sub\u003e% predicted), asthma symptom scores (c-ACT and ACQ-7-IA) and rescue medication use from baseline to 6 months; 4) Factors influencing the SAD improvement; 5) Comparison in characteristics at baseline between patients with improvement in small airway function and those without improvement in small airway function.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using R version 4.2.3 (R Foundation for Statistical Computing, Vienna, Austria). Continuous variables with a normal distribution are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), whereas non-normally distributed variables are presented as median and interquartile range (IQR; Q1\u0026ndash;Q3). Between-group differences were assessed using Student\u0026rsquo;s t-test for normally distributed variables and the Wilcoxon rank-sum test for non-normally distributed variables. For comparisons across multiple time points, one-way analysis of variance (ANOVA) was applied to normally distributed data, while the Kruskal\u0026ndash;Wallis H test was used for non-normally distributed data. Categorical variables are summarized as frequencies and percentages, with group comparisons performed using the Chi-square test or Fisher\u0026rsquo;s exact test, as appropriate. All statistical tests were two-sided, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered indicative of statistical significance. Missing data were not imputed; analyses were restricted to cases with complete information for the variables of interest.\u003c/p\u003e \u003cp\u003eMultivariable logistic regression was used to assess the association between SAD improvement and type 2 inflammation biomarkers, asthma symptom scores, or lung function parameters. SAD improvement was defined as the first follow-up visit at which the patient no longer met the SAD diagnostic criteria. Patients who did not meet the improvement criteria at their final study visit were classified as non-improvement cases. For changes in test indicators, the follow-up data of patients in the improvement group were taken from the results of the last test before the improvement of small airway dysfunction; data of the last follow-up test during the observation period of the study were used for patients in the non-improvement group. The association between SAD improvement and these changes was analyzed using the difference between follow-up and baseline values (Δ\u0026thinsp;=\u0026thinsp;follow-up value - baseline value). For the frequency of asthma exacerbations, C-ACT scores, and ACQ-7-IA scores, which reflected asthma severity, the association with SAD improvement was examined both for baseline values and for changes from baseline to follow-up. Baseline covariates included age, sex and BMI. Association strength was estimated using odds ratios (ORs) with 95% confidence intervals (CIs).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eBaseline characteristics\u003c/h2\u003e\n \u003cp\u003eOf 106 enrolled children with moderate-to-severe asthma (mean age 8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6 years; 74.5% male), 75.5% had comorbid allergic rhinitis and 15.1% had atopic dermatitis. Mean c-ACT was 19.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4, ACQ-7-IA score was 2.72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54, and pre-BD FEV\u003csub\u003e1\u003c/sub\u003e was 1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54 L at baseline. Patients averaged 2.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 asthma exacerbations in the previous year (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic and Clinical Characteristics of the study cohort at baseline\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;106\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral Characteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79 (74.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, years, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.71\u0026thinsp;\u0026plusmn;\u0026thinsp;2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI, kg/m\u0026sup2;, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17.17\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComorbidities, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtopic dermatitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16 (15.09%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllergic rhinitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80 (75.47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsthma duration, months, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39.00 (24.00, 72.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ec-ACT score, points, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACQ-7-IA score, points, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsthma exacerbations in past year, times, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;1 hospitalization for exacerbation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27 (25.47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary function test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV\u003csub\u003e1\u003c/sub\u003e, L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV\u003csub\u003e1\u003c/sub\u003e% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003cp\u003ePre-BD FEV\u003csub\u003e1\u003c/sub\u003e/FVC, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.93\u0026thinsp;\u0026plusmn;\u0026thinsp;13.38\u003c/p\u003e\n \u003cp\u003e76.01\u0026thinsp;\u0026plusmn;\u0026thinsp;9.