Introduction
Chronic respiratory diseases, including asthma, idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), and bronchiectasis (BE), significantly contribute to global respiratory morbidity [1-7]. Each of these conditions is characterized by persistent respiratory symptoms, structural abnormalities in the airways or lung parenchyma, and progressive functional decline [2,6,8,9]. Among these diseases, chronic cough (CC) is often underrecognized; however, it remains a common and distressing symptom [10-15]. In asthma, a cough may be an early or even predominant symptom, caused by airway hyperresponsiveness, inflammation, and neuronal dysfunction [10,16]. In IPF, cough is often non-productive, persistent, and linked to fibrotic changes that trigger abnormal cough reflexes [12]. COPD often presents with a cough caused by airway inflammation, mucus hypersecretion, and airflow limitation [11]. Similarly, in BE, cough is closely linked to impaired mucociliary clearance and recurrent infections [14].
Despite its prevalence, the phenotypic characteristics of ‘CC’ in these distinct diseases remain poorly defined and underexplored. CC affects up to 10% of the general adult population and can significantly impair their quality of life [17,18].
Although the pathophysiology and management of chronic respiratory diseases have been extensively studied, the specific characteristics of CC within these conditions remain poorly defined [19-22]. Although tools such as the cough assessment test (COAT), Leicester cough questionnaire (LCQ), cough numeric rating scale (NRS), and cough symptom score (CSS) are used in chronic respiratory diseases, they are not applied comprehensively or systematically, especially in conjunction with assessments of cough hypersensitivity.
This study aims to comprehensively analyze CC in four major chronic respiratory diseases using multiple validated assessment tools. Our goal is to enhance the understanding of CC in each disease, characterize disease-specific cough patterns, and evaluate the effectiveness of existing cough measurement tools in these clinical contexts.
Materials and Methods
1. Study populations
This prospective cohort study was conducted across 10 university-affiliated referral hospitals in South Korea, all of which participate in the Korean Academy of Tuberculosis and Respiratory Diseases (KATRD) Cough Research Group. Participants were enrolled prospectively between November 2021 and October 2023. Eligible participants met all of the following criteria:
(2) Respiratory diseases identified as the primary cause of CC: The cough was clinically assessed and determined to be primarily caused by one of the following respiratory diseases, which are classified in a mutually exclusive manner based on expert evaluation, relevant diagnostic tests, and clinical judgment:
(3)
A. Asthma: Airway hyperresponsiveness assessed through bronchodilator reversibility or bronchial provocation testing, in accordance with the KATRD asthma guidelines [8].
B. IPF: Diagnosis is based on a ‘mostly usual interstitial pneumonia’ pattern observed on high-resolution chest computed tomography or confirmed through histopathologic analysis from a lung biopsy [2].
C. COPD: Aged 40 years or older with a post-bronchodilator forced expiratory volume in 1 second/forced vital capacity ratio of less than 0.7, in accordance with the KATRD COPD guideline [25].
D. BE: Radiological confirmation of bronchial dilation is consistent with the clinical features of BE [26].
Patients were excluded from the analysis if there was overlap between the target respiratory diseases or if other potential causes of CC were present (n=37).
2. Collected variables
Demographic information included sex, age, smoking status, cumulative smoking exposure measured in pack-years, and smoking duration. To assist in the differential diagnosis of CC related to chronic respiratory diseases, we systematically assessed relevant comorbid conditions, such as allergic rhinitis, chronic rhinosinusitis, post-nasal drip, eosinophilic bronchitis, gastroesophageal reflux disease, and laryngopharyngeal reflux. Additionally, we reviewed medication history to exclude individuals currently using angiotensin-converting enzyme inhibitors or dipeptidyl peptidase-4 inhibitors, as these could confound the evaluation.
3. Description of cough assessment tools
1) Cough assessment test
The COAT is a validated instrument developed by the Cough Research Group of the KATRD to evaluate CC [27]. It has been shown to correlate well with both the cough NRS and the LCQ [24,28-30]. The COAT consists of five items, each scored from 0 to 4, resulting in a total score that ranges from 0 to 20. The items measured include cough frequency, limitations in daily activities, sleep disturbances due to cough, fatigue, and cough hypersensitivity.
3) Cough numeric rating scale
The cough NRS is an alternative to the traditional visual analog scale for assessing cough severity [34]. The scale ranges from 0 (no cough) to 10 (the most severe cough imaginable).
4) Cough symptom score
The CSS is a two-part questionnaire that assesses cough severity and frequency during both day and night. Each period is scored on a scale from 0 (no cough) to 5 (severe cough), resulting in a total score that ranges from 0 to 10 [35,36]. This tool captures diurnal variation in symptoms by providing separate measurements for daytime and night-time.
