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.