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV\u003csub\u003e1\u003c/sub\u003e/FVC% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88.96\u0026thinsp;\u0026plusmn;\u0026thinsp;11.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmall airway function\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMMEF\u003csub\u003e25/75\u003c/sub\u003e, L/s, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.20\u0026thinsp;\u0026plusmn;\u0026thinsp;21.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e25\u003c/sub\u003e, L/s, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e25\u003c/sub\u003e% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.28\u0026thinsp;\u0026plusmn;\u0026thinsp;21.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e50\u003c/sub\u003e, L/s, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e50\u003c/sub\u003e% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58.68\u0026thinsp;\u0026plusmn;\u0026thinsp;21.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall airway dysfunction, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67 (63.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eType 2 inflammation biomarkers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeNO, ppb, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.00 (13.00, 46.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum total IgE, IU/mL, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e721.34 (294.75, 1,330.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood eosinophil count, \u0026times;10\u003csup\u003e6\u003c/sup\u003e/L, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e610.00 (400.00, 840.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSputum eosinophil percentage, %, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.00 (2.50, 21.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eChanges of the percentage of SAD and Changes in small airway function indicators\u003c/h3\u003e\n\u003cp\u003eFollowing dupilumab initiation, the proportion of SAD patients significantly decreased from 63.2% to 36.8% at 3 months (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and continued to decline progressively to 16.0%, 9.4% and 3.8% at 6, 9, and 12 months (all \u003cem\u003ep\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e\n\u003cp\u003eAll small airway indicators improved significantly from baseline (all \u003cem\u003ep\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.001). MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted improved from 57.2\u0026thinsp;\u0026plusmn;\u0026thinsp;21.3% to 72.6\u0026thinsp;\u0026plusmn;\u0026thinsp;22.1%, 75.8\u0026thinsp;\u0026plusmn;\u0026thinsp;20.3%, 76.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18.0%, and 77.9\u0026thinsp;\u0026plusmn;\u0026thinsp;19.1% at 3, 6, 9, and 12 months respectively. MEF\u003csub\u003e25\u003c/sub\u003e% predicted rose from 48.3\u0026thinsp;\u0026plusmn;\u0026thinsp;21.1% from to 62.9\u0026thinsp;\u0026plusmn;\u0026thinsp;21.8%, 66.4\u0026thinsp;\u0026plusmn;\u0026thinsp;20.0%, 66.4\u0026thinsp;\u0026plusmn;\u0026thinsp;19.2%, and 69.7\u0026thinsp;\u0026plusmn;\u0026thinsp;25.8%. And MEF\u003csub\u003e50\u003c/sub\u003e% predicted increased from 58.7\u0026thinsp;\u0026plusmn;\u0026thinsp;21.7% to 72.8\u0026thinsp;\u0026plusmn;\u0026thinsp;23.6%, 76.1\u0026thinsp;\u0026plusmn;\u0026thinsp;20.2%, 77.5\u0026thinsp;\u0026plusmn;\u0026thinsp;19.2%, and 76.8\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6% (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb-d).\u003c/p\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eChanges in type 2 inflammation biomarkers\u003c/h2\u003e\n \u003cp\u003eAll type 2 inflammation biomarkers declined significantly after treatment. FeNO decreased from 26.00 (13.00, 46.50) ppb at baseline to 12.00 (8.00, 19.00) ppb at 3 months, then stabilized between 10.00-12.50 ppb through 12 months. Serum total IgE fell from 721.34 (294.75, 1330.94) IU/mL to 317.00 (115.16, 706.96) IU/mL, 162.81 (90.33, 297.70) IU/mL, 135.07 (52.59, 249.87) IU/mL and 118.09 (60.56, 201.60) IU/mL at 3, 6, 9 and 12 months. Blood eosinophil count dropped from 610.00 (400.00, 840.00) \u0026times; 10\u003csup\u003e6\u003c/sup\u003e/L to 500.00 (270.00, 700.00) \u0026times;10\u003csup\u003e6\u003c/sup\u003e/L, 385.00 (260.00, 675.00) \u0026times;10\u003csup\u003e6\u003c/sup\u003e/L, 350.00 (170.00, 550.00) \u0026times;10\u003csup\u003e6\u003c/sup\u003e/L and 375.00 (285.00, 570.00) \u0026times;10\u003csup\u003e6\u003c/sup\u003e/L. And sputum eosinophil percentage declined from 6.00 (2.50, 21.50) % to 1.25 (0.50, 3.56) %, 1.00 (0.00, 2.00) %, 0.50 (0.00, 1.50) % and 1.00 (0.02, 3.13) %. Most improvements occurred within three months and maintained thereafter (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eChanges in annualized asthma exacerbation, pre-BD FEV\u003csub\u003e1\u003c/sub\u003e, asthma symptom score and rescue medication use\u003c/h2\u003e\n \u003cp\u003eFollowing dupilumab initiation, the annualized asthma exacerbation rate significantly decreased from 2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10 at baseline to 0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32 at 6 months (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with hospitalization rates decreasing from 25.5% to \u0026le;\u0026thinsp;1%. Pre-BD FEV\u003csub\u003e1\u003c/sub\u003e improved from 85.9% to 97.6% predicted at 6 months (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Disease control also showed sustained improvement: C-ACT scores increased from 19.