Severe Asthma and Sleep Disorders: A Severe Asthma Network Italy (SANI) Registry Analysis

Introduction

Asthma is a chronic inflammatory disease of the airways that affects up to 18% of people worldwide,¹ characterized by dyspnea, wheezing, coughing, chest stiffness, variable airflow obstruction, bronchial hyperresponsiveness and recurrent exacerbations. According to Global Initiative for Asthma (GINA), severe asthma is defined as uncontrolled disease despite adherence with maximal optimized high dose of inhaled corticosteroids (ICS) plus long-acting beta2-agonists (LABA) treatment and management of contributing or worsening factors, or that worsen when high dose treatment is decreased.² Currently, epidemiologic data on severe asthma are still limited. According to the European Network For Understanding Mechanisms Of Severe Asthma (ENFUMOSA), about 10% of the asthmatic population develops severe asthma.² A poor asthma control leads to hospitalization, disability, and higher risk of death.³ Over the past ten years, it has been increasingly recognized that asthma can be linked with various disorders that influence the unique symptomatic experience of each patient and may lead to a condition that is challenging to manage.³ Patients with poorly controlled asthma frequently need long-term oral corticosteroids (LTOCS) resulting in potential oral corticosteroids (OCS)-related comorbidities (sleep apnea, hypertension, dyslipidemia, and adrenal insufficiency),³ moreover, they usually suffer from gastroesophageal reflux disease (GERD),⁴ chronic rhinitis and rhinosinusitis (with or without polyps),^5,6 dysfunctional breathing, and obesity,⁷ among others. The combination between cough and/or asthma, obstructive sleep apnea (OSA), rhinosinusitis, and esophageal reflux generates a syndrome known as CORE (Cough/asthma, Obesity/OSA, Rhinosinusitis, and Esophageal reflux).⁸ Allergic rhinitis, a very common comorbidity in severe asthmatics^3,5 and with unique pheno-endotypic characteristics,⁹ also has a direct impact on sleep disorders (SD),¹⁰ including OSA; when allergic rhinitis and asthma are comorbid, the risk of developing OSA further increases.¹¹ Interestingly, many asthmatic patients refer SD such as frequent awakenings, snoring and daytime drowsiness, and these conditions have a relevant impact on the quality of life of patients with asthma, including those affected by severe asthma. The term sleep disorders embrace a spectrum of breathing abnormalities including mainly OSA, snoring, respiratory-related arousals and hypoventilation.¹² OSA is a complex pathology influenced by numerous factors such as craniofacial structure, obesity, upper airway collapsibility, muscle tone reduction during sleep, lower arousal threshold and ventilatory control.¹³ Snoring and arousal are generally self-reported or reported by the partner with whom the patient shares the bed. The frequent coexistence of Asthma and Sleep disorders causes a significant impairment in health-related quality of life (HRQoL).¹⁴ In this study, we attempt to analyze the link between sleep disorders and patients with severe asthma enrolled in the Severe Asthma Network Italy (SANI),¹⁵ a registry designed to identify the prevalence and characteristics of within a real-world context.¹⁶ We want to investigate the prevalence and overall disease burden of patients affected by sleep disorders in this cohort and identify their clinical features, risk factors and treatable traits.

Materials and Methods

Study Population

Severe Asthma Network Italy (SANI)¹⁵ is a disease registry that gathers clinical, functional and demographic data on patients with severe asthma. Among the clinical features collected in the registry there are also several possible comorbidities of severe asthma, including allergic rhinitis, chronic rhinosinusitis with or without nasal polyps, cardiovascular diseases, gastroesophageal reflux and sleep disorders. All these comorbidities are tracked in the registry as individual variables, leaving the investigators at each center responsible for entering accurate information based on the diagnostic tests required by the guidelines of each single comorbidity. The inclusion criteria for being enrolled in the SANI registry are: a confirmed diagnosis of severe asthma according to European Respiratory Society (ERS)/American Thoracic Society (ATS) classification,¹⁷ being aged ≥12 years, and giving informed consent to participate in the study. Briefly, ERS/ATS recommendations define as severe asthmatic a patient that, despite high doses of ICS plus another controller or chronic oral corticosteroid therapy for at least 6 months in the previous year, is still clinically uncontrolled (altered Asthma Control Test and/or Asthma Control Questionnaire), or experiencing at least 2 acute asthma exacerbations per year (or at least one severe exacerbation requiring emergency department admission, or hospitalization or intubation), or is still having a compromised lung function (FEV1<80% predicted value).¹⁷ No exclusion criteria are foreseen to guarantee the most complete and real-life picture possible of patients affected by severe asthma in Italy.¹⁵ Patients are enrolled in certified centers spread throughout Italy. Every center was selected according to inclusion criteria involving staff and equipment standards, diagnostic and research criteria defined by protocol approved by the Central Ethics Committee (see below).

