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Clinical characteristics of obese, fixed airway obstruction, exacerbation-prone phenotype and comorbidities among severe asthma patients: a single-center study

BMC Pulmonary Medicine volume 24, Article number: 76 (2024) Cite this article

Abstract

Background

Severe asthma places a large burden on patients and society. The characteristics of patients with severe asthma in the Chinese population remain unclear.

Methods

A retrospective review was conducted in patients with severe asthma. Demographic and clinical data were collected. Patients were grouped according to phenotypes in terms of exacerbations, body mass index (BMI) and fixed airway obstruction (FAO) status, and the characteristics of different groups were compared. Comorbidities, factors that influence asthma phenotypes, were also analyzed in the study.

Results

A total of 228 patients with severe asthma were included in our study. They were more likely to be overweight or obese. A total of 41.7% of the patients received GINA step 5 therapy, and 43.4% had a history of receiving regular or intermittent oral corticosteroids (OCS). Severe asthmatic patients with comorbidities were prone to have more asthma symptoms and decreased quality of life than patients without comorbidities. Patients with exacerbations were characterized by longer duration of asthma, poorer lung function, and worse asthma control. Overweight or obese patients tended to have more asthma symptoms, poorer lung function and more asthma-related comorbidities. Compared to patients without FAO, those in the FAO group were older, with longer duration of asthma and more exacerbations.

Conclusion

The existence of comorbidities in patients with severe asthma could result in more asthma symptoms and decreased quality of life. Patients with exacerbations or with overweight or obese phenotypes were characterized by poorer lung function and worse asthma control. Patients with FAO phenotype tended to have more exacerbations.

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Introduction

Severe asthma is defined as requiring Global Initiative for Asthma (GINA) step 4/5 interventions to prevent it from becoming “uncontrolled”, or remaining “uncontrolled” despite this treatment. It accounts for approximately 5–10% of all patients with asthma [1]. The China Asthma and Risk Factors Epidemiological Survey (CARE) showed that the prevalence of asthma in Chinese adults was 4.2%, of which severe asthma accounted for 5.99% [2]. Severe asthma places a large physical, mental, emotional, social, and economic burden on patients, and is associated with major treatment and socioeconomic burdens of a country [3, 4].

Compared to individuals with mild-to-moderate asthma, those with severe asthma have been reported to have more symptoms, exacerbations, and comorbidities [5]. In particular, various phenotypes of severe asthma have been proposed based on different clinical characteristics such as age at the onset of asthma, airway inflammation, atopic status and other characteristics [6, 7]. According to the Guidelines for Bronchial Asthma Prevent and Management in China, severe asthma was divided into 5 clinical phenotypes: early-onset allergic asthma; late-onset persistent eosinophilic asthma; asthma with frequent exacerbations; obese asthma; and asthma with fixed airway obstruction [8]. Acute exacerbations remain a serious challenge in asthma treatment and an explicit cause of progressive loss of lung function in asthmatic patients [9, 10]. It is defined as a new phenotype of asthma named exacerbation-prone asthma (EPA) [11]. Obese asthma is considered as a complex syndrome, as well as another phenotype of asthma [12]. The incidence of obesity in asthma patients varies from country to country [13, 14], with nearly 40% of severe asthma patients being obese around the world [15]. Obese asthmatic patients tend to have more symptoms, more frequent and severe exacerbations, and decreased quality of life [16]. Fixed airflow obstruction (FAO) is another feature of severe asthma [17] and presented as a new phenotype [18].Comorbidities are important in the management of severe asthma, and contribute to poor disease control by aggravating symptoms through affecting severe asthma phenotype and treatment response [19, 20].

Identifying the clinical characteristics of different phenotypes and recognizing comorbidities is a strategic approach in the treatment of severe asthma and could help to predict patients at high risk of exacerbation, formulating optimal individualized therapeutic schedule, and achieving effective asthma control [21]. Since the characteristics of severe asthma patients in the Chinese population remain unclear, in this study, we retrospectively analyzed the clinical characteristics of obese, fixed airway obstruction, exacerbation-prone phenotype and comorbidities among severe asthma patients. The results of this study will improve our understanding of severe asthma in the Chinese population, and thus, identify differences in the clinical characteristics of different phenotypes.

Materials and methods

Study design and setting

We screened all patients diagnosed with severe asthma from the asthma database of Zhongshan hospital between January 2016 and December 2020. Severe asthma is defined as requiring Global Initiative for Asthma (GINA) step 4/5 to prevent it from becoming “uncontrolled”, or remaining “uncontrolled” despite this treatment [1, 8]. This study was approved by the ethics committee of Zhongshan hospital, Fudan university (approval number: B2019-020R), and was conducted in accordance with the Declaration of Helsinki.

Patients

Patients in our study were 14 years or older. They received treatment with medium-to-high dose inhaled corticosteroid (ICS) and long-acting beta agonist (LABA) with or without other controller medications. Patients with allergic bronchopulmonary aspergillosis (ABPA), chronic obstructive pulmonary disease (COPD), and chronic respiratory failure with long-term use of non-invasive positive pressure ventilation were excluded.

Data collection and definition

Demographic and clinical data including age, sex, height, weight, smoking status, lung function, FENO, and allergen detection results were recorded. Symptom control was assessed using the Asthma Control Test (ACT), and the score ranged from 5 to 25, with a higher score reflecting better asthma control. Quality of life was measured with the Asthma Quality of Life Questionnaire (AQLQ).