5) Cough hypersensitivity questionnaire
The cough hypersensitivity questionnaire (CHQ) is a validated tool designed to assess cough-related sensations and triggers in patients with CC [37].
It consists of 22 binary (yes/no) items, divided into two domains: six items related to sensations (e.g., throat tickle, chest irritation) and 16 items related to triggers (e.g., cold air, talking, perfumes). Scores are calculated based on the total number of ‘yes’ responses, with sub-scores for sensations (0-6) and triggers (0-16), resulting in a total score range of 0-22. Higher scores indicate greater cough hypersensitivity. This tool is considered clinically feasible, requiring approximately one minute to complete, and is suitable for use in both routine assessments and research settings [38]. Details are summarized in Supplementary Table S1.
4. Statistical analysis
Categorical variables were analyzed using Pearson’s chi-square test. For continuous variables, normality was assessed with the Shapiro-Wilk test. Since normality was not satisfied, Kruskal-Wallis tests were employed to compare distributions across the four groups. Differences among groups for continuous variables were evaluated using the Kruskal-Wallis test, followed by Dunn’s pairwise comparisons with Holm correction for multiple testing when significant. For categorical variables, chi-square or Fisher’s exact tests were applied as appropriate, and pairwise comparisons of proportions were conducted using the Holm method when overall significance was observed. To assess the impact of disease classification on cough-related score differences, multivariable linear regression analysis was performed, adjusting for sex, age, and smoking status, with the asthma group serving as the reference category in all regression models. A p-value of less than 0.05 was deemed statistically significant. All statistical analyses were conducted using R version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria) with RStudio version 2024.12.0+467 (by Posit Software, PBC, Boston, MA, USA).
5. Ethical approval and consent to participate
The study protocol received approval from the Institutional Review Board of Hanyang University Hospital (No. GURI 2021-10-011-001). All participants provided written informed consent before enrollment. The study was conducted in accordance with the Declaration of Helsinki and applicable local regulations.
Results
1. Demographics of study population
A total of 303 patients were initially enrolled, of which 37 were excluded: 19 due to non-chronic respiratory diseases, 13 classified as having unexplained CC at final diagnosis, and five with uncertain diagnoses. Ultimately, 266 patients were included in the final analysis (Figure 1). Demographic information is detailed in Table 1. Patients with asthma were younger, with a median age of 59.0 years (interquartile range [IQR], 45.0 to 68.0), compared to those with IPF (median, 73.0 years; IQR, 66.0 to 78.0), COPD (median, 69.5 years; IQR, 65.0 to 75.0), and BE (median, 67.0 years; IQR, 60.0 to 74.0) (p<0.001). The proportion of female patients was highest in the asthma (67.0%) and BE (70.2%) groups, while male patients predominated in the IPF (80.6%) and COPD (83.3%) groups (p<0.001). Never-smokers were most common in the asthma (67.9%) and BE (73.7%) groups, whereas a majority of COPD and IPF patients were ever-smokers (p<0.001).
2. COAT, LCQ, cough NRS, and CSS across groups
Table 2 presents the COAT, LCQ, NRS, and CSS scores stratified by disease group. Patients with asthma and IPF reported higher symptom burdens in the COAT total score compared to those with COPD and BE (median: asthma 8.0 [IQR, 5.0 to 12.0]; IPF 8.0 [IQR, 5.0 to 11.0]; COPD 5.0 [IQR, 2.0 to 9.0]; BE 4.0 [IQR, 2.0 to 8.0]; p<0.001) (Figure 2). Post hoc analysis revealed that patients with asthma and IPF had significantly higher scores than those with COPD and BE. Asthma exhibited significantly higher scores across all COAT subdomains, while IPF demonstrated higher scores in symptom frequency and fatigue compared to COPD and BE, particularly higher than BE. These patterns persisted in multivariable models that adjusted for age, sex, and smoking status. Asthma and IPF remained significantly associated with higher COAT symptom frequency (COAT1), greater impact on daily life (COAT2), and fatigue (COAT4) compared to BE. IPF also showed higher levels of sleep disturbance (COAT3) and cough triggered by dust, irritant odors, and cold air (COAT5) than BE, whereas COPD only differed from BE in cough-related fatigue (all p<0.05) (Supplementary Table S2). The LCQ total score was significantly lower in the asthma group, indicating worse cough-specific quality of life compared to COPD and BE (median: asthma 13.1 [IQR, 10.4 to 16.4]; COPD 15.0 [IQR, 13.0 to 18.4]; BE 16.2 [IQR, 12.7 to 18.2]; p=0.001).
