Correlation between fractional exhaled nitric oxide and Asthma Control Test score and spirometry parameters in on-treatment-asthmatics in Ho Chi Minh City
Introduction
Asthma is a chronic inflammatory disease of the airway. The aim of asthma management is to control the background inflammation and allow patients to achieve and maintain asthma control (1). In asthma, the prominent inflammatory mechanism is Th2-driven inflammation (also called eosinophilic inflammation) (2-4). Among various methods used to determine and measure this type of airway inflammation, fractional exhaled nitric oxide (FeNO) is currently the simplest and most reliable tool in clinical practice (5,6). In 2011, the American Thoracic Society (ATS) published guidelines for the use of FeNO, stating that FeNO is a simple, quantitative, noninvasive and safe tool to measure airway eosinophilic inflammation in asthma (7).
Currently, clinicians always consider factors related to asthma control and asthma severity to support clinical decision-making in asthma management. For asthma control in Vietnam, besides use of the Global Initiative for Asthma (GINA) criteria, the Asthma Control Test (ACT) questionnaire is most frequently used to assess asthma control and is validated for use in Vietnam (8,9). For asthma severity, although GINA (from 2014 onwards) recommends to use their treatment steps to determine patients’ asthma severity, spirometry is still used in many countries (including Vietnam) as an important indicator for potential adverse outcomes and for information on asthma severity (10,11). To evaluate the role of FeNO in asthma management, the relationship between FeNO and asthma control and asthma severity was tested and an association was found between FeNO and the ACT score, as well between FeNO and spirometry parameters (12-19). However, no data are available to confirm whether this relationship also exists in asthmatic patients in Vietnam.
Therefore, the present study aimed to determine possible correlations between FeNO and the ACT score and between FeNO and patients’ spirometry parameters.
Methods
Study design and setting
This was a prospective cross-sectional study that involved 410 eligible participants who are ambulatory patients and recruited between March 2016 and March 2017 at the Asthma & COPD Clinic, University Medical Center, Ho Chi Minh City, Vietnam.
Ethical approval
The study protocol was approved by the Institutional Review Board of the University of Medicine & Pharmacy at Ho Chi Minh City, Vietnam. All patients and authorized representatives were given a written informed consent and those who participated or their representative in this study had to sign this consent form.
Inclusion and exclusion criteria
Patients that were eligible for inclusion in this study were (I) aged ≥12 years, (II) diagnosed at least 6 months previously with asthma according to GINA 2015 (had asthma symptoms and evidence of bronchodilator reversibility test—FEV1 change ≥12% and 200 mL after inhale 4 puffs (400 mcg salbutamol) of Ventolin®), (III) treated and followed-up by doctors at this clinic, and (IV) had sufficient command of the Vietnamese language to respond to questionnaires.
Excluded were patients meeting any of the following exclusion criteria: (I) diagnosed with allergic rhinitis and other skin atopic conditions, (II) hospitalized for asthma or had an acute upper or lower respiratory tract infection within 4 weeks prior to this study; (III) had a known respiratory disorder other than asthma and/or systemic/thoracic abnormalities that might influence normal lung function; (IV) currently smoking or had smoked >10 pack-years; (V) did not adhere to their treatment more than 2 weeks within 3 months prior to the study.
Sample size and sampling technique
Sample size required to determine whether a correlation coefficient differs from zero was calculated from this formula (20): N=[(Zα+Zβ)/C]2 +3
With α (two-tailed) =0.05 (Type I error rate), β =0.20 (Type II error rate), C =0.5*ln[(1+r)/(1−r)] and estimated correlation coefficient r=0.15 → n=347. The higher the correlation coefficient, the lower the sample size.
Data collection
- Asthma Control Test (ACT): this test comprises five questions assessing the frequency of shortness of breath, frequency of asthma nighttime symptoms, degree of functional limitation, frequency of using rescuers, and patient’s self-assessment of their level of asthma control. Each item has five response choices (each with a score ranging from 1–5). Accordingly, the level of asthma control is categorized as follows: controlled (scores 20–25), partially controlled (scores 15–19), and uncontrolled (scores <15) (8). The Vietnamese version of the ACT questionnaire has been validated (8) and was used in this study.