Both regular and intermittent oral corticosteroid (OCS) use were included in OCS use. Regular OCS use is defined as a prescription for ≥ 90 days of OCS exposure in the previous year. Intermittent OCS use is defined as a prescription for repeated OCS use and/or ≥ 2 exacerbations (treated with OCS) [15]. The number of exacerbations was defined as the number that required the use of corticosteroids for at least 3 days or asthma-related hospitalization or emergency visit [22] in the previous year. Comorbidities were identified by clinical symptoms supported by the associated validated screening questionnaires for allergic rhinitis (the score for allergic rhinitis value ≥ 7) [23], chronic rhino-sinusitis (sinonasal questionnaire score ≥ 1) [24], obstructive sleep apnea (Berlin questionnaire score ≥ 2) [25], gastroesophageal reflux disease (GERD questionnaire score > 2) [26], anxiety/depression (hospital anxiety and depression score ≥ 11) [27], dysfunctional breathing (Nijmegen score ≥ 23) [28], and vocal cord dysfunction (Pittsburgh vocal cord dysfunction index ≥ 4) [29] as described in previous study [30]. The Chinese-specific cut-off points of body mass index (BMI) was categorized as follows: (1)obesity as BMI ≥ 28 kg/m2, (2)overweight as BMI 24.0-27.9 kg/m2, (3)normal as BMI 18.5–23.9 kg/m2, (4)underweight as BMI < 18.5 kg/m2 [31]. Allergen-specific immunoglobulin E (sIgE) was tested for house dust mite (hx2), molds and yeasts mix (mx2), food allergen mix (fx5), weed pollen mix (wx5) and tree pollen mix (tx4).

The smoking status of patients was included in our study. Never smokers were defined as individuals who had never smoked regularly or smoked less than 100 cigarettes during their lifetime. Ex-smokers were defined as individuals who had previously smoked more than one cigarette each day but had quit smoking for more than 1 year. Current smokers were defined as persons who smoked more than one cigarette per day and had smoked for more than 1 year [32]. Heavy smokers were defined as smoking > 10 PY, indicating smoking one pack (20 cigarettes) daily for 10 years [33, 34].Heavy smokers were excluded in the study.

FAO was defined as a persistent status of the ratio of forced expiratory volume to forced vital capacity in 1 s (FEV1/FVC) below 0.70 after bronchodilator inhalation [35]. COPD is a heterogeneous lung condition characterized by chronic respiratory symptoms due to abnormalities of the airways and/or alveoli that cause persistent, often progressive airflow obstruction [36].

The clinical features of different phenotypes were analyzed in terms of exacerbations, BMI and FAO. Since this was a retrospective study to investigate the clinical characteristics of severe asthma in China, the data are somewhat incomplete. Therefore, we divided the available data into different subgroups for analysis, expecting more valuable results.

Statistical analysis

Statistical analysis was performed with SPSS (version 23.0; IBM Corporation, Armonk, New York). Normal distribution variables were shown as mean ± SD and compared using Student’s t-test or one-way ANOVA test. Non-normally distributed variables were shown as median with interquartile range and compared using Mann-Whiteny test or Kruskal-Wallis test. Categorical data were shown as frequencies with percentages and compared using chi-squared or Fisher’s exact test. Linear regression was used to investigate factors associated with quality of life. Multivariate logistic regression analysis was conducted to asses factors related to uncontrolled asthma. A p-value < 0.05 was considered to be statistically significant.

Results

Demographic and clinical characteristics of patients

A flow chart of the research was shown in Fig. 1. This study included 228 patients with severe asthma. The demographic and clinical characteristics of enrolled patients were described in Table 1. The median age of all patients was 53.0 (38.0–62.0) years and median age at asthma onset was 40.0 (22.3–50.8) years. Patients were mainly male (52.6%), overweight or obese (54.8%), and never smoked (74.6%). More than half of the patients (66.3%) were allergen-positive. Allergic rhinitis was the predominant comorbidity (76.7%) in the total population, followed by gastroesophageal reflux (40.3%). Ninety-five (41.7%) patients received treatment at GINA step 5. A total of 43.4% of the patients had a history of receiving regular or intermittent OCS, and 80 (35.1%) patients were receiving biologics (Omalizumab).

Fig. 1
figure 1

Flow diagram of study participants

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Table 1 Basic characteristics of patients included in the study
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Comparison of characteristics of patients according to comorbidities

A total of 183 patients were included in this subgroup analysis. As shown in Table 2, the characteristics of patients according to comorbidities were analyzed. Patients with 3 or more comorbidities had lower ACT and AQLQ scores than those with less than 3 or without comorbidities (P = 0.004; P = 0.007). 60% of patients with 3 or more comorbidities received treatment at GINA step 5, which was the highest compared to other groups (P = 0.039). The requirement of the use of corticosteroids for at least 3 days during exacerbations was more likely to occur when patients had more comorbidities (P = 0.013). There were no significant differences in age, lung function, neutrophils, eosinophils, or total IgE levels among the groups.

Table 2 Comparison of characteristics of patients according to comorbidities
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Comparison of characteristics between patients with and without exacerbations in the previous year

Sex, age at asthma onset, laboratory findings, and number of comorbidities were similar between the two groups. Compared to patients without exacerbations, the average age of patients with exacerbations was older and the duration of asthma was longer. Exacerbations were related to progressive loss of lung function in asthmatic patients. In this study, poorer lung function was observed in patients with exacerbations, regardless of pre-bronchodilator or post-bronchodilator. Furthermore, patients had better asthma control and higher quality of life if they did not experience exacerbations. Compared to those without exacerbations, patients with exacerbations had a higher percentage of receiving treatment at GINA step 5 (Table 3).