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40 to 26.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39, while ACQ-7-IA scores decreased from 2.72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54 to 1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67, indicating fewer patients with poor control (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, rescue medication use reduced substantially: SABA from 31.1% to 4.0%, SAMA from 18.9% to 1.0%, and oral corticosteroid (OCS) from 10.4% to 0.0% at 6 months.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eChanges in annualized asthma exacerbation, pre-BD FEV\u003csub\u003e1\u003c/sub\u003e and asthma symptom score and rescue medication use\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e6 months\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnualized asthma exacerbation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnnualized asthma exacerbation, times, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-BD FEV\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV1, L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV1% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e85.93\u0026thinsp;\u0026plusmn;\u0026thinsp;13.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.64\u0026thinsp;\u0026plusmn;\u0026thinsp;10.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsthma symptom score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC-ACT, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACQ-7-IA, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eWilcoxon rank-sum test; Chi-square test of independence.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eFactors influencing SAD improvement\u003c/h2\u003e\n \u003cp\u003eMultivariable analysis showed that among the indicators (\u0026Delta;) with significant changes during follow-up, \u0026Delta; Pre-BD FEV₁/FVC predicted (OR\u0026thinsp;=\u0026thinsp;1.27, 95% CI: 1.09\u0026ndash;1.51, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and \u0026Delta; FeNO (OR\u0026thinsp;=\u0026thinsp;1.02, 95% CI: 1.00-1.06, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049) were statistically significantly positively associated with improvement in small airway dysfunction. In addition, the higher the baseline value of c-ACT score, the higher the probability of SAD improvement at follow-up (OR\u0026thinsp;=\u0026thinsp;1.52, 95% CI: 1.19\u0026ndash;2.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the lower the baseline value of ACQ-7-IA score, the higher the probability of SAD improvement at follow-up (OR\u0026thinsp;=\u0026thinsp;0.69, 95% CI: 0.50\u0026ndash;0.91, p\u0026thinsp;=\u0026thinsp;0.010). (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFactors influencing SAD improvement\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eType 2 inflammation biomarkers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; FeNO, ppb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00, 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.049\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Serum total IgE, IU/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99, 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Blood eosinophil count, \u0026times;10\u003csup\u003e6\u003c/sup\u003e/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98, 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Sputum eosinophil percentage, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97, 1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.640\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnualized asthma exacerbation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnnualized asthma exacerbation, times\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67, 1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.913\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Annualized asthma exacerbation, times\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55, 1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary function test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Pre-BD FEV\u003csub\u003e1\u003c/sub\u003e, L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97, 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Pre-BD FEV\u003csub\u003e1\u003c/sub\u003e% predicted, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94, 1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.292\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Pre-BD FEV\u003csub\u003e1\u003c/sub\u003e/FVC, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90, 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; Pre-BD FEV\u003csub\u003e1\u003c/sub\u003e/FVC% predicted, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09, 1.