The Usefulness of FEF_25–75 in Predicting Airway Hyperresponsiveness to Mannitol

Introduction

Airway hyperresponsiveness (AHR), showing increased airway sensitivity to an inhaled airway constrictor, is a major characteristic of bronchial asthma.¹ This is important not only when diagnosing asthma, but also in monitoring the current status of an asthma patient.² Despite the usefulness of AHR testing, it is not easy to use in real-world clinics, especially in the primary care clinics in which most asthmatic patients are managed, due to the complexity of the test and clinician unfamiliarity with it.³ As a result, primary care providers need a cost-effective test that can serve as a substitute or screening test. Measuring patient lung function is very important in clinical practice because pulmonary function is regarded as a treatment outcome in asthma, and it is crucial to evaluate the current status of patients.⁴ Furthermore, because current asthma guidelines strongly recommend regular spirometry testing,⁴ many subjects with asthma or suspected asthma undergo spirometry during clinic visits. Thus, it would be useful in real practice if a surrogate biomarker of AHR could be found among the values already commonly measured during routine spirometry.

Among the various measurements collected during conventional spirometry, forced expiratory flow at 25% and 75% of the pulmonary volume (FEF_25–75) measures the average flow rates of medium-to-small airways during the forced vital capacity (FVC) segment to testing and presents the status of those airways in patients, along with the normal forced expiratory volume in 1 second (FEV₁) and FEV₁/FVC.^5,6 One study suggested that FEF_25–75 is more appropriate than FEV₁ for assessing AHR and that it can reveal small-airway impairment earlier than other tests in patients with bronchial asthma or allergic rhinitis.⁷ Another study showed that FEF_25–75 is associated with AHR in allergic patients and bronchial asthma patients with respiratory symptoms,^8,9 suggesting it could be a potential surrogate test for AHR.

The mannitol provocation test applies mannitol as an indirect stimulator to provoke AHR.^10,11 Very few data are available about the value of the spirometric indices for predicting AHR to mannitol. In this study, we compare the predictive value of those common spirometric parameters as surrogate markers of airway responsiveness to mannitol.

Methods and Materials

Study Design and Study Population

We conducted a retrospective study at a single university hospital between December 2013 and July 2014 to determine whether spirometric parameters predict AHR, consecutively enrolling 428 patients. All patients had asthma-like symptoms of dyspnea, coughing, or wheezing and underwent both spirometry and a mannitol provocation test. None of the patients in this study had any medical history of airway diseases such as asthma or chronic obstructive pulmonary disease (COPD) at the time of study enrollment. Demographic data (age, sex, height, and weight), respiratory symptoms, spirometric results, and mannitol provocation test results were collected by chart review. This study was conducted in accordance with Declaration of Helsinki. Only first authors, corresponding authors, and co-authors have access to patients’ information, and patients’ information will be discarded after the study is completed. The Institutional Review Board of Hanyang University Guri Hospital approved the study protocol and waived the need for informed consent because of the retrospective study design (IRB number 2017-04-036-002).

Spirometry and Mannitol Provocation Test

Spirometry was conducted by well-trained technicians according to the American Thoracic Society and European Respiratory Society guidelines.¹² The mannitol provocation test was carried out using Aridol™ (Pharmaxis Ltd., Sydney, Australia) according to the manufacturer’s protocol.¹³ AHR was defined as at least a 15% decrease in FEV₁ after the provocation (compared with baseline FEV₁). Patients were classified into two groups by the presence of AHR: the AHR group and the non-AHR group.

Statistical Analyses

Data were analyzed using SPSS software for Windows version 23.0 (IBM Corp., Armond, NY, USA). Continuous and categorical data are presented as the mean ± standard deviation and n (%), respectively. Differences in continuous data such as age, height, weight, and spirometric values were analyzed using the independent Student’s t-test or Mann–Whitney U-test. The chi-square test was performed to compare categorical variables such as sex and the presence of underlying diseases. The area under the receiver operating characteristic curve (AUC) was used to compare the predictive value of the spirometric parameters (percentages of the predicted values of FEV₁ [FEV₁%pred], FEF_25–75 [FEF_25–75 %pred], FEV₁/FVC, and FEF_25–75/FVC). To calculate and compare the AUC values, we used MedCalc (MedCalc Software, Ostend, Belgium) with the DeLong method. P-values less than 0.05 were considered statistically significant.

The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of FEF_25–75 %pred for AHR to mannitol were calculated using different cut-off values of FEF_25–75 %pred (50%, 60%, 70%, 80%, and 90% and an optimal cut-off value determined using the Youden index). The most suitable AUC to predict AHR using FEF_25–75 %pred was determined by plotting sensitivity versus 1–specificity using a receiver operating characteristic (ROC) curve. The best threshold of FEF_25–75 %pred for predicting AHR was determined using the Youden index as the value that maximized sensitivity while minimizing the false-positive rate.¹⁴ Subsequently, we calculated PPV and NPV using MedCalc to determine the effectiveness of FEF_25–75 %pred in predicting the results of the mannitol provocation test. To evaluate whether FEF_25–75 ≤ optimal cut-off values were associated with AHR to mannitol in the overall study population and the subgroup with normal spirometry, we performed univariable and multivariable logistic binary regression analyses. In the multivariable analysis, age, sex, BMI, and smoking status were adjusted.