Table 3 Comparison of characteristics between patients with and without exacerbations
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Comparison of characteristics between patients with BMI ≥ 24 and BMI < 24

To understand the role of overweight or obesity in severe asthma, 228 patients were divided into two groups with BMI ≥ 24 or BMI < 24 and the characteristics were analyzed in Table 4. There were no differences in age, age at asthma onset, duration of asthma, or laboratory findings. The percentage of female in BMI ≥ 24 group was lower than in BMI < 24 group (P = 0.007). Compared to BMI < 24 group, the measurement of the percentage of forced expiratory volume in 1 s (FEV1% pred) after bronchodilator inhalation was lower in BMI ≥ 24 group (P = 0.011). The BMI ≥ 24 group had worse asthma control as measured by ACT than the BMI < 24 group (P = 0.007). The percentage of patients with 3 or more comorbidities in BMI ≥ 24 group was 26.5%, much higher than BMI < 24 group.

Table 4 Comparison of characteristics between patients with BMI ≥ 24 and BMI < 24
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Considering that there were significant differences in other covariates such as sex, ACT score, and comorbidities according to BMI, multiple linear regression analysis was performed to evaluate the effects of BMI, sex, number of comorbidities, and ACT scores on post-bronchodilator FEV1% pred. As shown in Table 5, there was a negative correlation between lung function and BMI(P = 0.022), while other factors did not significantly affect lung function.

Table 5 Multiple linear regression analysis of factors associated with post-bronchodilator FEV1% pred
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Comparison of characteristics between patients with and without FAO

In order to further clarify the clinical characteristics of patients with FAO, we divided the patients into FAO and non-FAO groups (Table 6). Eighty-eight (46.6%) patients had FAO. Sex, BMI, and age at asthma onset were similar between the two groups. Patients in FAO group were older and had longer duration of asthma than those in non-FAO group. Compared to non-FAO group, FEV1% pred was lower in FAO group. The value of FENO, laboratory findings, asthma control, and quality of life did not differ significantly between two groups. However, the exacerbations of asthma and the percentage of patients requiring the use of corticosteroids for at least 3 days were affected by FAO (P = 0.004; P = 0.007). The percentage of severe asthma at GINA step 5 (65.9%) in FAO group was significantly higher compared to non-FAO group.

Table 6 Comparison of characteristics between patients with and without FAO
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Multiple regression analysis for factors associated with quality of life and Asthma control

Factors like age, sex, number of exacerbations, number of comorbidities, duration of asthma, and pre-bronchodilator FEV1% pred were taken into analysis after univariate analysis. As shown in Table 7, exacerbations and comorbidities were significantly linked to patients’ quality of life in the multiple linear regression. Patients with more exacerbations or comorbidities tended to have decreased quality of life. In addition, female patients had lower quality of life than male. The older the patients were, the more it affected their life.

Table 7 Linear regression for factors associated with quality of life
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Five potential risk factors of age, duration of asthma, number of exacerbations, sex, and number of comorbidities were included in logistic regression analysis after the univariate analysis. The logistic regression analysis showed that more exacerbations were associated with higher odds (OR = 1.229, P = 0.025). Similarly, more than 3 comorbidities were associated with higher odds (OR = 5.494, P = 0.009). Besides, female patients were more likely to have poorer asthma control than male (OR = 0.406, P = 0.013). (Table 8).

Table 8 logistic regression analysis of uncontrolled asthma (ACT < 20)
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Discussion

In our present study, patients with severe asthma were mainly overweight or obese, allergen-positive and never smoked. Patients enrolled in our study had a severe disease status, as a total of 41.7% of the patients were receiving GINA step 5 therapy, and 43.4% had a history of receiving regular or intermittent OCS. Approximately 90% of patients had asthma-related comorbidities and 53.1% of them experienced at least one exacerbation in the previous year. Approximately half of patients in this cohort had fixed airway obstruction.

The most common comorbidity in patients with severe asthma in our study was allergic rhinitis, and almost half of patients had gastroesophageal reflux. Asthma and allergic rhinitis have similar triggers and pathophysiology, characterized by similar inflammatory cell infiltrates [37]. Previous studies showed that patients with allergic rhinitis had distinct abnormalities of lower airway function although they had not yet developed into asthma [38, 39]. The relationship between asthma and gastroesophageal reflux is bidirectional. Acid infusion into the esophagus may cause bronchoconstriction, on the other hand, asthma may predispose to gastroesophageal reflux [40]. Gastroesophageal reflux is associated with frequent asthma exacerbations and oral corticosteroid therapy during exacerbations [41]. More than a quarter of patients had anxiety/depression, which may result in poorer quality of life and asthma control [42]. Strong associations were detected between comorbidities and severe asthma [43]. Comorbidities are important to the increased risk and frequency of annual hospitalizations due to asthma exacerbation [44]. In accordance with our present results, patients with 3 or more comorbidities had more symptoms and decreased quality of life. Comorbidities also increased the likelihood of systemic corticosteroids use when exacerbation. Therefore, recognition of these comorbidities is important for asthma management.