The physical, psychological, and social subdomains of the LCQ exhibited a consistent trend, with asthma patients reporting a more impaired quality of life. In adjusted analyses, asthma was linked to significantly lower LCQ scores across all domains—physical, psychological, and social—when compared to BE (all p<0.05). Although IPF also demonstrated significantly lower scores in the psychological and social domains compared to BE, this was not the case in the physical domain (Supplementary Table S3). The cough NRS revealed that the asthma group experienced significantly greater severity than both the COPD and BE groups, with the IPF group also reporting higher scores than BE (median: asthma 5.0 [IQR, 4.0 to 7.0], COPD 5.0 [IQR, 3.0 to 5.0], BE 4.0 [IQR, 2.0 to 5.0]; p=0.003). The total CSS scores also showed significant differences among the groups (p<0.001), with asthma and IPF patients reporting higher overall scores than those with COPD and BE. Notably, the severity of night-time cough was greatest in the asthma and IPF groups compared to the COPD and BE groups (p=0.002). These differences remained significant after adjusting for age, sex, and smoking status (all p<0.05) (Supplementary Table S4).
3. CHQ across groups
The total CHQ scores and subdomain scores (triggers and sensations) were generally comparable across asthma, IPF, COPD, and BE, with no statistically significant differences (Table 3). Among all diagnostic groups, the most frequently reported cough triggers (over 50% of patients) included cold air (asthma 62.3%, IPF 59.5%, COPD 50.0%, BE 52.6%), sputum (especially in IPF, COPD, and BE), and smoke. Talking was reported more often as a cough trigger in asthma (29.2%) and IPF (29.7%) compared to COPD (9.1%; p=0.002). Eating or drinking was more frequently associated with cough in IPF (27.0%) than in BE (5.3%; p=0.015), suggesting a greater sensitivity related to swallowing. Post-nasal drip was notably more common in asthma (32.1%) than in IPF (8.1%) or COPD (12.1%; p=0.001), reflecting the upper airway involvement characteristic of asthma. Sputum (phlegm) was reported by over 60% of patients with IPF (64.9%), COPD (63.6%), and BE (64.9%), significantly more than in asthma (45.3%; p=0.023).
Regarding CHQ sensation items, dry throat, throat irritation, and a tickle in the throat were common (30% to 50%) across all groups, without significant differences. However, the urge to cough was significantly more prevalent in individuals with asthma (43.4%) compared to those with COPD (19.7%; p=0.004), indicating heightened cough reflex sensitivity in asthma.
4. Differences in cough measurements by underlying structural lung disease
In multivariable linear regression analyses adjusted for age, sex, and smoking, symptom scores varied significantly by underlying lung disease (Figure 3). IPF, which exhibited the highest symptom burden across most domains, served as the reference group. Compared to IPF, the asthma group showed no significant differences in any symptom scores. In contrast, the BE group demonstrated a distinctive profile, with significantly lower COAT scores (β=-3.82, p<0.001), higher LCQ scores (β=1.90, p=0.036), and lower CSS scores (β=-1.47, p<0.001). The COPD group was also associated with lower COAT scores (β=-2.56, p=0.006) and CSS scores (β=-0.89, p=0.020), along with a marginally higher LCQ score (β=1.66, p=0.052).
Discussion
This study offers a comprehensive comparative analysis of cough characteristics across four major chronic respiratory diseases: asthma, IPF, COPD, and BE. Utilizing multiple validated assessment tools, this research goes beyond previous studies that typically focused on a single disease or used limited symptom scales. It integrates both quantitative and qualitative aspects of cough, employing COAT, LCQ, NRS, CSS, and CHQ scores. The study reveals the heterogeneity of cough burden and its clinical significance within each disease group. Patients with asthma and IPF consistently exhibited higher cough severity and lower cough-related quality of life, as indicated by significantly elevated COAT and CSS scores and diminished LCQ scores. These findings underscore that cough in these populations is not only frequent but also functionally and psychosocially debilitating.