- FeNO measurement: FeNO was measured by a Niox Mino device (Aerocrine AB, Solna, Sweden) at flow rate of 50 mL/s for 10 seconds, according to the user’s manual (21,22). FeNO measurement was performed according to the ATS/European Respiratory Society (ERS) 2005 recommendations, Single-Breath online measurement with flow rate of 50 mL/s (23). Participants who were indicated for FeNO measurement underwent this test before performing the spirometry test to avoid distort the spirometry's results.
- Spirometry: this was conducted using a Koko spirometer (nSpire Health, USA) following the manufacturer’s instructions (24). Calibration of the device and and preparation of the patients before measurement was in accordance with the ERS/ATS 2005 recommendations (25). Participants performed spirometry after FeNO measurement. Spirometry variables comprised FVC% predicted (%FVC), FEV1% predicted (%FEV1), FEV1/FVC, PEF% predicted (%PEF), and FEF25–75% predicted (%FEF25–75).
Statistical analysis
Data were processed with Epidata software and analyzed using STATA 12.0 software. Ratio variables are presented as mean and standard deviation (SD). Student’s t-test was used to compare the means of two groups and one-way ANOVA to compare the means of multiple groups for normally distributed data. Mann-Whitney U-test and Kruskal Wallis test were used to compare the median of two groups or of more than two groups, respectively, for non-normally distributed data. Correlations between FeNO and the other outcomes were analyzed using Spearman’s correlation test. A P value ≤0.05 was considered statistically significant. In this study, the results showed that FeNO was not associated with age, gender, BMI, duration of disease, current respiratory symptoms, history of cigarette smoking, family history of allergy and trigger factors. Thus, it seems that the influence of these epidemiological features on the correlation between FeNO and ACT or FeNO and spirometry was not much then multivariate regression was not used in this analysis.
Results
Characteristics of study population
Of the 435 patients participated to the study, 25 (6%) were excluded from the analysis because of the following reasons: 8 patients failed to perform standard spirometry (did not meet ATS/ERS criterion A, B, C and D) (25-27); 9 patients failed to be measured FeNO; 2 patients did not know how to respond to ACT questionnaire and 6 patients were suspected to have asthma and COPD overlap (ACO). There were 410 participants whose data were analyzed with mean age of 42 (range, 12–76) years and 65% were female (Table 1). The mean and median ACT score were 20.5 and 21.0; mean and median FeNO were 29.5 and 24.0 parts per billion (ppb). Additional functional and biological patient characteristics are presented in Table 1. FeNO was divided into three groups according to the ATS category, i.e., mild (<25 ppb), moderate (25–50 ppb) and high (>50 ppb) (7) and the percentages of these groups were 52%, 33% and 15%, respectively. Epidemiological features of asthmatic patients (such as age, gender, BMI, duration of the disease, current respiratory symptoms, history of cigarette smoking, family history of allergy and trigger factors) may affect to FeNO results so they can influence to the correlation between FeNO and ACT or between FeNO and spirometry parameters. Therefore, a comparison of means of FeNO among subgroups of patients with different epidemiological features was presented in Table 2.
Full table
Full table
FeNO was not associated with age, gender, BMI, duration of disease, current respiratory symptoms, history of cigarette smoking, history of allergy and trigger factors (all P>0.05).
Treatment may affect all main variables such as FeNO, ACT and spirometry indexes; therefore Table 3 was created to determine this influence. FeNO is not different among three groups received step 2, 3 and 4 of GINA treatment but ACT and obstructive spirometric parameters (%FEV1, FEV1/FVC and %PEF) are significantly different among these three groups.
Full table
Correlations between FeNO and the ACT score are presented in Figure 1; Spearman’s correlation coefficient was r=−0.224 (P<0.001). Spearman’s correlation coefficients for FeNO and the spirometry variables were displayed in Table 4. However, bronchodilators such as LABAs may influence in airflow limitation and so distort these correlations, therefore a subgroups analysis with and without LABA component in patients’ treatment were investigated. In LABA subgroup, all obstructive spirometric parameters (%FEV1, FEV1/FVC, %PEF, %FEF25–75) but not restrictive spirometric parameter (%FVC) correlated with FeNO and these correlations are similar to correlations in the whole study population. However, the correlations in non-LABA subgroups are opposite with correlations in LABA subgroup.