There are no precise biomarkers for the recognition of patients who are prone to exacerbations of asthma. A cross sectional study found that blood and sputum eosinophils, FEV1, depression, and some other factors are high risk triggers of asthma symptoms [45]. A meta-analysis of 23 observational studies validated that blood eosinophil counts ≥ 200 cells/µL were associated with asthma exacerbations [46]. Contrary to this finding, blood eosinophils were lower in patients with exacerbations in our study, which may be related to neutrophilic inflammation caused by rhinovirus. Rhinoviruses are known to be important triggers of asthma exacerbations [47, 48]. Lung function in patients with exacerbations was worse than in patients without exacerbations, further identifying the finding that exacerbations are the main cause of progressive loss of lung function [9]. Besides, poor lung function was also considered to be an independent factor of a higher probability of hospital readmission [49], forming a vicious circle between poor lung function and frequent exacerbations.

Asthma is usually controlled with inhaled corticosteroids. Obese asthmatics do not respond as well to standard controller medications such as ICS and combination ICS-long-acting beta agonists (LABA) [50]. Obese asthma may represent a unique phenotype of asthma, with a more severe disease outcome due to impairment of efficacy of conventional therapy [51]. As shown in our study, overweight or obese asthmatic patients had poorer asthma control according to ACT score. Furthermore, overweight or obesity is shown to be detrimental to lung function, characterized mainly by reduced FEV1 and FVC [13]. Physiological studies suggested that obesity decreased lung volume, which was associated with airway narrowing [52]. In our study, post-bronchodilator FEV1% pred was decreased in overweight or obese patients. In addition, overweight or obese patients tended to have more comorbidities. Obesity is associated with a range of asthma-related comorbidities, as it is reported to be associated with obstructive sleep apnea and gastroesophageal reflux that can affect asthma symptomatology [19, 53]. These were the potential causes that overweight or obese patients had poorer lung function and more asthma symptoms. It should be noted that the relationship between obesity and asthma is complex, influenced by many other factors including asthma-related comorbidities and some factors that produce obesity [54]. A study even showed that obesity does not increase the risk of asthma readmissions [54]. The effect of obesity on asthma control may need to be confirmed after expanding the sample size in the future.

Approximately 50% of the patients had fixed airway obstruction and more than three-quarters of them were non-smokers. Heavy smokers in our study were excluded to avoid misclassification of asthma with COPD. Fixed airway obstruction in older non-smoking asthmatic subjects may be related to increased lung compliance and loss of elastic recoil [55, 56]. We compared the characteristics of severe asthma patients with FAO to those without FAO. Patients with FAO were older, with longer duration of asthma, and lower pre-bronchodilator FEV1% pred than patients without FAO. Several studies found that FAO was associated with increased exacerbation rate [18, 57]and mortality [58, 59]. Consistent with this finding, we observed significantly difference in the number of exacerbations between patients with and without FAO. It should be noted that a study about the risk factors of FAO in older adults of asthma found that FAO is not independently associated with worse asthma control, quality of life, or exacerbations in older patients with asthma after controlling for confounding factors [60]. Therefore, we need to take into consideration of the age of FAO patients. For older patients with FAO, doctors should focus on other previously established risk factors rather than focus on maximizing lung function to improve care outcomes in this population.

Previous studies have confirmed the relationship between ACT score and lung function, exacerbations [61]. AQLQ score was affected by lung function, exacerbations, and BMI [62]. In our study, both of quality of life and asthma control were affected by the number of exacerbations and comorbidities in our study.

Our study has some limitations. First, all patients in this study were from one institution, indicating the potential for selection bias. Second, we only described baseline characteristics and lacked long-term follow-up data. Third, induced sputum is a valuable research tool for detecting airway inflammation and identifying asthma phenotypes. Due to lack of induced sputum data in our study, the patient’s asthma phenotype is not very clear.

In summary, this study performed a single-center retrospective analysis based on Chinese population in patients with severe asthma. Our findings contributed to improve our understanding of severe asthma in Chinese population and assisted us to learn the differences in clinical features of different phenotypes, which may lead to optimization of strategies to prevent and treat asthma.

Conclusion

Severe asthma patients were more likely to be overweight or obese. The existence of comorbidities in severe asthma patients may result in more asthma symptoms and decreased quality of life. Patients with exacerbations or with overweight or obese phenotype were characterized by poorer lung function and worse asthma control. Patients with FAO phenotype tended to have more exacerbations. Both of quality of life and asthma control were affected by the number of exacerbations and comorbidities.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to the fact that individual privacy could be compromised but are available from the corresponding author on reasonable request.

Abbreviations

BMI:

Body mass index

hx2:

House dusts mix

mx2:

Molds and yeasts mix

fx5:

Food allergen mix

wx5:

Weed pollen mix

tx4:

Tree pollen mix

IgE:

Immunoglobulin E

ICS:

Inhaled corticosteroid

LABA:

Long-acting beta agonist

LAMA:

Long-acting muscarine antagonist

LTRA:

Leukotriene receptor antagonist

OCS:

Oral corticosteroid

FEV1 :

Forced expiratory volume in 1 s

FVC:

Forced vital capacity

FENO:

Fractional exhaled nitric oxide

ACT:

Asthma control test

AQLQ:

Asthma quality of life questionnaire

FAO:

Fixed airway obstruction

References

  1. Chung KF, Wenzel SE, Brozek JL, Bush A, Castro M, Sterk PJ, Adcock IM, Bateman ED, Bel EH, Bleecker ER, Boulet LP, Brightling C, Chanez P, Dahlen SE, Djukanovic R, Frey U, Gaga M, Gibson P, Hamid Q, Jajour NN, Mauad T, Sorkness RL, Teague WG. International ERS/ATS guidelines on definition, evaluation and treatment of severe Asthma. Eur Respir J. 2014;43(2):343–73.