One key finding highlights the characteristics of cough hypersensitivity across various chronic structural lung diseases. The three most commonly reported triggers among all groups were cold air (50.0%-62.3%), sputum (45.3%-64.9%), and smoking (39.4%-43.2%). Post-nasal drip and talking were reported more frequently as cough triggers in asthma compared to IPF and COPD. Talking was more commonly noted in asthma and IPF than in COPD, while eating or drinking was identified more often as a trigger in IPF than in BE. Sputum was a prevalent trigger in IPF, COPD, and BE, but was reported less frequently in asthma. The urge to cough was notably stronger in asthma and IPF, with other common sensations including ticklishness, irritation, and dryness, indicating a high prevalence of cough hypersensitivity. These findings underscore the need for targeted assessment and management of cough hypersensitivity, especially in patients with chronic structural lung diseases. Cough reflex hypersensitivity is emerging as a treatable trait not only in patients with refractory CC but also in those with respiratory diseases that present with CC [39].
Together, these patterns suggest distinct underlying mechanisms and support the idea of cough hypersensitivity as a shared, yet heterogeneously expressed, endotype across various respiratory diseases.
The LCQ score distribution indicates that most participants in our study experienced a cough of mild to moderate severity [40]. The mean CHQ scores were approximately 5.0 for all four chronic respiratory disease groups, which is lower than what is typically reported for patients with cough variant asthma or refractory CC [41].
This reflects the broader clinical profiles of our participants, many of whom also experienced dyspnea, sputum production, or structural lung disease, rather than presenting with cough as the sole chief complaint. As a result, the LCQ and CHQ score patterns observed in this cohort differ from those commonly seen in populations with isolated CC. Nevertheless, cough hypersensitivity remains a shared factor that adversely affects quality of life across these diverse patient groups.
This study has several notable strengths. First, it employed a multidimensional approach to cough characteristics across various chronic respiratory diseases within a real-world cohort. The use of multiple cough assessment tools enabled a more comprehensive characterization of cough phenotypes. Second, the finding that cough burden was lower in COPD and BE compared to asthma and IPF highlights disease-specific differences in cough mechanisms. This may reflect heightened cough reflex sensitivity driven by airway eosinophilic inflammation in asthma or fibrotic distortion in IPF, in contrast to mucus- or infection-related cough, which is more prominent during exacerbations in COPD and BE [42-44].
Third, this is one of the first to examine cough hypersensitivity specifically in chronic respiratory diseases. The findings reveal that cough hypersensitivity, now recognized as a key mechanism in CC, is also prevalent in these conditions. Among different disease groups, the most common cough triggers were cold air, sputum, and smoke. However, there were notable differences: talking and post-nasal drip were more frequently reported in asthma, while swallowing-related triggers were more common in IPF. Sputum was a trigger in IPF, COPD, and BE. Sensation profiles were generally similar across groups, but the urge to cough was more pronounced in asthma than in COPD, indicating increased cough reflex sensitivity. These results suggest that future management strategies for CC should not only address underlying causes but also include symptom-focused interventions. Furthermore, the variations in triggers and sensations among disease groups imply that, while the overarching pathophysiology may be similar, the specific features and mechanisms likely differ. This highlights the importance of individualized assessment and treatment approaches, potentially incorporating evaluations of comorbidities and tailored therapeutic strategies.
This study has several limitations. First, its cross-sectional design does not allow for the evaluation of longitudinal changes or treatment responses. Instead, the study provides a broad comparative overview of various chronic respiratory diseases, focusing on differences in cough-related questionnaires. While this design limits mechanistic interpretation, it is suitable for exploring disease-specific differences in cough perception and hypersensitivity within a clinically diverse cohort. Second, participants were recruited from tertiary university hospitals, which may introduce referral bias and limit the generalizability of the findings to primary care settings. However, such centers are often ideal for capturing well-characterized cases with CC, thereby enhancing internal validity. Third, although standardized criteria were used to assign final diagnoses, some patients with overlapping or atypical features may have been excluded due to diagnostic uncertainty. This conservative approach was necessary to ensure diagnostic clarity and reduce heterogeneity in the analysis. Fourth, while smoking status was adjusted for in the analysis, cumulative exposure was not included, as this variable was unevenly distributed across disease groups; few patients with asthma or BE were current or ex-smokers. To minimize potential bias, only categorical smoking status was considered. Finally, we did not adjust for disease-specific severity indices (e.g., Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage in COPD, Gender, Age, and Physiology [GAP] score in IPF) because these measures primarily reflect airflow limitation or mortality risk and do not directly quantify cough burden. Additionally, the heterogeneity of severity metrics across diseases limits direct comparisons. While our goal was to examine cough-specific features across different diseases, future studies should incorporate harmonized or cough-sensitive severity measures to further validate these findings.
In conclusion, this study reveals that CC is both common and varied in individuals with chronic respiratory diseases. Our multimodal assessment identified unique cough profiles, particularly in asthma and IPF, emphasizing the importance of customized management strategies.
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