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsthma symptom score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ec-ACT score, points\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19, 2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; c-ACT score, points\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.66, 1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACQ-7-IA score, points\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50, 0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026Delta; ACQ-7-IA score, points\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.44, 7.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003csup\u003e1\u003c/sup\u003eWald test.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u0026Delta; indicates the change in each marker during follow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics of patients with improvement in small airway function and those without improvement in small airway function\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIn this study, we further compared baseline characteristics between patients who demonstrated SAD improvement and those who did not (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Overall, patients in the \u0026ldquo;improved\u0026rdquo; group exhibited a more favorable baseline clinical profile. They had better asthma control, reflected by higher c-ACT scores (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lower ACQ-7-IA scores (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004). Baseline pulmonary function was also less impaired in this group, with higher values for pre-BD FEV₁% predicted (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and FEV₁/FVC (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as consistently better small-airway indicators including MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, MEF\u003csub\u003e25\u003c/sub\u003e% predicted, and MEF\u003csub\u003e50\u003c/sub\u003e% predicted (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These differences suggest that children with milder baseline airflow limitation and better controlled type 2\u0026ndash;driven asthma symptoms were more likely to experience subsequent recovery of small-airway function under dupilumab treatment.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline clinical characteristics of patients with improvement in small airway function and those without improvement in small airway function\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eImproved\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;82\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNot improved\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;24 \u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value \u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral Characteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (74.39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (75.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.952\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, years, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.55\u0026thinsp;\u0026plusmn;\u0026thinsp;2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI, kg/m\u0026sup2;, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.26\u0026thinsp;\u0026plusmn;\u0026thinsp;5.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComorbidities, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtopic dermatitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (13.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (20.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAllergic rhinitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (80.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (58.33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsthma duration, months, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.00 (12.00, 72.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.00 (31.5, 79.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ec-ACT score, points, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACQ-7-IA score, points, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsthma exacerbations in past year, times, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\ge\\:\\)\u003c/span\u003e\u003c/span\u003e 1 hospitalization for exacerbation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary function test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV1, L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV1% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.70\u0026thinsp;\u0026plusmn;\u0026thinsp;12.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.47\u0026thinsp;\u0026plusmn;\u0026thinsp;11.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV1/FVC, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78.38\u0026thinsp;\u0026plusmn;\u0026thinsp;8.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.90\u0026thinsp;\u0026plusmn;\u0026thinsp;8.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePre-BD FEV1/FVC% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91.63\u0026thinsp;\u0026plusmn;\u0026thinsp;10.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.83\u0026thinsp;\u0026plusmn;\u0026thinsp;9.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmall airway function\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMMEF\u003csub\u003e25/75\u003c/sub\u003e, L/s, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.34\u0026thinsp;\u0026plusmn;\u0026thinsp;20.