    Article  CAS  PubMed  Google Scholar 

  2. Lin J, Wang W, Chen P, Zhou X, Wan H, Yin K, Ma L, Wu C, Li J, Liu C, Su N, Liu G, Xie H, Tang W, Huang M, Chen Y, Liu Y, Song L, Chen X, Zhang Y, Li W, Sun L. Prevalence and risk factors of Asthma in mainland China: the CARE study. Respir Med. 2018;137:48–54.

    Article  PubMed  Google Scholar 

  3. Antonicelli L, Bucca C, Neri M, De Benedetto F, Sabbatani P, Bonifazi F, Eichler HG, Zhang Q, Yin DD. Asthma severity and medical resource utilisation. Eur Respir J. 2004;23(5):723–9.

    Article  CAS  PubMed  Google Scholar 

  4. Cisternas MG, Blanc PD, Yen IH, Katz PP, Earnest G, Eisner MD, Shiboski S, Yelin EH. A comprehensive study of the direct and indirect costs of adult Asthma. J Allergy Clin Immunol. 2003;111(6):1212–8.

    Article  PubMed  Google Scholar 

  5. Shaw DE, Sousa AR, Fowler SJ, Fleming LJ, Roberts G, Corfield J, Pandis I, Bansal AT, Bel EH, Auffray C, Compton CH, Bisgaard H, Bucchioni E, Caruso M, Chanez P, Dahlén B, Dahlen SE, Dyson K, Frey U, Geiser T, Gerhardsson de Verdier M, Gibeon D, Guo YK, Hashimoto S, Hedlin G, Jeyasingham E, Hekking PP, Higenbottam T, Horváth I, Knox AJ, Krug N, Erpenbeck VJ, Larsson LX, Lazarinis N, Matthews JG, Middelveld R, Montuschi P, Musial J, Myles D, Pahus L, Sandström T, Seibold W, Singer F, Strandberg K, Vestbo J, Vissing N, von Garnier C, Adcock IM, Wagers S, Rowe A, Howarth P, Wagener AH, Djukanovic R, Sterk PJ, Chung KF. Clinical and inflammatory characteristics of the European U-BIOPRED adult severe Asthma cohort. Eur Respir J. 2015;46(5):1308–21.

    Article  CAS  PubMed  Google Scholar 

  6. Haldar P, Pavord ID, Shaw DE, Berry MA, Thomas M, Brightling CE, Wardlaw AJ, Green RH. Cluster analysis and clinical Asthma phenotypes. Am J Respir Crit Care Med. 2008;178(3):218–24.

    Article  PubMed  Google Scholar 

  7. Sorkness RL, Bleecker ER, Busse WW, Calhoun WJ, Castro M, Chung KF, Curran-Everett D, Erzurum SC, Gaston BM, Israel E, Jarjour NN, Moore WC, Peters SP, Teague WG, Wenzel SE. Lung function in adults with stable but severe Asthma: air trapping and incomplete reversal of obstruction with bronchodilation. J Appl Physiol (Bethesda Md: 1985). 2008;104(2):394–403.

    Article  Google Scholar 

  8. Asthma group of Chinese Throacic Society. Guidelines for bronchial Asthma prevent and management(2020 edition). Zhonghua Jie He He Hu Xi Za Zhi. 2020;43(12):1023–48.

    Google Scholar 

  9. Castillo JR, Peters SP, Busse WW. Asthma exacerbations: Pathogenesis, Prevention, and treatment. J Allergy Clin Immunol Pract. 2017;5(4):918–27.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Bai TR, Vonk JM, Postma DS, Boezen HM. Severe exacerbations predict excess lung function decline in Asthma. Eur Respir J. 2007;30(3):452–6.

    Article  CAS  PubMed  Google Scholar 

  11. Dougherty RH, Fahy JV. Acute exacerbations of Asthma: epidemiology, biology and the exacerbation-prone phenotype. Clin Exp Allergy. 2009;39(2):193–202.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Schatz M, Hsu JW, Zeiger RS, Chen W, Dorenbaum A, Chipps BE, Haselkorn T. Phenotypes determined by cluster analysis in severe or difficult-to-treat Asthma. J Allergy Clin Immunol. 2014;133(6):1549–56.

    Article  PubMed  Google Scholar 

  13. Alqarni AA, Aldhahir AM, Siraj RA, Alqahtani JS, Alshehri HH, Alshamrani AM, Namnqani AA, Alsaidalani LN, Tawhari MN, Badr OI, Alwafi H. Prevalence of overweight and obesity and their impact on spirometry parameters in patients with Asthma: a Multicentre, Retrospective Study. J Clin Med 2023, 12(5).

  14. González Barcala FJ, de la Fuente-Cid R, Alvarez-Gil R, Tafalla M, Nuevo J, Caamaño-Isorna F. [Factors associated with Asthma control in primary care patients: the CHAS study]. Arch Bronconeumol. 2010;46(7):358–63.

    Article  PubMed  Google Scholar 

  15. Wang E, Wechsler ME, Tran TN, Heaney LG, Jones RC, Menzies-Gow AN, Busby J, Jackson DJ, Pfeffer PE, Rhee CK, Cho YS, Canonica GW, Heffler E, Gibson PG, Hew M, Peters M, Harvey ES, Alacqua M, Zangrilli J, Bulathsinhala L, Carter VA, Chaudhry I, Eleangovan N, Hosseini N, Murray RB, Price DB. Characterization of severe Asthma Worldwide: Data from the international severe Asthma Registry. Chest. 2020;157(4):790–804.

