Discussion
Early diagnosis of asthma is very important, not only to relieve the patient’s symptoms, but also to prevent the development of chronic inflammation and airway remodeling. However, early diagnosis is difficult because patients need to satisfy the 2 criteria of variable symptoms and air-flow limitation. This is especially true for mild asthma, which is often undiagnosed because FEV1 is normal and the bronchodilation test has a high false-negative rate. Our data indicating that small-airway dysfunction is present in asthmatic patients with FEV1 ≥ 80% predicted may help to provide an early diagnosis in patients with mild asthma. Measurements of small-airway function, including FEF50% and FEF25%-75%, combined with measures of airway inflammation (FENO or EOS counts) provided the best prediction of positive BHR diagnosis in subjects who had both typical asthma-like symptoms and FEV1 ≥ 80% predicted.
Type II airway inflammation increases both EOS counts and FENO, which are used in asthma diagnosis and the therapeutic response’s evaluation of anti-asthma.24,25 Our data also showed that the levels of both EOS and FENO were higher in the BHR-positive group. Previous studies in guinea pigs have shown that NO may itself contribute to BHR, by increasing plasma exudation via its vasodilator effect and by its transformation into peroxynitrite, which induces BHR.26 Furthermore, in our study, a weak correlation between FENO and PD20 in patients with positive BHR was observed (r = -0.266, P = .0005), suggesting that FENO is valuable in predicting BHR, which was also noted by Jatakanon et al.27
Currently, FENO is particularly helpful in ruling out asthma. Its cut-off value for predicting asthma ranged from 10.5 to 64 ppb in different studies.28FENO < 30 ppb has a high specificity (87%) and NPV (93%) for excluding asthma from untreated nonsmoking adults with chronic cough.29 Schleich et al showed that FENO > 34 ppb had a low predictive value (AUC = 0.62) for predicting BHR in patients with suspected asthma.30Schneider et al illustrated that, in their sample as a whole, asthma could be ruled in at FENO > 71 ppb (PPV, 80%) and ruled out at FENO ≤ 9 ppb (NPV, 82%), with an AUC of 0.656.31 Importantly, when patients with neutrophilic inflammation were omitted, the AUC was 0.745 and asthma could be ruled in at FENO > 31 ppb (PPV, 82%) and ruled out at FENO ≤ 12 ppb (NPV, 81%).31 Our present study showed that FENO > 41 ppb has a sensitivity of 65.29%, specificity of 78.16%, PPV of 49.33%, and NPV of 87.37%. The AUC for predicting BHR was 0.748, regardless of the inflammatory type, which is similar to the AUC from Schneider et al when patients with neutrophilic inflammation were omitted.
In our current study, patients positive for BHR, but with FEV1 in the normal range, had abnormal values of small-airway function variables, obtained with spirometry and IOS. Two-thirds of asthmatic patients with FEV1 ≥ 80% predicted had small-airway dysfunction, and patients with small-airway dysfunction exhibit a greater likelihood of BHR. FEF50%, FEF75%, and FEF25%-75% were weakly correlated with PD20. This might indicate that small-airway dysfunction could be a forerunner of decreased FEV1 and could be used to detect early disease.