Results

Baseline Characteristics of the Study Population

The baseline characteristics of the study population are shown in Table 1. Of 428 patients, 87 (20.3%) had AHR, and 341 (79.7%) did not. The mean age was 52.4 ± 18.3 years, and 183 subjects (42.8%) were male. Patients with and without AHR did not differ significantly in age, sex, height, weight, BMI, or smoking status. Spirometric values, FEV₁ %pred (p < 0.001), FVC %pred (p = 0.048), FEV₁/FVC (p=0.001), and FEF_25–75 %pred (p = 0.001), were all significantly higher in the non-AHR group than in the AHR group (Table 1). The baseline characteristics of subjects with normal spirometry are presented in Supplemental Table 1.

Table 1 The Baseline Characteristics of Overall Study Population

Final Clinical Diagnosis After Work-Up

After work-up, asthma was diagnosed by the attending physicians in 105 subjects; its prevalence was higher in the AHR group (94.3% vs 6.7%, p < 0.001) than in the non-AHR group. Among subjects with normal spirometry, the prevalence of asthma was also higher in the AHR group (70.3% vs 7.1%, p < 0.001). COPD was diagnosed in 15 subjects; the rate of COPD patients did not differ significantly between the AHR and non-AHR groups (p = 0.524).

AUC Values of Spirometric Parameters in the Overall Study Population

The ROC curves and AUC values of the spirometric parameters for predicting AHR in the overall study population are shown in Figure 1 and Table 2, respectively. The AUC value of FEF_25–75 %pred (0.772, 95% CI = 0.729–0.811) was significantly higher than those of FEV₁/FVC (AUC = 0.741, 95% CI = 0.697–0.782, p = 0.047), FEF_25–75/FVC (AUC = 0.741, 95% CI = 0.696–0.782, p = 0.046), and FEV₁ %pred (AUC = 0.666, 95% CI = 0.619–0.710, p < 0.001) (Table 2, Figure 2).

Table 2 AUC Values of Typical Spirometric Indices Obtained Based on All Patients’ Spirometry

Figure 1 ROC curves for predicting AHR to mannitol (total study population). Abbreviations: ROC, receiver operating characteristic; AHR, airway hyperresponsiveness.

Figure 2 ROC curves for predicting AHR to mannitol (subjects with normal spirometry). Abbreviations: ROC, receiver operating characteristic; AHR, airway hyperresponsiveness.

AUC Values of Spirometric Parameters in the Subgroup with Normal Spirometry

The ROC curves and AUC values of the spirometric parameters for predicting AHR in the subgroup with normal spirometry are shown in Figure 3 and Table 3, respectively. The AUC value of FEF_25–75 %pred (AUC = 0.704, 95% CI = 0.646–0.757) was higher, though not always significantly, than those of FEV₁/FVC (AUC = 0.644, 95% CI = 0.584–0.700, p = 0.047), FEF_25–75/FVC (AUC = 0.665, 95% CI = 0.606–0.720, p = 0.231), and FEV₁ %pred (AUC = 0.589, 95% CI = 0.529–0.648, p = 0.012) (Table 3, Figure 2).

Table 3 AUC Values of Typical Spirometric Indices in Patients with Normal Spirometry (FEV1 ≥ 80% and FEV1/FVC ≥ 70)

Figure 3 AUC distributions in the total study population and subjects with normal spirometry. Abbreviation: AUC, area under the curve.

Performance of Spirometric Parameters in Predicting AHR

The optimal cut-off values of FEF_25–75 %pred for predicting AHR were 81% (Supplemental Figure 1) and 87% (Supplemental Figure 2) in the overall population and the subgroup with normal spirometry, respectively. As shown in Table 4, the sensitivity, specificity, PPV, and NPV of FEF_25–75%pred <81% for predicting AHR in the overall study population were 77.0% (95% CI = 66.8–85.4%), 63.9% (95% CI = 58.6–69.0), 35.3%, and 91.6%, respectively (Table 4, Supplementary Figure 1). The sensitivity, specificity, PPV, and NPV of FEF_25–75 %pred <87% for predicting AHR in the subgroup with normal spirometry were 70.0% (95% CI = 53.5–83.4%), 66.8 (95% CI = 60.7–72.5%), 24.3%, and 93.6%, respectively (Table 4). The sensitivity, specificity, PPV, and NPV calculated using other cut-off values for FEF_25–75 %pred are also provided in Table 4.