    Article  CAS  PubMed  Google Scholar 

  16. Peters U, Dixon AE, Forno E. Obesity and Asthma. J Allergy Clin Immunol. 2018;141(4):1169–79.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Moore WC, Meyers DA, Wenzel SE, Teague WG, Li H, Li X, D’Agostino R Jr., Castro M, Curran-Everett D, Fitzpatrick AM, Gaston B, Jarjour NN, Sorkness R, Calhoun WJ, Chung KF, Comhair SA, Dweik RA, Israel E, Peters SP, Busse WW, Erzurum SC, Bleecker ER. Identification of Asthma phenotypes using cluster analysis in the Severe Asthma Research Program. Am J Respir Crit Care Med. 2010;181(4):315–23.

    Article  PubMed  Google Scholar 

  18. Smith BM, Zhao N, Olivenstein R, Lemiere C, Hamid Q, Martin JG. Asthma and fixed airflow obstruction: long-term trajectories suggest distinct endotypes. Clin Exp Allergy 2020.

  19. Porsbjerg C, Menzies-Gow A. Co-morbidities in severe Asthma: clinical impact and management. Respirology. 2017;22(4):651–61.

    Article  PubMed  Google Scholar 

  20. Kritikos V, Harvey ES, Stevens S, Katelaris CH, Langton D, Rimmer J, Farah CS, Gillman A, Hew M, Radhakrishna N, Thomas D, Gibson PG. Comorbidities modify the phenotype but not the treatment effectiveness to Mepolizumab in severe eosinophilic Asthma. J Allergy Clin Immunol Pract. 2023;11(3):885–895e813.

    Article  CAS  PubMed  Google Scholar 

  21. Schoettler N, Strek ME. Recent advances in severe Asthma: from phenotypes to Personalized Medicine. Chest. 2020;157(3):516–28.

    Article  CAS  PubMed  Google Scholar 

  22. Ramsahai JM, Hansbro PM, Wark PAB. Mechanisms and management of Asthma exacerbations. Am J Respir Crit Care Med. 2019;199(4):423–32.

    Article  CAS  PubMed  Google Scholar 

  23. Annesi-Maesano I, Didier A, Klossek M, Chanal I, Moreau D, Bousquet J. The score for allergic rhinitis (SFAR): a simple and valid assessment method in population studies. Allergy. 2002;57(2):107–14.

    Article  CAS  PubMed  Google Scholar 

  24. Dixon AE, Sugar EA, Zinreich SJ, Slavin RG, Corren J, Naclerio RM, Ishii M, Cohen RI, Brown ED, Wise RA, Irvin CG. American Lung Association-Asthma Clinical Research C: Criteria to screen for chronic sinonasal Disease. Chest. 2009;136(5):1324–32.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Tay TR, Abramson MJ, Hew M. Closing the million patient gap of uncontrolled Asthma. Med J Australia. 2016;204(6):216–7.

    Article  PubMed  Google Scholar 

  26. Reddel HK, Sawyer SM, Everett PW, Flood PV, Peters MJ. Asthma control in Australia: a cross-sectional web-based survey in a nationally representative population. Med J Australia. 2015;202(9):492–7.

    Article  PubMed  Google Scholar 

  27. McDonald VM, Simpson JL, Higgins I, Gibson PG. Multidimensional assessment of older people with Asthma and COPD: clinical management and health status. Age Ageing. 2011;40(1):42–9.

    Article  PubMed  Google Scholar 

  28. Juniper EF, Guyatt GH, Epstein RS, Ferrie PJ, Jaeschke R, Hiller TK. Evaluation of impairment of health related quality of life in Asthma: development of a questionnaire for use in clinical trials. Thorax. 1992;47(2):76–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Irwin RS, Curley FJ, French CL. Difficult-to-control Asthma. Contributing factors and outcome of a systematic management protocol. Chest. 1993;103(6):1662–9.

    Article  CAS  PubMed  Google Scholar 

  30. Radhakrishna N, Tay TR, Hore-Lacy F, Hoy R, Dabscheck E, Hew M. Profile of difficult to treat Asthma patients referred for systematic assessment. Respir Med. 2016;117:166–73.

    Article  CAS  PubMed  Google Scholar 

  31. Appropriate body-mass. Index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157–63.

    Article  Google Scholar 

  32. Zhang XY, Liang J, Chen DC, Xiu MH, He J, Cheng W, Wu Z, Yang FD, Haile CN, Sun H, Lu L, Kosten TA, Kosten TR. Cigarette Smoking in male patients with chronic schizophrenia in a Chinese population: prevalence and relationship to clinical phenotypes. PLoS ONE. 2012;7(2):e30937.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Park MB, Lee TS, Lee JH, Lee J. Most patients with COPD are unaware of their health threats and are not diagnosed: a national-level study using pulmonary function test. Sci Rep. 2023;13(1):5893.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  34. Sprio AE, Ciprandi G, Riccardi E, Giannoccaro F, Carriero V, Bertolini F, Ricciardolo FLM. The influence of Smoking on Asthma in the real-life. Respir Med. 2020;170:106066.

    Article  PubMed  Google Scholar 

  35. Smith BM, Zhao N, Olivenstein R, Lemiere C, Hamid Q, Martin JG. Asthma and fixed airflow obstruction: long-term trajectories suggest distinct endotypes. Clin Exp Allergy. 2021;51(1):39–48.