Full table
Table 5 shows differences in mean FeNO in the subgroups of patients with different levels of spirometry variables (categorized as normal vs. abnormal; or as levels of abnormality). Medians of FeNO are significantly different in subgroups of asthmatic patients having different ACT scores, %FEV1, %PEF and %FEF25–75 (%FEF25–75 in both scenarios e.g., in whole participants and in those who have FEV1/FVC >0.7). Because FEF25–75 can represent small airway airflow obstruction in an early stage before FEV1 and FEV1/FVC become abnormal, and because FeNO also measures airway inflammation in asthma associated with small airway obstruction (28), Tables 4 and 5 (in addition to data on the whole participants) also show the relationship between FeNO and %FEF25–75 as determined in patients with no obstructive syndrome (i.e., Gaensler index, FEV1/FVC >0.7).
Full table
Discussion
The results of this study showed that FeNO was not associated with many epidemiological features of asthmatic patients such as age, gender, BMI, duration of the disease, current respiratory symptoms, history of cigarette smoking and family history of allergy and having trigger factors (Table 2). This finding was supported by many previous studies although some others had opposite results. For example, one study in Vietnam found that FeNO in healthy people was not associated with epidemiological factors of the participants such as age, gender, weight, BMI except a fair correlation with height (29). Regarding the relationship between FeNO and genders, Olivieri and colleagues found that there was a difference between the sexes in which women had lower FeNO than men, and this finding was reported in studies (30-38). On the other hand, many other authors found that this relationship did not exist (29,39,40). In term of age, studies showed that there was a correlation between FeNO and age in children (18,32,41-44) but not in adults (7,30,35,36,40). Allergic symptoms were proven to increase FeNO in patients with and without asthma; however, this statement is not always true (7,45). In a study of adult patients, Kalpaklioglu found no difference in the levels of oral FeNO among patients with allergic rhinitis, with non-allergic rhinitis, or healthy persons. In addition, FeNO levels are higher in patients having non-allergic rhinitis with asthma than those having allergic rhinitis with asthma (46). With the above information, FeNO results seem not to be much interfered by many epidemiological features of asthmatic patients, thus ATS 2011 recommended using threshold of FeNO rather than using predictive values like in spirometry (7).
In the present study, most patients (66%) were categorized as having well controlled asthma based on their ACT scores (ACT 20–25) and only 10% had uncontrolled asthma (ACT 5–14) (Table 5). However, the relatively high mean FeNO (29.5 ppb) of 410 on treated patients (with GINA step 2–4) indicates that airway inflammation still occurs in asthmatic patients receiving treatment according to the GINA guidelines. This finding is consistent with earlier observations. For example, Gemicioglu et al. investigated 416 on-treatment-asthmatics and found that mean FeNO was 31.8 ppb using the same measurement device as used in the present study (Niox Mino) and with a similar ACT score (19 vs. 20.5 in the present study) (32). In addition, our FeNO data are similar to other studies worldwide investigating on-treatment-asthmatics: e.g., 31.5 ppb in the USA (47), 31 ppb in Nepal (48) and 38.4 ppb recently reported in India (16).
The mean FeNO in well-controlled asthmatic patients in the present study (26.9 ppb, not presented in result part) was higher than the lower threshold of the ATS categorization (<25 ppb) (7), this result and other reports indicated that it is difficult to completely control airway inflammation by optimal intervention and the airway inflammation even still exist in ex-asthma patients (49,50). Because there is no comparable study on FeNO in Vietnam, no direct comparison can be made with an asthmatic Vietnamese population. However, previous studies on FeNO in Vietnam are mentioned here to provide a brief overview of FeNO levels in this land. For example, based on two small studies (conducted in the middle and the south of Vietnam), mean FeNO ranged from 10.4 to 15.7 ppb in healthy persons (29,51) compared to 31.1 ppb (51) and 18.8 ppb (51) in ACO and COPD patients, respectively. These comparisons imply that FeNO in treated asthmatics is much higher than that of COPD patients or of healthy persons. These findings confirm previous reports showing that airway inflammation cannot be completely suppressed by optimal treatment, or that inflammation persists even in ex-asthmatics (asthmatics had no abnormal symptoms and signs and had no treatment) (49,50).
