Correlation of fraction of exhaled nitric oxide with asthma control test and asthma severity in diagnosed cases of asthma

Abstract

Background

Fraction of NO in exhaled air (FENO) has emerged as a simple, non-invasive, sensitive marker of airway inflammation in asthma diagnosis and management. Correlation studies of FENO with clinical grades of asthma and symptom burden are sparse, more so in Indian population. Hence, this study was carried out in Indian subjects to evaluate FENO correlation with asthma severity.

Methods

The study was performed on 52 proven cases of asthma in the age group of 17–90 years in period of December 2016 to May 2018. All the subjects had assessment in the form of Asthma Control Test (ACT)questionnaire, FENO parts per billion measurement with a portable NO analyzer (NIOX MINO Airway Inflammation Monitor; Aerocrine) and spirometry. Statistical analysis was presented in the form of percentage (%) and mean.

Results

Of a total of 52 asthma cases, 27 (51.9%) were male cases while 25 (48.1%) were female cases. Study population ranged from 17 to 82 years. Subjects categorized into 03 categories of asthma severity based on their treatment step. ACT score of ranged between 11 and 25 with a mean value of 20.27 and standard deviation of 3.73. No significant correlation was found between FENO and ACT (r) = −0.177, P-value = 0.210 (>0.05). Significant correlation between FENO and different grades of asthma severity was found with p-value 0.032 (<0.05).

Conclusion

Asthma severity as assessed by the step of treatment is correlated well with FENO value in an asthmatic individual to maintain the controlled asthma status. FENO and ACT were found to have no correlation.

Introduction

Asthma is a disease of variable obstruction of airflow which occurs both spontaneously as well as while the patient is on treatment. GINA 2020 defines asthma as “a heterogeneous disease, usually characterized by chronic airway inflammation. It is defined by the history of respiratory symptoms such as wheeze, shortness of breath, chest tightness and cough that vary over time and in intensity, together with variable expiratory airflow limitation.” Asthma patients have airway inflammation by which they are rendered more responsive to a number of triggers and hence excessive narrowing and reduction in airflow with wheezing as compared to non-asthmatic individuals. Worldwide asthma prevalence is reported to be around 1–18% in different countries.¹ Asthma is considered as airflow obstruction which is reversible and inflammation with airway hyper-responsiveness (AHR). This airway inflammation has been implicated in playing a key role in disease pathophysiology in various studies.^{2, 3, 4} Breathlessness, cough, chest tightness, and wheezing are typical symptoms of asthma in clinical history of subjects. The diagnosis of asthma requires identification of characteristic symptoms as well as demonstration of variable airflow limitation. Presently among the diagnostic modalities available for objective assessment of bronchial asthma in clinical practice are spirometry and other pulmonary function tests (PFTs), reversibility assessment with bronchodilators and bronchial challenge tests. However these different tests measure different aspects of disease pathology. None, among these conventional methods, is a direct measure of the airway inflammation and useful in assessing the treatment response of such inflammation. Fraction of NO in exhaled air (FENO) emerging as a potentially important clinical tool in asthma diagnosis. Measurement of FENO is a simple, safe, easy to perform, quantitative, and non-invasive method that provides an additional tool to other methods of assessing airways disease, including asthma. Role of FENO in asthma has been reviewed in various studies in the context of diagnosis, prediction of steroid responsiveness and prediction of AHR.^{5, 6, 7, 8, 9, 10} FENO can be easily measured through a hand held apparatus with a simple expiratory maneuver. Another important tool which is a patient based approach in self-assessment of disease severity and its control is asthma control test (ACT).¹¹ In current asthma management, GINA 2018 identifies grades of severity of asthma retrospectively based on the treatment options required to keep asthma under control. It grades severity into mild, moderate, and severe on the basis of stepwise treatment approach. We attempted to derive some correlation, if it exists, among FENO, GINA grades of severity of asthma, and ACT in our outpatient, as well as inpatients who were objectively diagnosed cases of asthma.