    Article  PubMed  Google Scholar 

  36. Venkatesan P. GOLD COPD report: 2023 update. Lancet Respir Med. 2023;11(1):18.

    Article  PubMed  Google Scholar 

  37. Stachler RJ. Comorbidities of Asthma and the unified airway. Int Forum Allergy Rhinol. 2015;5(Suppl 1):17–22.

    Google Scholar 

  38. Corren J. The connection between allergic rhinitis and bronchial Asthma. Curr Opin Pulm Med. 2007;13(1):13–8.

    Article  PubMed  Google Scholar 

  39. Allergic Rhinitis and its Impact on Asthma (ARIA): achievements in 10 years and future needs. J Allergy Clin Immunol 2012, 130(5):1049–1062.

  40. Zerbib F, Guisset O, Lamouliatte H, Quinton A, Galmiche JP, Tunon-de-Lara JM. Effects of bronchial obstruction on lower esophageal sphincter motility and Gastroesophageal Reflux in patients with Asthma. Am J Respir Crit Care Med. 2002;166(9):1206–11.

    Article  PubMed  Google Scholar 

  41. Mallah N, Turner JM, González-Barcala FJ, Takkouche B. Gastroesophageal reflux Disease and Asthma exacerbation: a systematic review and meta-analysis. Pediatr Allergy Immunol. 2022;33(1):e13655.

    Article  PubMed  Google Scholar 

  42. Stubbs MA, Clark VL, Gibson PG, Yorke J, McDonald VM. Associations of symptoms of anxiety and depression with health-status, Asthma control, Dyspnoea, dysfunction breathing and obesity in people with severe Asthma. Respir Res. 2022;23(1):341.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Rogliani P, Laitano R, Ora J, Beasley R, Calzetta L. Strength of association between comorbidities and Asthma: a meta-analysis. Eur Respir Rev 2023, 32(167).

  44. Wang W, Lin J, Zhou X, Wang C, Huang M, Cai S, Chen P, Lin Q, Zhou J, Gu Y, Yuan Y, Sun D, Yang X, Yang L, Huo J, Chen Z, Jiang P, Zhang J, Ye X, Liu H, Tang H, Liu R, Liu C, Zhang W, Hu C, Chen Y, Liu X, Dai L, Zhou W, Huang Y, Xu J. Associations between comorbidities and annual incidence plus frequency of Asthma exacerbation hospitalisation during the past year: data from CARN study. BMC Pulm Med. 2022;22(1):261.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Feng M, Zhang X, Wu WW, Chen ZH, Oliver BG, McDonald VM, Zhang HP, Xie M, Qin L, Zhang J, Wang L, Li WM, Wang G, Gibson PG. Clinical and inflammatory features of exacerbation-prone Asthma: a cross-sectional study using Multidimensional Assessment. Respiration. 2020;99(12):1109–21.

    Article  PubMed  Google Scholar 

  46. Mallah N, Rodriguez-Segade S, Gonzalez-Barcala FJ, Takkouche B. Blood eosinophil count as predictor of Asthma exacerbation. A meta-analysis. Pediatr Allergy Immunol. 2021;32(3):465–78.

    Article  CAS  PubMed  Google Scholar 

  47. Gonzalez-Barcala FJ, San-Jose ME, Nieto-Fontarigo JJ, Carreira JM, Calvo-Alvarez U, Cruz MJ, Facal D, Garcia-Sanz MT, Valdes-Cuadrado L, Salgado FJ. Association between blood eosinophil count with Asthma hospital readmissions. Eur J Intern Med. 2018;53:34–9.

    Article  PubMed  Google Scholar 

  48. Zhu J, Message SD, Qiu Y, Mallia P, Kebadze T, Contoli M, Ward CK, Barnathan ES, Mascelli MA, Kon OM, Papi A, Stanciu LA, Jeffery PK, Johnston SL. Airway inflammation and Illness severity in response to experimental rhinovirus Infection in Asthma. Chest. 2014;145(6):1219–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Gonzalez-Barcala FJ, Calvo-Alvarez U, Garcia-Sanz MT, Garcia-Couceiro N, Martin-Lancharro P, Pose A, Carreira JM, Moure-Gonzalez JD, Valdes-Cuadrado L, Muñoz X. Asthma exacerbations: risk factors for hospital readmissions. Ir J Med Sci. 2018;187(1):155–61.

    Article  CAS  PubMed  Google Scholar 

  50. Boulet LP, Franssen E. Influence of obesity on response to fluticasone with or without salmeterol in moderate Asthma. Respir Med. 2007;101(11):2240–7.

    Article  PubMed  Google Scholar 

  51. Dixon AE, Holguin F, Sood A, Salome CM, Pratley RE, Beuther DA, Celedón JC, Shore SA. An official American Thoracic Society Workshop report: obesity and Asthma. Proc Am Thorac Soc. 2010;7(5):325–35.

    Article  PubMed  Google Scholar 

  52. King GG, Brown NJ, Diba C, Thorpe CW, Muñoz P, Marks GB, Toelle B, Ng K, Berend N, Salome CM. The effects of body weight on airway calibre. Eur Respir J. 2005;25(5):896–901.

    Article  CAS  PubMed  Google Scholar 

  53. Prasad B, Nyenhuis SM, Weaver TE. Obstructive sleep apnea and Asthma: associations and treatment implications. Sleep Med Rev. 2014;18(2):165–71.