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.65\u0026thinsp;\u0026plusmn;\u0026thinsp;11.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e25\u003c/sub\u003e, L/s, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e25\u003c/sub\u003e% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.09\u0026thinsp;\u0026plusmn;\u0026thinsp;20.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.84\u0026thinsp;\u0026plusmn;\u0026thinsp;10.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e50\u003c/sub\u003e, L/s, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMEF\u003csub\u003e50\u003c/sub\u003e% predicted, %, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.75\u0026thinsp;\u0026plusmn;\u0026thinsp;21.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.35\u0026thinsp;\u0026plusmn;\u0026thinsp;11.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eType 2 inflammation biomarkers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeNO, ppb, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.00 (13.00, 49.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.00 (11.50, 43.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum total IgE, IU/mL, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e743.89 (292.67, 1,303.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e506.29 (285.00, 1,525.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood eosinophil count, \u0026times;10\u003csup\u003e6\u003c/sup\u003e/L, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e625.00 (400.00, 850.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e535.00 (405.00, 770.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSputum eosinophil percentage%, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.25 (3.50, 25.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.50 (1.50, 13.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e1 n (%)\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e2 Chi-square test for independence; Wilcoxon rank-sum test; Fisher\u0026apos;s exact test\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, dupilumab significantly reduces the percentage of pediatric asthma patients with SAD and improves small airway function indicators. This result aligns with previous studies. In the VESTIGE study, dupilumab significantly reduced SAD prevalence in adult patients with moderate-to-severe asthma[11]. While another study with 25 pediatric patients showed similar trends in lung function parameters including small airways[13]. Our real-world data, derived from a larger pediatric cohort of patients with asthma, corroborated significant improvements in SAD.\u003c/p\u003e \u003cp\u003eAfter adding dupilumab to the baseline ICS\u0026ndash;LABA therapy in children with asthma, beyond the reduction in SAD prevalence, all small-airway function indicators\u0026mdash;including MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, MEF\u003csub\u003e25\u003c/sub\u003e% predicted, and MEF\u003csub\u003e50\u003c/sub\u003e% predicted\u0026mdash;showed substantial and sustained improvement. These findings corroborate and expand upon the limited existing pediatric data on dupilumab and small-airway function. In the phase-III VOYAGE trial, MMEF\u003csub\u003e25/75\u003c/sub\u003e significantly improved by 0.60\u0026ndash;0.65 L/s in children (6\u0026ndash;11 years) with uncontrolled moderate-to-severe asthma after 52 weeks of dupilumab treatment versus placebo[10]. Improvement in small-airway function has clinical significance, as reduced MMEF\u003csub\u003e25/75\u003c/sub\u003e independently predicts future exacerbations regardless of FEV\u003csub\u003e1\u003c/sub\u003e[14]. Our cohort showed halved exacerbation rates and decreased rescue medication use, suggesting that early restoration of peripheral airway function translates into concrete disease-modifying benefits. Moreover, enhanced small-airflow may also enhance inhaled-drug deep delivery, creating a positive cycle that improves asthma control and reduces systemic therapy needs.\u003c/p\u003e \u003cp\u003eType 2 inflammation biomarkers also declined significantly following treatment. The rapid reduction in FeNO, together with decreases in serum IgE, blood eosinophils, and sputum eosinophils, aligns with the known pharmacologic mechanism of dupilumab. Blockade of IL-4Rα inhibits both IL-4- and IL-13-mediated processes, reducing eosinophilic inflammation, mucus hypersecretion, and airway epithelial nitric oxide production\u0026mdash;factors intricately linked to small-airway narrowing and remodeling[15, 16]. Notably, sputum eosinophil percentage, an important indicator that had been less reported in other pediatric asthma studies, was systematically reported in this study. The results showed that the sputum eosinophil percentage significantly decreased after the treatment with dupilumab from 6.00 (2.50, 21.50) % at baseline to 1.00 (0.02, 3.13) % at 12 months, with a highly significant extent and speed of the decrease, and was maintained at a low level after 3 months. Compared with the blood eosinophil count, sputum eosinophils can more directly reflect the local airway type 2 inflammatory state. Although the decrease in sputum eosinophils in this study was consistent with the downward trend in blood eosinophil count, the sputum eosinophil percentage decreased rapidly to near normal levels (\u0026lt;\u0026thinsp;2.5%) after treatment, whereas the blood eosinophil count tended to decrease more slowly after treatment, suggesting that dupilumab might preferentially and effectively inhibit local inflammatory cell infiltration in the airways[17].