Materials and methods

The study was conducted as an observational study in a tertiary care center over a period of 1 ½ year. Fifty-two patients in the age group of 17–90 years, who were diagnosed cases of asthma on basis of symptoms and spirometry evidence of reversible airway obstruction were studied. Inclusion criteria were defined as those who were diagnosed case of asthma as per GINA guidelines. Those who had acute exacerbation at the time of enrollment, who could not perform all three measurement of spirometry, FENO, and ACT during the same visit, smokers, oral corticosteroid dependent, concurrent infection, patients with cystic fibrosis and other chronic lung diseases were excluded from study. Informed consent of all participants was obtained. The sample size was calculated on the basis of previous international study and prevalence studies to test the hypothesis with 5% level of significance and 80% power:

Ho: ρ = 0 against H1: ρ≠0where ρ is correlation coefficient between 02 variable of interest.

Correlation between variables	Correlation coefficient	Sample size
FeNO and ACT score	0.69	14
FeNO and GINA grade of severity	0.59	20

The maximum sample size worked out to be 20; however 52 cases of asthma were studied. Fifty-two adult patients (between age 17 years and 90 years) of bronchial asthma in outpatient and inpatient department in a tertiary care hospital in western Maharashtra were selected. All of these patients were diagnosed cases of bronchial asthma on the basis of their clinical features and spirometry.

Baseline history and clinical examination findings were recorded. All the subjects had an assessment in the form of ACT questionnaire which is a subject-based, five question questionnaire that can be rated by the patient, and total score is used to identify insufficiently controlled asthma cases. Before undergoing spirometry, FENO parts per billion (ppb) was measured with a portable NO analyzer (NIOX MINO Airway Inflammation Monitor; Aerocrine) using single breath exhalation technique. The measurement was done in ppb unit. In accordance with ATS recommendation, the normal values of exhaled NO were set as 5–25 ppb for healthy adults. Before the measurement of FENO, each patient was asked to refrain from smoking, eating, and drinking coffee or using any bronchodilators for at least 6 h. All patients underwent pulmonary function testing for functional evaluation. Spirometry was performed based on the techniques mentioned in the spirometry manual (chest research foundation) with special reference to American Thoracic society of Standardization of spirometry. The parameters measured in spirometry were forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC ratio. In the same visit, subjects also underwent absolute eosinophil count (AEC) test.

Patients were overall assessed and their grade of asthma severity as well asthma control was determined as per GINA guideline 2018. Patients with an ACT score more 20–25 were considered to be well controlled, 16–19 as not well controlled. The patients who have ACT scores ≤15 were categorized as poorly controlled asthma. Another classification was on the basis of treatment required as per the stepwise approach of GINA guidelines into mild, moderate and severe asthma. Data were entered in Excel sheet, and Data analysis was carried out by using SPSS (Statistical package for social sciences), Version 20:0 software. Data are presented in the form of graphs and tables. Qualitative data variables are expressed by using frequency and percentage (%). Quantitative data variables are expressed by using mean, SD, and so on. Pearson's correlation coefficient has been used to find the correlation between FENO and different variables e. g. FEV1 (%), AEC, and so on.

For the comparison between spirometry parameters, FENO and AEC with GINA severity and control grade we have used Kruskal-Wallis Test (non-parametric test). p-value < 0.05 was considered as significant.

The study was scrutinized by institutional ethical committee and was approved.

Results

A total number of 52 asthma cases were included in the study. Of these, 27 (51.9%) were male cases, whereas 25 (48.1%) were female cases. The population under study ranged from 17 years to 82 years with a mean age of 39.10 years and standard deviation (SD) of 13.73. Age wise distribution of patients is given in Table 1. Among the 52 patients studied, 31 patients (59.6%) revealed a family history of bronchial asthma, whereas 21 patients (40.4%) had no such history in their family.

Table 1.

Age wise distribution of cases.

Age group	Number of patients	Percentage (%)
≤20	3	5.8
21–30	12	23.1
31–40	18	34.6
41–50	8	15.4
51–60	7	13.5
>60	4	7.7
Total	52	100.0

Subjects were also categorized into 3 categories of asthma severity based on their treatment step as outlined in GINA 2018. Nineteen (36.5%) patients fell into mild asthma severity receiving either step-1 or step-2 treatment. Majority of patients, 27 (51.9%) out of total 52 cases, were found to be in category of moderate severity asthma and were receiving step-3 treatment. Six (11.5%) patients fell into severe asthma with step-4 or step-5 treatment regime. ACT score of 52 patients ranged between 11 and 25 with a mean value of 20.27 and SD of 3.73. Maximum number of cases, 33 (63.5%), were in well-controlled group, whereas 12 (23.1%) were in not well-controlled group. Only 7 (13.5%) cases fell in very poorly controlled group. In FENO distribution as per decade wise age group, highest mean FENO values were seen in age group of 51–60 years. By using ANOVA test, p-value was 0.316 (>0.05). No significant difference was found between mean FENO in relation to age (years). FENO distribution as per age is shown in Table 2.