We found the 2 most valuable spirometric variables for predicting BHR were FEF25%-75% (AUC = 0.763) and FEF50% (AUC = 0.762) (Table 3). The 2 FEFs were strongly correlated and had equivalent value in predicting BHR. However, because both produced AUC < 0.80, using them singly would be insufficient for predicting BHR in patients with suspected asthma. Thus, we combined the FEFs with FENO or EOS counts to enhance their predictive value for BHR diagnosis. The AUCs of FEFs combined with FENO were significantly higher than those of the univariate AUCs. This suggests that FEFs combined with FENO (2 noninvasive and convenient measurements) can improve the prediction of BHR diagnosis. The cut-off values had certain difference among different studies possibly because we included patients with mild asthma-like symptoms and normal FEV1, who had higher FEF levels than those with more severe symptoms.4, 32-34
One main limitation of FEF is that it depends on FVC and lung capacity.35, 36 In contrast to FEV1, FEF25%-75% is not normalized to FVC when assessing air-flow obstruction. Therefore, FEF25%-75% could be artificially low in individuals with restrictive lung or chest bellows disease (e.g., obesity) and could therefore overdiagnose asthma. In our study, mean BMI and FVC were in the normal range (23.37 ± 3.477 kg/m2 and 101.5% ± 12%, respectively), and neither variable differed between groups.36,37 Most importantly, all patients in the study had undergone HRCT, therefore guaranteeing that restrictive lung diseases or obesity were excluded and minimizing the possibility of overdiagnosis of asthma in our patients. Furthermore, IOS is a noninvasive alternate test that is not affected by expiratory flow and is more physiologically relevant than spirometry.38,39 We evaluated the ability of IOS measurement to assess small-airway function and to predict BHR. In our study, R5-R20 alone exhibited poor predictive value for BHR diagnosis, and the AUC was still lower than 0.80 when we combined R5-R20 and FENO. This finding suggests that when combined with FENO, FEFs provide better value than R5-R20 for predicting BHR even though they are less physiologically relevant.
Chest tightness is a symptom of asthma that is more likely reflects muscle tightness or physical difficulty with moving air that is sensed through proprioception and not through pain pathways.40-42 In asthmatic patients with normal FEV1 in our study, the most frequent complaints were chest tightness and cough rather than wheeze or dyspnea. Relevant clinical subtypes of asthma, “chest tightness variant asthma”43 and “chest pain variant asthma”40, 44 have been described in the medical literature. Asthmatic patients who only complain of chest tightness are easily misdiagnosed in clinical practice. We found that decreases of FEV1, FEV1/FVC, FEF25%, FEF50%, FEF75%, and FEF25%-75% were more serious in subjects with than without chest tightness, indicating that small-airway dysfunction may be involved in the mechanism of chest tightness. The joint model of small-airway function variables (FEF50%, FEF75%, or FEF25%-75%) and FENO gave particularly high predictive values for BHR in subjects with chest tightness (all of the AUCs ≥ 0.880). In addition, the joint model of EOS with small-airway function variables (FEF50%, FEF75%, or FEF25%-75%) was highly predictive of BHR in subjects with chest tightness (all of the AUCs ≥ 0.815) , which it was not for the population as a whole. Since the cost of peripheral blood cells count is much cheaper than FENO, these tests may provide very economic alternatives for predicting BHR in suspected asthmatics, especially in primary hospitals. The diagnosis of asthma should be strongly considered in patients with lower FEFs, high FENO or high EOS counts, and the symptom of chest tightness.
The progressive statistical design of this study consisted of several steps. First, the possible influencing variables were found from a Mann-Whitney test. Then, the correlation between the relevant variables and PD20 was determined with Spearman analysis. Through the analysis of AUC, the predictive value of those variables was further verified. The repeatability of our data calculation was shown by an 80/20 split-sample cross- validation. The AUCs in the validation sample were close to those in the whole model.
To overcome some limitations of our current study, larger-scale and multicenter prospective clinical trials should be performed to ensure the integrity of the inspection results.
In conclusion, asthmatic patients suffer from small-airway dysfunction, even though their FEV1 is within the normal range. Patients with small-airway dysfunction exhibit an increased likelihood of having BHR. In order to improve the diagnosis rate of mild asthma and relieve patients’ symptoms as early as possible, we combined 2 simple and noninvasive methods—small-airway function tests and FENO to improve the diagnosis rate of mild asthma. The likelihood of BHR strongly increased with FEF25%-75%<84.4%, FEF50% <76.8%, and FENO >41 ppb. FEV25%-75% and FEF50%, derived from spirometry, could be combined with FENO to diagnose asthma in patients with normal FEV1 and symptoms suggestive of asthma, allowing the patient to forego MCH challenge testing for the diagnosis. FEF25%-75%, or FEF50% combined with EOS can also be a very economic method to predict BHR in suspected asthma subjects with chest tightness.