We performed a retrospective analysis on the data from SANI registry to investigate the prevalence of sleep disorders and the clinical features of this comorbidity in patients with severe asthma. Patients were stratified based on the presence or absence of sleep disorders at their baseline visit in the SANI registry. Symptoms of sleep disorders (snoring and clinical diagnosis of OSA) were confirmed by the investigators from the various clinical centres that support the SANI initiative.

Statistical Analysis

Continuous variables were expressed as mean ± standard deviation or median and interquartile range, as appropriate, while categorical variables were represented as counts and percentages. Differences in the distributions of demographic and clinical characteristics among subjects with or without sleep disorders were evaluated using Student’s t-test for means, Wilcoxon–Mann–Whitney for medians and Chi-squared test for proportions. For all variables with at least one expected count less than 5, Fisher’s exact test was used instead of a chi-squared test.

A multivariable logistic regression was performed to assess the association of demographic and clinical variables with the presence of sleep disorders (yes vs no). Variables having a significant univariate test (p-value <0.05) and with less than 10% of missing values were selected for the multivariable analysis. We excluded highly correlated variables (eg, if body mass index, BMI was selected, height and weight were excluded). Therapies were also excluded since they were directly related to predictors of disease severity and including them would result in biased estimates of the variables of interest (collider bias).

A two-tailed p-value <0.05 was considered statistically significant. Statistical analyses were performed using SAS statistical software version 9.4.

Ethical Issues

The study was carried out according to the declarations of Helsinki and Oviedo. The SANI registry¹² was set up according to the 3rd Edition Recommendation on registries for evaluating patient outcomes published by the Effective Health Care Program of the Agency for Healthcare Research and Quality.¹⁸ The protocol was performed according to the principles and procedures of the Good Clinical Practice (ICH Harmonized Tripartite Guidelines for Good Clinical Practice 1996; Directive 91/507. EEC, The Rules Governing Medical Products in the European Community) and according to the Italian laws (Legislative Decree n.211, 24 June 2003; Legislative Decree n.200 6 November 2007; Health Ministry Decree, 21 December 2007). The Registry Protocol, with the Project Code OR00617 and the study number 1742, has been approved by the Central Ethics Committee; the enrolment in the other centres started upon approval of each local Ethics Committee. All enrolled patients signed an informed consent.

Results

Out of 2042 patients in the registry, 219 were excluded for lack of sleep data. Of the remaining 1823 patients, 475 (26.1%) patients had SD: 374 (20.5% of the entire study population, corresponding to 78.7% of patients with reported SD) with snoring and 101 (5.5% of the entire study population, corresponding to 21.3%) with OSA (Figure 1). Patients with SD were more frequently men (214, 45.1% vs 480, 35.6%, p<0.001) and overweight (median BMI [IQR]: 27.3 [23.9–31.6] vs 25.2 [22.3–28.2], p<0.001 (Table 1).

Table 1 Demographic Characteristics in Patients with and without Sleep Disorders

Figure 1 Flowchart of patients’ selection.

Patients with SD had more frequently rhinitis ever in their lives (356, 75.6% vs 812, 60.8%, p<0.001). Moreover, patients with SD that experienced rhinitis were more prone to have moderate to severe disease (Table 2). Chronic rhinosinusitis without nasal polyps (CRSsNP) and with nasal polyps (CRSwNP) were more frequent in patients with SD (172, 37.1% vs 341, 26.3%, p<0.001 and 266, 56.2% vs 554, 41.3%, p<0.001, respectively). Patients with CRSwNP and SD had a higher extension of polyps in nasal cavities compared to those without SD as reported in Table 2. Moreover, the prevalence of gastroesophageal reflux disease (GERD) in patients suffering also from SD was higher than those without SD (251, 53.2% vs 467, 34.8%, p<0.001), as well as cardiovascular diseases (CVD) (181, 40.1% vs 293, 23.7%, p<0.001), and diabetes mellitus (37, 8.2% vs 55, 4.4%, p=0.004) (Table 2). The multivariable logistic regression confirmed that several factors were significantly associated with SD. Higher BMI was a significant predictor (OR = 1.10, 95% CI = 1.07–1.14, p < 0.001). Moderate-to-severe persistent rhinitis showed a strong association (OR = 2.52, 95% CI = 1.65–3.85, p < 0.001), as did a history of CRSsNP in the past (OR = 1.83, 95% CI = 1.15–2.89, p = 0.010). CRSwNP was also associated with increased risk (OR = 1.77, 95% CI = 1.28–2.45, p<0.001), along with confirmed GERD (OR = 1.81, 95% CI = 1.29–2.53, p <0.001) and suspected GERD (OR = 2.86, 95% CI = 1.87–4.40, p < 0.001). CVD was another significant factor (OR = 1.53, 95% CI = 1.09–2.13, p = 0.014) (Figure 2).