\u003c/p\u003e \u003cp\u003eMultivariable logistic regression model found that the rapid and sustained increases in MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, MEF\u003csub\u003e25\u003c/sub\u003e% predicted and MEF\u003csub\u003e50\u003c/sub\u003e% predicted values corresponded with the sharp reduction in FeNO. This aligns with recent findings showing negative correlations between MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted, MEF\u003csub\u003e25\u003c/sub\u003e% predicted, MEF\u003csub\u003e50\u003c/sub\u003e% predicted and FeNO\u003csub\u003e200\u003c/sub\u003e in 248 asthmatic children (r = \u0026minus;\u0026thinsp;0.46 to \u0026minus;\u0026thinsp;0.49, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)[18].Besides, another study observed a significant positive correlation between increases in FeNO and SAD (r\u0026thinsp;=\u0026thinsp;0.52, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001)[19]. These results implicate an IL-4/IL-13\u0026ndash;driven type 2 inflammation axis as the primary therapeutic target. Dupilumab also attenuates IL-13\u0026ndash;driven sub-epithelial fibrosis and airway smooth-muscle hypertrophy, key components of small-airway remodeling[20]. The observed association between FeNO reduction and MMEF\u003csub\u003e25/75\u003c/sub\u003e improvement (OR 1.02 per 1-ppb decrease, 95% CI 1.00\u0026ndash;1.06) is consistent with the hypothesis that reduced epithelial nitric-oxide synthase activity\u0026mdash;potentially through attenuated IL-13\u0026ndash;STAT6 signaling\u0026mdash;may contribute to improved peripheral airway function[21]. Emerging evidence further suggests a neuro-immune interface: IL-4 and IL-13 enhance transient receptor potential vanilloid-1 (TRPV1) expression on airway sensory nerves, causing bronchial hyper-reactivity[22]. By inhibiting these pathways, dupilumab may indirectly improve small-airway compliance and reduce dynamic collapse during forced expiration, achieving comprehensive improvement across all indicators.\u003c/p\u003e \u003cp\u003eIn addition, it was found by comparing baseline characteristics of patients with improvement in small airway function and those without improvement in small airway function in this study that patients in the improvement group showed better asthma symptom control (higher c-ACT scores, and lower ACQ-7-IA scores) and a relatively milder degree of lung function impairment (higher Pre-BD FEV₁% predicted, Pre-BD FEV₁/FVC, etc.) at baseline. These findings strongly suggest that dupilumab may achieve a better therapeutic effect by intervening in the early stage of the disease, i.e., before irreversible structural remodeling occurred in the small airways. In patients with mild baseline symptoms and mild airway obstruction, the pathological changes of small airways may still be in a stage dominated by inflammation and reversible dysfunction rather than remodeling stage of serious fibrosis or smooth muscle hyperplasia. Therefore, the response to the treatment with dupilumab was more significant. Conversely, in patients in the non-improvement group with severe baseline symptoms and poor lung function, the small airways may have undergone a longer remodeling process, making functional recovery more difficult even after effective suppression of type 2 inflammation. This emphasizes the importance of early biomarker assessment and consideration of early intervention with biologics such as dupilumab in the management of asthma in children with moderate-to-severe asthma, in order to maximize preservation and recovery of small airway function before irreversible airway remodeling occurs, thereby altering the long-term prognosis of the disease.\u003c/p\u003e \u003cp\u003eThis study has some limitations. The retrospective design and limited sample size may introduce bias. Prospective, further multicenter studies with larger pediatric populations and extended follow-up are needed to validate these findings and to explore dupilumab\u0026rsquo;s role in combination therapies and younger populations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDupilumab substantially improves SAD in children with moderate-to-severe asthma by rapidly reducing type 2 inflammation biomarkers. A decrease in FeNO may serve as a potential predictive indicator for reflecting improvements in small airway function.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the investigators, study coordinators and most of all the patients who are participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy design and hypothesis generation: LS, LZ. Data acquisition, analysis, or interpretation: LS, LC, KY, YY, and FG. Chart review and manuscript preparation: LS, LZ, and JZ. Critical revision: NZ and JZ. Funding was obtained by LS. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by State Key Laboratory of Respiratory Disease (Special Project for Clinical and Epidemiological Research, Project No. SKLRD-L-202603).