    Article  PubMed  Google Scholar 

  54. Gonzalez-Barcala FJ, Nieto-Fontarigo JJ, Lourido-Cebreiro T, Rodríguez-García C, San-Jose ME, Carreira JM, Calvo-Alvarez U, Cruz MJ, Facal D, Garcia-Sanz MT, Valdes-Cuadrado L, Salgado FJ. Obesity does not increase the risk of Asthma readmissions. J Clin Med 2020, 9(1).

  55. Tonga KO, Chapman DG, Farah CS, Oliver BG, Zimmermann SC, Milne S, Sanai F, Jetmalani K, Berend N, Thamrin C, King GG. Reduced lung elastic recoil and fixed airflow obstruction in Asthma. Respirology. 2020;25(6):613–9.

    Article  PubMed  Google Scholar 

  56. Rutting S, Chapman DG, Badal T, Sanai F, Zimmermann SC, Thamrin C, King GG, Tonga KO. Higher body mass index is associated with increased lung stiffness and less airway obstruction in individuals with Asthma and fixed airflow obstruction. ERJ Open Res 2021, 7(1).

  57. Chipps BE, Hirsch I, Trudo F, Alacqua M, Zangrilli JG. Benralizumab efficacy for patients with fixed airflow obstruction and severe, uncontrolled eosinophilic Asthma. Annals of Allergy Asthma & Immunology: Official Publication of the American College of Allergy Asthma & Immunology. 2020;124(1):79–86.

    Article  CAS  Google Scholar 

  58. Huang S, Vasquez MM, Halonen M, Martinez FD, Guerra S. Asthma, airflow limitation and mortality risk in the general population. Eur Respir J. 2015;45(2):338–46.

    Article  PubMed  Google Scholar 

  59. Panizza JA, James AL, Ryan G, de Klerk N, Finucane KE. Mortality and airflow obstruction in Asthma: a 17-year follow-up study. Intern Med J. 2006;36(12):773–80.

    Article  CAS  PubMed  Google Scholar 

  60. Bennett GH, Carpenter L, Hao W, Song P, Steinberg J, Baptist AP. Risk factors and clinical outcomes associated with fixed airflow obstruction in older adults with Asthma. Ann Allergy Asthma Immunol. 2018;120(2):164–168e161.

    Article  PubMed  Google Scholar 

  61. van Dijk BCP, Svedsater H, Heddini A, Nelsen L, Balradj JS, Alleman C. Relationship between the Asthma Control Test (ACT) and other outcomes: a targeted literature review. BMC Pulm Med. 2020;20(1):79.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Zhang Q, Fu X, Wang C, Shen H, Zhu L, Shi G, Qiu Z, Wen Z, Gu W, Luo W, Zhao L, Chen Y, Lim S, Xiao C, Kang J, Zhang Y, Huang M, Xu J, Huang K, Li Q, Zhang X, Zhao J, Liu X, Sun S, Tang H, He B, Cai S, Chen P, Wei C, Wang G, Chen P, Xie L, Lin J, Tang Y, Han Z, Chung KF, Zhong N. Severe eosinophilic Asthma in Chinese C-BIOPRED Asthma cohort. Clin Transl Med. 2022;12(2):e710.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the participants who volunteered for the study. Thanks to Zhifeng Zhang for the detection of allergen-specific IgE.

Funding

This work was supported by National Natural Science Foundation of China (82270028, 81970060, 82000013, 82100028), Clinical Research Special Fund of Zhongshan Hospital (2020ZSLC26), Shanghai Municipal Key Clinical Specialty (shslczdzk02201), Clinical Research Plan of SHDC (SHDC2020CR1002A).

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Author notes

  1. Guiping Zhu, Yuqing Mo, Ling Ye contributed equally to this work.

Authors and Affiliations

  1. Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, 200032, Shanghai, China

    Guiping Zhu, Yuqing Mo, Ling Ye, Hui Cai, Yingying Zeng, Mengchan Zhu, Wenjun Peng, Xin Gao, Xixi Song, Chengyu Yang, Jian Wang, Zhihong Chen & Meiling Jin

  2. Department of Allergy, Zhongshan Hospital, Fudan University, 200032, Shanghai, China

    Guiping Zhu, Ling Ye, Yingying Zeng, Mengchan Zhu, Wenjun Peng, Xin Gao, Xixi Song, Chengyu Yang & Meiling Jin

  3. The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, 450008, Zhengzhou, China

    Yuqing Mo

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Contributions

MJ took responsibility for the content of the manuscript, including the data analysis, and manuscript preparation. GZ, YM, LY, HC, YZ and MZ analyzed the data and performed the statistical analysis. JW, ZC and MJ designed the research study. GZ, YM, JW and MJ drafted the manuscript. WP, XG, XS, CY interpreted the data and revised the manuscript. All authors reviewed the manuscript for critical content. All authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Jian Wang, Zhihong Chen or Meiling Jin.

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Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and received permission from the ethics committee of Zhongshan hospital, Fudan University (approval number: B2019-020R). This study was exempt from informed consent by the approval of the ethics committee of Zhongshan hospital, Fudan University because of the retrospective nature of the study.

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Zhu, G., Mo, Y., Ye, L. et al. Clinical characteristics of obese, fixed airway obstruction, exacerbation-prone phenotype and comorbidities among severe asthma patients: a single-center study. BMC Pulm Med 24, 76 (2024). https://doi.org/10.1186/s12890-023-02835-4

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Keywords

BMC Pulmonary Medicine

ISSN: 1471-2466

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