Table 4 Criterion of FEF25–75 for Predicting AHR to Mannitol

As shown in Table 5, FEF_25–75 %pred <81% and FEF_25–75 %pred <87% were associated with AHR in the overall study population (unadjusted odds ratio [OR] = 5.93, 95% CI = 3.43–10.25; adjusted OR = 9.57, 95% CI = 4.88–18.74) and in the subgroup with normal spirometry (unadjusted OR = 4.69, 95% CI = 2.27–9.67; adjusted OR = 6.86, 95% CI = 2.80–16.78), respectively.

Table 5 Unadjusted or Adjusted or of FEF25–75 ≤Optimal Cut-Off Values for AHR to Mannitol

Discussion

In this study, we investigated the diagnostic value of FEF_25–75 %pred in predicting AHR during the mannitol provocation test. Our results show that FEF_25–75 %pred had a significantly higher AUC value than the other spirometric parameters we evaluated. FEF_25–75 %pred values with a cut-off of 81% (for the overall population) and 87% (for those with normal spirometry) performed relatively well in terms of sensitivity and NPV for predicting AHR in the mannitol provocation test.

AHR is an abnormal bronchial response to bronchoconstrictor stimuli and one of the typical features of bronchial asthma.^1,15 To confirm AHR, direct and indirect provocation tests¹⁶ are used, both of which have limited clinical practicality due to their complexity.^3,17 Thus, an easy-to-use biomarker that can predict AHR is needed for real practice in primary clinics.

From that perspective, FEF_25–75 has the advantages of being routinely reported during simple spirometry and being easily assessable in primary clinics. FEF_25–75 is more sensitive to the presence of small-airway diseases than FEV₁.^5,6,18 An asthma patient with a normal FEV₁ might show a decreased FEF_25–75 level by the time of the test.¹⁹ Asthma patients in primary care clinics can show mild respiratory symptoms and normal ranges of airflow limitation, allowing earlier diagnosis and under- or late diagnosis,²⁰ respectively. Several previous attempts have been made to assess AHR using FEF_25–75.^21,22 In a study by Rao et al.²¹ FEF_25–75 was used to identify a positive bronchodilator response in asthmatic patients, and it was able to predict the severity and acute exacerbation of asthma. Another study found that an abnormal FEF_25–75 level was associated with AHR in patients with asthma-like symptoms and normal FEV_1.²² However, those previous studies did not determine an ideal cut-off value for FEF_25–75. The major advantage of our study is that we calculated cut-off values of FEF_25–75 and evaluated their performance in predicting AHR to mannitol provocation. We further showed that it can be applied not only to subjects with abnormal lung function, but also to those with normal spirometry values.

The clinical relevance of our study is reflected in the relatively good sensitivity and high NPV of FEF_25–75 %pred for predicting AHR. The relatively good sensitivity of FEF_25–75 %pred indicates that it might be used as a sensitive indicator to screen for AHR in patients with asthma-like respiratory symptoms in primary clinics, even when they have normal lung function. This measure can help in diagnosing asthma or deciding whether to transfer patients to secondary or tertiary hospitals for AHR testing. Notably, the NPV of FEF_25–75 %pred is greater than 90%, which indicates that an FEF_25–75 > 81% can be used to exclude the presence of AHR in patients with respiratory symptoms. However, considering the limitations of our retrospective study, well-designed prospective studies are needed.

Our study has several limitations. First, this was a retrospective study performed in a single referral hospital. Second, although we provide the useful information that FEF_25–75 predicts AHR better than other pulmonary measurements (FEF_25–75/FVC, FEV₁ %pred, and FEV₁/FVC), we could not compare FEF_25–75 with other measurements that reflect small-airway diseases (eg, V₅₀ or V₂₅) because we did not measure those values during spirometry. Additionally, our study did not compare the performance of FEF_25–75 %pred with tests such as fractional exhaled nitric oxide or blood eosinophil count. However, those tests are not commonly performed in primary clinics, putting those comparisons beyond the scope of our study. Lastly, we did not evaluate the association between treatment (eg, medication), airway reversibility, and subjective symptoms in patients presenting asthma-like symptoms. Because our study was retrospective, we could not evaluate treatment outcome measurements (eg, asthma control test for asthma, modified Medical Research Council scale for dyspnea, or visual analogue scale for cough). In general, the objective assessment of treatment response in respiratory diseases is very limited. Nonetheless, because we did not evaluate the clinical implications of our results in terms of treatment outcomes, we accept this as a limitation of our study. A well-designed prospective study for this issue is needed.

Conclusion

We found that FEF_25–75 %pred had a significantly higher AUC value than other spirometric parameters for predicting AHR in the mannitol provocation test. With a cut-off of 81%, the FEF_25–75 %pred showed good sensitivity and NPV in predicting AHR in the mannitol provocation test.