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed for the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Ethical Review Board of the First Affiliated Hospital of Guangzhou Medical University approved the study (No. ES-2024-001-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eVenkatesan, P., \u003cem\u003e2025 GINA report for asthma.\u003c/em\u003e Lancet Respir Med, 2025.\u003c/li\u003e\n\u003cli\u003eDunican, E.M., et al., \u003cem\u003eMucus plugs in patients with asthma linked to eosinophilia and airflow obstruction.\u003c/em\u003e J Clin Invest, 2018. \u003cstrong\u003e128\u003c/strong\u003e(3): p. 997-1009.\u003c/li\u003e\n\u003cli\u003eGao, F., et al., \u003cem\u003eSmall airway dysfunction links asthma exacerbations with asthma control and health-related quality of life.\u003c/em\u003e Respir Res, 2024. \u003cstrong\u003e25\u003c/strong\u003e(1): p. 306.\u003c/li\u003e\n\u003cli\u003eUsmani, O.S., et al., \u003cem\u003eThe prevalence of small airways disease in adult asthma: A systematic literature review.\u003c/em\u003e Respir Med, 2016. \u003cstrong\u003e116\u003c/strong\u003e: p. 19-27.\u003c/li\u003e\n\u003cli\u003eRiley, C.M., et al., \u003cem\u003eClinical Implications of Having Reduced Mid Forced Expiratory Flow Rates (FEF25-75), Independently of FEV1, in Adult Patients with Asthma.\u003c/em\u003e PLoS One, 2015. \u003cstrong\u003e10\u003c/strong\u003e(12): p. e0145476.\u003c/li\u003e\n\u003cli\u003eLong, J.W. and Y.L. Jiang, \u003cem\u003eAssociation of Small Airway Functional Indices With Respiratory Symptoms and Comorbidity in Asthmatics: A National Cross-Sectional Study.\u003c/em\u003e J Clin Med Res, 2024. \u003cstrong\u003e16\u003c/strong\u003e(5): p. 220-231.\u003c/li\u003e\n\u003cli\u003eTamura, K., et al., \u003cem\u003eMucus Plugs and Small Airway Dysfunction in Asthma, COPD, and Asthma-COPD Overlap.\u003c/em\u003e Allergy Asthma Immunol Res, 2022. \u003cstrong\u003e14\u003c/strong\u003e(2): p. 196-209.\u003c/li\u003e\n\u003cli\u003eLe Floc\u0026apos;h, A., et al., \u003cem\u003eDual blockade of IL-4 and IL-13 with dupilumab, an IL-4R\u0026alpha; antibody, is required to broadly inhibit type 2 inflammation.\u003c/em\u003e Allergy, 2020. \u003cstrong\u003e75\u003c/strong\u003e(5): p. 1188-1204.\u003c/li\u003e\n\u003cli\u003eGandhi, N.A., G. Pirozzi, and N.M.H. Graham, \u003cem\u003eCommonality of the IL-4/IL-13 pathway in atopic diseases.\u003c/em\u003e Expert Rev Clin Immunol, 2017. \u003cstrong\u003e13\u003c/strong\u003e(5): p. 425-437.\u003c/li\u003e\n\u003cli\u003eBacharier, L.B., et al., \u003cem\u003eDupilumab in Children with Uncontrolled Moderate-to-Severe Asthma.\u003c/em\u003e N Engl J Med, 2021. \u003cstrong\u003e385\u003c/strong\u003e(24): p. 2230-2240.\u003c/li\u003e\n\u003cli\u003eWashko, G.R., et al., \u003cem\u003eEffect of dupilumab on small airways measured by airway oscillometry in VESTIGE.\u003c/em\u003e J Allergy Clin Immunol, 2025. \u003cstrong\u003e156\u003c/strong\u003e(5): p. 1209-1218.\u003c/li\u003e\n\u003cli\u003eXiao, D., et al., \u003cem\u003ePrevalence and risk factors of small airway dysfunction, and association with smoking, in China: findings from a national cross-sectional study.\u003c/em\u003e Lancet Respir Med, 2020. \u003cstrong\u003e8\u003c/strong\u003e(11): p. 1081-1093.\u003c/li\u003e\n\u003cli\u003eShi, T., et al., \u003cem\u003eThe assessment of dupilumab in children with moderate-to-severe asthma and comorbid type 2 inflammatory diseases.\u003c/em\u003e BMC Pulm Med, 2024. \u003cstrong\u003e24\u003c/strong\u003e(1): p. 607.\u003c/li\u003e\n\u003cli\u003eLazova, S., et al., \u003cem\u003eMMEF(25-75) may predict significant BDR and future risk of exacerbations in asthmatic children with normal baseline FEV(1).\u003c/em\u003e Int J Physiol Pathophysiol Pharmacol, 2022. \u003cstrong\u003e14\u003c/strong\u003e(1): p. 33-47.\u003c/li\u003e\n\u003cli\u003eLaPorte, S.L., et al., \u003cem\u003eMolecular and structural basis of cytokine receptor pleiotropy in the interleukin-4/13 system.\u003c/em\u003e Cell, 2008. \u003cstrong\u003e132\u003c/strong\u003e(2): p. 259-72.\u003c/li\u003e\n\u003cli\u003eGandhi, N.A., et al., \u003cem\u003eTargeting key proximal drivers of type 2 inflammation in disease.\u003c/em\u003e Nat Rev Drug Discov, 2016. \u003cstrong\u003e15\u003c/strong\u003e(1): p. 35-50.\u003c/li\u003e\n\u003cli\u003ePeltrini, R., et al., \u003cem\u003eDiscovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.\u003c/em\u003e Am J Respir Crit Care Med, 2024. \u003cstrong\u003e210\u003c/strong\u003e(9): p. 1101-1112.\u003c/li\u003e\n\u003cli\u003eZhang, L., et al., \u003cem\u003eIdentification and treatment of persistent small airway dysfunction in paediatric patients with asthma: a retrospective cohort study.\u003c/em\u003e BMC Pulm Med, 2024. \u003cstrong\u003e24\u003c/strong\u003e(1): p. 94.\u003c/li\u003e\n\u003cli\u003eCottini, M., et al., \u003cem\u003eSmall airway dysfunction mediates the relationship between Fractional Exhaled Nitric Oxide and asthma control.\u003c/em\u003e Ann Allergy Asthma Immunol, 2025. \u003cstrong\u003e134\u003c/strong\u003e(5): p. 548-555.e4.\u003c/li\u003e\n\u003cli\u003eNakagome, K. and M. Nagata, \u003cem\u003eThe Possible Roles of IL-4/IL-13 in the Development of Eosinophil-Predominant Severe Asthma.\u003c/em\u003e Biomolecules, 2024. \u003cstrong\u003e14\u003c/strong\u003e(5).