A negative and weak correlation was found between FeNO and the ACT score (Spearman's r =−0.224, P<0.001); in addition, mean FeNO level increases when ACT-based asthma control levels deteriorate (Table 5). This means that FeNO can reflect asthma control (as also reported in many studies). The negative and weak correlation between FeNO and ACT score exists both in steroid naive asthmatics and in asthmatics-on-treatment. In steroid naive patients, some correlations reported by others researchers are stronger than ours, e.g., Senna et al. (12) (n=27, r =−0.69, P=0.001), Bernstein et al. (14) (n=55, r =−0.48, P<0.001), Mohan et al. (52) (n=96, r =−0.75, P<0.001) and Kavitha et al. (16) (n=151, r =−0.76, P<0.001). In treated patients, similar to the present population, the correlations are much weaker than in the naive group, e.g., Shirai et al. (15) (n=105, r =−0.31; P=0.003), Gutierrez et al. (53) (n=441, r =−0.16; P<0.01), Habib et al. (54) (n=53, r =−0.581; P<0.0001), Gemicioglu et al. (32) (n=416, r =−0.31; P=0.002), Mohan et al. (52) (n=96, r =−0.65; P<0.001) and Kavitha et al. (16) (n=151, r =−0.68; P<0.001). However, other groups found no correlation between these two variables. For example, Han et al. (55) and Yangui et al. (56) found no correlation whereas Bernstein et al. (14) found this association in their untreated group but not in their treated group. In Vietnam, a unique study including 42 children found no correlation between FeNO and the other variables investigated (57). The present study found that FeNO value was higher in the groups with lower levels of asthma control. Similarly, Papakosta et al., Shirai et al. and Habib et al. also reported that the means/medians of FeNO showed a significant difference between the two/three groups with different asthma control levels, with higher FeNO in the worse asthma control group (13,15,54).
In asthma, chronic airway inflammation can result in chronic airflow limitation. Whereas airway inflammation plays a key role in the pathogenesis of asthma, it is less clear whether poor lung function is associated with severe inflammation. Although some studies found an association between higher levels of inflammatory markers and more severe airflow limitation, there is no consensus (11,12,58-60). The spirometry parameters %FEV1 and %FEF25–75 have received increasing attention regarding this association (12,59). The present study found that almost all variables related to airway obstruction, e.g., %FEV1, %PEF, %FEF25–75 and the Gaensler ratio (FEV1/FVC), had a significant correlation with FeNO. However, the parameter related to airway restriction (%FVC) was not correlated with FeNO (Table 4). This finding is similar to result in another Vietnamese study in which FeNO have a significant association with FEV1, FEV1/FVC and PEF (61). Contrary to the present study’s results, Gemicioglu et al. found no association between FeNO with any spirometry parameters in 2 recent studies (32,44). However, in the present study, when subgroups of patients with and without LABA component in their treatment was analyzed, the correlations between FeNO and obstructive spirometric indexes (%FEV1, Gaensler ratio, %PEF, %FEF25–75) only happen in LABA treatment group but not in non-LABA treatment group and vice versa with restrictive index (%FVC).
Regarding FeNO and %FEV1, Kavitha et al. reported that FeNO had a strong correlation with FEV1 (n=151, r =−0.78, P<0.001) (16) and Torre et al. (17), Leung et al. (18) and Surja et al. (62) found that FeNO correlated with FEV1 with coefficients of r =−0.2 (n=96, P=0.03), r =−0.221 (n=92, P=0.014) and r2=0.403 (n=56, P=0.001), respectively. In pregnant women, Nittner-Marszalska et al. also found a correlation between FeNO and FEV1 (n=72, r =−0.21; P=0.0014) (19). Nevertheless, many researchers reported that no such association was found such as Senna (n=27, r =−0.24, P=0.23) (12), Yangui (n=37, r =−0.02, P>0.05) (56), Silkoff (63), Xia (n=57, r =−0.186, P>0.05) (64), Zietkowski (n=101, r =0.02, P=0.87) (59), Dal Negro (n=20, r =−0.38, P>0.05) (65) and Stirling (n=52, P=0.73) (66).