Table 2 Comorbidities in Patients with and without Sleep Disorders

Figure 2 Results of multivariable logistic regression to assess the association of demographic and clinical variables with the presence of sleep disorders (yes vs no). Abbreviations: BD, bronchodilator; BMI, body mass index; CRSsNP, Chronic rhinosinusitis without nasal polyps; CRSwNP, Chronic rhinosinusitis with nasal polyps; CVD, cardiovascular disease; FEV1, forced expiratory volume in the first second; GERD, gastroesophageal reflux disease.

Patients with SD, had higher mean Forced Expiratory Volume in the first second values (FEV1% 77.4±24% vs 73.9±21.8%, p=0.014) but worse Asthma Control Test (ACT: mean 16.8±5.3 vs 18±5.2, p<0.001) and quality of life (Asthma Quality of Life Questionnaire, AQLQ: mean 4.3±1.4 vs 4.7±1.4, p<0.001). Patients with SD had higher number of missed working days (median [IQR]: 0 [0–12] vs 0 [0–5], p<0.001) and, though statistically non-significant, an increase in disease-related hospital admissions (71, 15.7% vs 145, 11.5%, p 0.052). Additionally, a higher proportion of patients had at least an unscheduled medical visit (162, 40.5% vs 265, 26.0%, p<0.001) was observed in patients with SD. Moreover, patients with SD had a higher number of exacerbations needing systemic corticosteroid treatment (median [IQR]: 2 [0–4] vs 1 [0–3], p=0.002), as well as a generally higher occurrence of exacerbation needing oral corticosteroids (OCS) (300, 69.4% vs 729, 61.8%, p=0.005) (Table 3).

Table 3 Asthma Features in Patients with and without Sleep Disorders

Furthermore, patients with SD used more frequently intranasal corticosteroids (139, 29.3% vs 247, 18.3% p<0.001). About biological therapies, no significative difference was found among the two populations of severe asthmatic patients with and without sleep disorders (189, 39.8% vs 597, 44.3%, p 0.099) (Table 4).

Table 4 Treatments Administered to Patients with and without Sleep Disorders

Discussion

In this analysis of SANI registry data, we found that about one out of four patients with severe asthma suffer from SD. Asthma has been described to be more severe if sleep disorders coexist.¹⁹ The link between asthma and sleep disorders complicates the disease management and affects the severity of symptoms, quality of life and overall healthcare burden.²⁰ Therefore, sleep disorders should be considered a treatable trait when assessing patients with severe asthma since the vicious cycle between the two diseases amplifies and destabilizes the pathologies taken individually.²¹ Our study is one of the first observational registry-based studies examining the prevalence of sleep disorders in a large population of adults with severe asthma. The high prevalence of sleep disorders in our cohort underscores the importance of considering sleep disorders as a comorbidity in patients with severe asthma.²² Considering the limit that not all the patients had performed a polysomnography, the discrepancy between snoring and OSA could reflect an underdiagnosed OSA or other respiratory-related sleep disorders. Furthermore, the relatively low number of patients with a diagnosis of sleep apnoea (that need confirmation by polysomnography) compared to patients who only reported snoring, could highlight the need of a more detailed screening protocol in all patients suffering from severe asthma.

In our study, SD were more frequent overweight patients, supporting the existing literature that identifies overweight as a common risk factor for sleep disorders such as obstructive sleep apnoea²³ because it promotes upper airway collapse.²⁴ The significantly higher mean BMI in patients with sleep disturbances suggests a potential area for intervention, as weight reduction has been shown to improve sleep apnoea symptoms. Interesting is the evidence showing no significant correlation between smoking and sleep disorders in this cohort, which contrasts with some previous studies that have suggested a potential link.²⁵ It is important to consider this data in the context of the study’s demographic or the possibility that the impact of smoking might be overshadowed by the severity of the patients’ existing respiratory conditions.