Table 2.

FENO distribution in respect to age (years).

Age group	Number of patients	FeNO		p-value
		Mean	SD
≤20	3	61.3	75.2	0.316
21–30	12	57.9	37.2
31–40	18	35.0	29.8
41–50	8	50.5	35.7
51–60	7	70.9	51.4
>60	4	36.0	21.8

Correlation between FENO and ACT was derived using Pearson's correlation coefficient. FENO and ACT score had a correlation coefficient (r) = −0.177 and P-value = 0.210 (>0.05). Hence, no significant correlation was found between FENO and ACT. Fig. 1 depicts the correlation of FENO and ACT in our study.

Fig. 1.

Correlation between FENO Vs ACT.

Correlation between FENO and different grades of asthma severity based on the treatment steps were derived by using Kruskal-Wallis test. Mean values of FENO in respect to each severity grade. Mean FENO value in mild severity cases was 30.11 ppb with SD of 21.94. While mean FENO value in moderate severity was 61.44 with SD of 42.58. Among the 6 cases of severe asthma, the mean value of FENO 53.67 (SD = 44.53). The p-value for this correlation was 0.032 (<0.05); therefore we found a significant difference between mean FENO with respect to GINA severity grade. Correlation of Severity grade and FENO is depicted in Fig. 2. FENO and AEC were detected to be having a positive correlation with a correlation coefficient (r) = 0.341; P-value of 0.013 (Fig. 3).

Fig. 2.

FENO and GINA severity grade of asthma.

Fig. 3.

Correlation between FENO Vs AEC. AEC, absolute eosinophil count.

Discussion

The current bronchial asthma diagnosis depends on characteristic history of asthmatic symptoms with demonstrable evidence of variable airflow limitation by various methods. Although PFT reflects the airway obstruction and airflow limitation, it has been increasingly recognized that it does not reflect a true measure of airway inflammation. FENO is a non-invasive marker which is an indirect inflammation marker with simple use technique and a sensitive parameter. Thus FENO and FEV1 assess different parts of physiology of asthma.¹² Another new tool in evaluation of asthma is ACT which allows patient's self-assessment regarding their asthma control. In our study, we aimed to derive a correlation, if any exists, between ACT score and FENO in our patient with asthma who were diagnosed cases of asthma. We also attempted to assess if the FENO values have any correlation with the disease severity in our patients who were graded in severity according to GINA.