\u003c/li\u003e\n\u003cli\u003eEscamilla-Gil, J.M., M. Fernandez-Nieto, and N. Acevedo, \u003cem\u003eUnderstanding the Cellular Sources of the Fractional Exhaled Nitric Oxide (FeNO) and Its Role as a Biomarker of Type 2 Inflammation in Asthma.\u003c/em\u003e Biomed Res Int, 2022. \u003cstrong\u003e2022\u003c/strong\u003e: p. 5753524.\u003c/li\u003e\n\u003cli\u003eChoi, J.Y., et al., \u003cem\u003eTRPV1 Blocking Alleviates Airway Inflammation and Remodeling in a Chronic Asthma Murine Model.\u003c/em\u003e Allergy Asthma Immunol Res, 2018. \u003cstrong\u003e10\u003c/strong\u003e(3): p. 216-224.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dupilumab, children asthma, small airway dysfunction, real-world study, type 2 inflammation","lastPublishedDoi":"10.21203/rs.3.rs-8288806/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8288806/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: In children with asthma, airway wall inflammation and mucus secretion can obstruct the lumen, causing small airway dysfunction (SAD) which correlates with poor asthma control and frequent acute exacerbations. However, current medications show limited efficacy in improving small-airway function in pediatric patients. Dupilumab effectively suppresses type 2 inflammation in asthma and may represent a novel, effective therapy for children with asthma, although real-world evidence is still lacking in China. This study evaluated the effectiveness of dupilumab on SAD in children with uncontrolled moderate-to-severe asthma.\u003c/p\u003e\n\u003cp\u003eMethods: This retrospective cohort study analyzed 106 children (aged 6-14 years) with moderate-to-severe asthma treated with dupilumab at the Guangzhou Institute of Respiratory Health (January 2022 and March 2025). All participants had uncontrolled asthma despite the treatment with medium-to-high-dose inhaled corticosteroid (ICS) plus long-acting β₂-agonist (LABA) or leukotriene receptor antagonists (LTRA), with type 2 inflammation characteristics. The primary endpoint was the change of the percentage of patients with SAD (defined as at least two of MMEF\u003csub\u003e25/75\u003c/sub\u003e, MEF\u003csub\u003e25\u003c/sub\u003e or MEF\u003csub\u003e50\u003c/sub\u003e below 65% of predicted values) at 6 months after dupilumab initiation. The secondary endpoints included changes of the percentage of patients with SAD at 3, 9, 12 months and changes in small-airway function indicators at 3, 6, 9, 12 months; changes in type 2 inflammation biomarkers (FeNO, serum total IgE, blood eosinophil count and sputum eosinophil percentage) at 3, 6, 9, 12 months; changes in annualized asthma exacerbation, pulmonary function tests, asthma symptom scores and rescue medication use at 6 months; a multivariable logistic regression model was constructed to identify factors associated with improvement in SAD and baseline characteristics were compared between patients with and without improvement in SAD.\u003c/p\u003e\n\u003cp\u003eResults: In children with asthma (mean age 8.71±2.5), 75.5% had allergic rhinitis and 15.1% had atopic dermatitis, with mean pre-treatment exacerbations of 2.0±1.1 annually. Post-dupilumab, the proportion of SAD patients significantly decreased from 63.2% to 16.0% at 6 months. All small airway indicators improved significantly (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). MMEF\u003csub\u003e25/75\u003c/sub\u003e% predicted increased from 57.2±21.3% to 75.8±20.3%, MEF\u003csub\u003e25\u003c/sub\u003e% predicted from 48.3±21.1% to 66.4±20.0%, and MEF\u003csub\u003e50\u003c/sub\u003e% predicted from 58.7±21.7% to 76.1±20.2% at 6 months. All type 2 inflammation biomarkers declined significantly: FeNO from 26.00 (13.00, 46.5) to 10.00 (8.00, 16.25) ppb, serum total IgE from 721.34 (294.75, 1330.94) to 162.81 (90.33, 297.70) IU/mL, blood eosinophil count from 610.00 (400.00, 840.00)×10\u003csup\u003e6\u003c/sup\u003e/L to 385.00 (260.00, 675.00)×10\u003csup\u003e6\u003c/sup\u003e/L, and sputum eosinophil percentage from 6.00 (2.50, 21.50)% to 0.50 (0.00, 1.50)% at 6 months. Dupilumab also significantly reduced asthma exacerbation rates, improved pre-BD FEV\u003csub\u003e1\u003c/sub\u003e and asthma symptom scores, and decreased the medication requirement. Multivariable logistic regression model showed that SAD improvement was independently associated with greater increases in pre-BD FEV₁/FVC% predicted (OR 1.27, 95% CI 1.09–1.51) and larger reductions in FeNO (OR 1.02, 95% CI 1.00–1.06). Children who improved in SAD had better baseline asthma control and less impaired lung function.\u003c/p\u003e\n\u003cp\u003eConclusion: Dupilumab effectively ameliorates SAD in children with moderate-to-severe asthma, probably through suppression of type 2 inflammation.\u003c/p\u003e","manuscriptTitle":"Dupilumab improves the small airway dysfunction in children with moderate to severe asthma: A retrospective analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 14:11:15","doi":"10.21203/rs.3.rs-8288806/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"701f9f35-654c-41b6-aa79-11703711dc5c","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-05T17:39:31+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 14:11:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8288806","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8288806","identity":"rs-8288806","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}