It is well established that inflammation in asthma involves the large airways; however, small airways are now widely accepted as a major site of inflammation (67). The mid-flow rates measured during spirometry testing (FEF25–75) are believed to represent small airway airflow (68,69). Since FEF25–75 is generally considered to be an approximate measure of distal airways caliber, reduced FEF25–75 is considered to represent small airways obstruction caused by asthma inflammation (70,71). FeNO is a biomarker of airway inflammation in asthma which is associated with small airway obstruction (28). Several studies found that %FEF25–75 is significantly related with FeNO (72-77). Tosca et al. reported that FeNO correlated with %FEF25–75 (n=56, r =−0.33; P=0.01) (78) and del Giudice et al. found a correlation between FeNO and %FEF25–75 (n=37, P<0.0098; r =0.439) (79). In asthmatic children, Lim et al. divided %FEF25–75 into two groups (group 1 with normal %FEF25–75, i.e., ≥65%, and group 2 with abnormal %FEF25–75 i.e., <65%) and found a correlation with FeNO in group 2 (n=28, r =−0.493, P=0.038) but not in group 1 (n=90, r =−0.037; P=0.749) (80). In adults, Malerba et al. found that FeNO was correlated with %FEF25–75 (81). However, other studies in adults, e.g., Nishimoto et al. (44) and Silkoff et al. (63), found no such correlation. The present study shows a weak correlation between FeNO and %FEF25–75; however, FeNO in the abnormal %FEF25–75 group (%FEF25–75 <65%) was significantly higher than that of the normal %FEF25–75 group (%FEF25–75≥65%) (30.0 vs. 20 ppb; P<0.001, compare FEF25–75 in Table 5).
Current guidelines recommended using FEV1 to evaluate limitation of airway in asthmatic patients (1). However, air trapping can happen in asthma patients with normal FEV1 (82) and this trapping was proved to have good correlation with FEF25–75 rather than with FEV1 (83). Therefore, correlation between FeNO and FEF25–75 was recently studied in subjects without obstruction determined by FEV1/FVC (74). In our subgroup of patients with no airway obstruction (FEV1/FVC >0.7), FeNO still showed a correlation with %FEF25–75 (r =−0.22, P<0.001); also, a significant difference was found between the two groups of normal and abnormal %FEF25–75 (31.0 vs. 20.0 ppb; P<0.001, compare FEF25–75* in Table 5). This finding is consistent with data from Malerba et al. who found that FeNO correlated with %FEF25–75 under the condition that FVC, FEV1 and FEV1/FC were all in the normal range (81). These latter authors suggested that abnormal %FEF25–75 might be considered an early marker of airflow limitation associated with eosinophilic inflammation (81).
In general, there are some conflicting evidences about the correlation between FeNO and asthma control indicators (such as ACT) or between FeNO and asthma severity indicators (such as spirometry parameters). There is not comparable study in Vietnam to compare, however, with the results in the present study, it can be concluded that these relationships exist in the Vietnamese population and this may provide some information for using FeNO in asthma management in this population.
The present study has some limitations. First, because this study was conducted in one hospital only, the results are not generalizable to other locations and/or other countries. Second, other factors that could influence FeNO levels, e.g., traffic-related pollution exposure and second-hand tobacco smoke, were not evaluated (84).
Conclusions
This study shows that FeNO is correlated with the ACT score, %FEV1 and %FEF25–75 and that there is a significant difference between subgroups categorized according to different levels of these variables. The higher the level of ACT-based asthma control, the lower the FeNO (and vice versa); also, FeNO stability increases when %FEV1, %FEF25–75 worsens.
In view of these findings, together with the fact that FeNO measurement is simple, noninvasive and easy to interpret, this parameter may well be a useful tool for asthma management in clinical practice.
Acknowledgments
The authors acknowledge Staff in Department of Respiratory Functional Exploration, University Medical Center, Ho Chi Minh City, Vietnam.
Funding: None.
Footnote
Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/jtd.2020.04.01). VNN reports grants from University of Medicine and Pharmacy at Ho Chi Minh City, Viet Nam, other from Aerocrine Company, during the conduct of the study. NHC has no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol was approved by the Institutional Review Board of the University of Medicine & Pharmacy at Ho Chi Minh City, Vietnam. All patients and authorized representatives were given a written informed consent and those who participated or their representative in this study had to sign this consent form.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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