A total of 52 patients were observed in the study. Their age ranged from 17 years to 82 years, with a mean of 39.10 and SD of 13.73 years. Of 52 patients, 27 (51.9%) were men, whereas 25 (48.1%) were women. In our study, we observed two peaks of FENO values with respect to age groups. Age group of <20 years had a mean FENO value of 61.3 ppb. Thereafter a decline in mean FENO value was observed over next few decades. Then highest mean FENO value was seen in age group of 51–60 years with 70.9 ppb mean value with SD of 51.4. However, the difference between mean FENO with respect to age was not found to be statistically significant (p value > 0.05). Tsang et al have also found no significant correlation between age. Similar to our study, Olin et al also reported FENO to be increasing in the 35–65 years age range, whereas in contrast to this, Travers et al reported that there occurs no significant relationship in similar age range.^{13, 14, 15} Subjects were divided into 3 grades of asthma severity as per GINA guideline based on the treatment received by the patients. Nineteen (36.5%) patients fell into mild asthma severity receiving either step-1 or step-2 treatment e.g. low dose inhaled corticosteroids (ICSs), leukotriene receptor antagonist (LTRA), low dose theophylline with as needed short acting β2 agonists. Twenty seven (51.9%) patients were categorized as moderate severity of asthma receiving step-3 treatment in the form of low dose ICS + long acting β2 agonist (LABA) with other controller options e.g. med/high dose ICS, low dose ICS + LTRA or theophylline. Six (11.5%) patients fell into severe asthma with step-4 or step-5 treatment regime e.g. med/high dose ICS + LABA with other add on therapies in the form of low dose oral corticosteroids, tiotropium, anti IgE, or Anti IL-5. A significant difference of mean FENO with respect to different severity grades of asthma was found in our study with a p-value of 0.032(<0.05). Mild asthma has a mean FENO level of 30.11 ppb with an SD of 21.94. Mean value of FENO in moderate asthma was 61.44 ppb (SD = 42.58), whereas severe cases had a mean FENO value of 53.67 ppb (SD = 44.53). This correlation finding in our study is in agreement with the study carried out by Senna et al¹⁶ where they found a good correlation between FENO and GINA grade of severity (r = 0.59, P = 0.002). Buzoianu et al conducted their study among children, an age group different from our study. They found that among children FENO value did not correlate well with asthma severity based on GINA 2008 guideline criteria (p = 0.278) because GINA 2008 classification of asthma was based on accounting the day and night time symptoms, the exacerbations, limitation of daily activity, reliever medication use, and the FEV1 and PEF values. When Buzoianu et al¹⁷ used the asthma severity by taking account of the treatment response as per GINA 2014 guideline, which has been described in present GINA 2018 guidelines and used in our study as well, they observed a statistically significant correlation (p = 0.0468) between asthma severity and FENO values. In other words, an increased FENO value is related to an increased asthma severity.

Asthma control test (ACT) questionnaire was used as a separate tool for self-assessment of asthma control as perceived by the patient. Among 52 study subjects, ACT score ranged from 11 to 25 with a mean value of 20.27 and an SD of 3.73. Of these 52 subjects, 33 (63.5%) cases were falling in well controlled category based on ACT score of 20–25. Twelve (23.1%) subjects were in not well controlled group with score ranging between 16 and 19, whereas 7 (13.5%) cases were in very poorly controlled group with ACT score of 5–15. There was no significant correlation found between FENO with ACT score in our study (correlation coefficient r of −0.177) with a P-value of 0.210 (>0.05). Senna et al found a good correlation in ACT score and FENO (r = 0.7, P = 0.001). However, Roh et al could not derive a correlation between FENO and ACT (P = 0.45), which was similar to our findings. Study carried out by Bora et al also observed that the there was no correlation between parameters of airway inflammation and ACT scores. In this study, the mean values of ACT scores at baseline were not found to be having any correlation with FENO levels (r = 0.111, p = 0.318). Shirai et al also found a low correlation between FENO values and ACT scores (r = 0.310). These discrepancies in FENO and ACT correlation may be explained by the fact that symptom perception maybe be variable at an individual level. Another explanation can be given by ICSs effect because a decrease in FENO while parallel improvement in clinical parameters during ICSs use has been shown in many studies. In addition, population diversity and the sample size could be causing discrepancy.^{18, 19, 20, 21, 22}

Conclusion

The asthma severity as assessed by the steps of treatment is necessary to maintain the controlled asthma status. FENO value in an asthmatic individual is correlated with asthma severity assessed as per the step of treatment necessary to maintain the controlled asthma status. Increased FENO value in a patient predicts a severe asthma form, indicating that it needs a superior treatment step to achieve the optimum control of inflammation of airways and consequently controlled asthma status. However, discrepancies do exist in variable symptom perception at an individual level and also in the extent of airway inflammation, which is alternatively explained by ICSs effect and population diversity. FENO has come up as an easy to perform, sensitive, reproducible, and non-invasive biomarker in airway inflammation assessment. The symptom management of asthma and the treatment being used has to depend on the type on bronchial inflammation and quantitative assessment of inflammation even in the absence of severe symptoms to prevent worsening of asthma and precipitation of exacerbations. An integrated approach is required to diagnose and follow-up asthma cases that includes clinical evaluation, assessment of functional status and inclusion of biomarkers of inflammation of airways. FENO is a promising candidate for assessing severity of asthma, follow-up and changes in step-wise management of asthma.

Disclosure of competing interest

The authors have none to declare.