Moreover, our study shows that rhinitis, especially the persistent moderate/severe type, and chronic rhinosinusitis (both with or without nasal polyps), are significantly more frequent in patients with severe asthma and sleep disorders. These conditions contribute to the breathing abnormalities, snoring, apnea and arousal typically found in sleep disorders.²⁶ As seen in a previous SANI study⁶ patients affected by severe asthma and chronic rhinosinusitis with nasal polyps were more prone to be frequent exacerbators with a significantly higher oral corticosteroids exposure. These observations support the notion that CRSwNP may be a part of a distinctive clinical phenotype of asthma with shared inflammatory pathways and mechanical effects influencing both upper and lower airways. We can therefore speculate that treating the upper airways could ameliorate SD and asthma. This speculation is supported by a recent finding of very rapid improvement of SD in patients with CRSwNP (most of them with concomitant asthma) treated with Dupilumab.²⁷

More than a half of our patients with severe asthma and SD also have GERD, in line with previous studies,³ and its presence is associated with higher risk to have SD. Although this is a common disease, this condition induces mucosal inflammation causing spasm of the upper-airway and oedema, which could worsen asthma and promoting SD.²⁸ These mechanisms generate a vicious circle that perpetuates itself, amplifying and destabilizing the two diseases.^29,30

The finding about higher rate of CVD in our patients with severe asthma and SD is supported by a previous study of by Xu M. et al,³¹ that links asthma and increased CVD rate by chronic systemic inflammation, an underlying condition in asthmatic state.³² Moreover, our population group suffering from SD is frequently overweight or obese. Obesity and an increased intra-abdominal adipose tissue are the leading causes of metabolic syndrome and type II diabetes,^33,34 whose prevalence in our study is higher in patients with SD. It is also important not to underestimate the side effects of long-term oral corticosteroids therapy needed by patients with poorly controlled severe asthma. Indeed, several studies reported increased rates of diabetes mellitus, obesity, and CVD in patients with severe asthma and long-term OCS use compared with patients with milder disease and less or no OCS use.^35–37

Interestingly, our patients with SD showed less severe lung function impairment but worse control and quality of life, with an increased number of asthma exacerbations, unscheduled medical visits and higher OCS exposure. The finding that these patients have worse asthma control and quality of life, despite less severe functional impairment based on FEV1, may indicate that sleep disturbances are an important factor in the overall management of asthma. As found by Teodorescu et al, individuals with OSAS are 3.6 times as likely to have uncontrolled asthma,³⁸ that leads to a higher number of disease-related hospital admissions and the need of non-programmed medical visit.

As previously mentioned, patients with severe asthma and SD also presented a higher exacerbation rate needing steroid treatment and higher frequency of maintenance OCS therapy. These data define a more difficult-to-treat asthma phenotype that need to be further investigated, and it might be indicative of the complex interplay between sleep and asthma control, suggesting that treatment for sleep disorders might be an overlooked therapeutic target to reduce the need for intensive asthma therapy and improve outcomes. Based on this compelling data, physicians should be aware that treatment of patients with severe asthma and sleep disorders has the potential to improve patient outcomes and reduce healthcare burden.

Considering the overall results of our study, we confirm and strengthen the concept that sleep disorders are a common and relevant clinical feature among patients with severe asthma, and physicians should consider investigating patients’ sleep quality in their daily clinical practice. It is important to consider asthma and sleep disorders as two entities which can influence each other, and only treating properly both we could improve patient quality of life and reduce healthcare burden. Personalized therapeutical approaches, focused on modifying and treating comorbidities, including sleep disorders, are therefore necessary to guarantee a better management of asthma and so a better health outcome.

This study has some limitations that are intrinsic to the real-life nature of the registry from which the data derive: in particular, being a registry of patients with severe asthma, it is possible that not all patients were systematically evaluated for suspected sleep disorders and even fewer patients underwent a polysomnographic examination to confirm the suspicion of OSA; furthermore, it is also plausible that not all centers to which patients refer have equal expertise in the management of sleep disorders, leading to possible differences in the management of these comorbidities across the centers. However, we believe that, even taking these limitations into account, our results are relevant in highlighting the complicated relationship between severe asthma and sleep disturbances.

Further research should focus on examining the long-term impact of therapy for OSA on clinical outcomes in asthma. The known overlap of the two diseases, the shared risk factors and the fact that treating one improves symptoms and outcome of the other one, could make us think about the coexistence of asthma and OSA as a single disease or to consider the asthmatic patient with OSA as a particular patient phenotype.