The Forced Expiratory Volume in 1 Second Quotient (FEV1Q) offers a novel and straightforward spirometric approach to predict lung function decline and all-cause mortality in both healthy and diseased populations.1–5 FEV1Q is calculated by dividing FEV1 by sex-specific baseline thresholds: 0.4L for women and 0.5L for men. FEV1Q decreases by one unit every 18 years, with an accelerated decline observed in smokers and elderly individuals.1–4 However, thresholds for clinically significant changes in FEV1Q remain undefined. Lower FEV1Q values have been linked to increased mortality risk1 and have shown predictive power for hospitalization and functional status in chronic obstructive pulmonary disease (COPD) and healthy individuals.6–8 Nevertheless, its relationship with asthma-specific outcomes has not been explored.

This study primarily investigates correlations between FEV1Q and demographic, clinical, and inflammatory characteristics in asthma patients. Secondary objectives include assessing the predictive value and diagnostic accuracy of FEV1Q for asthma severity, control, and exacerbations, as well as comparing FEV1Q to FEV1% predicted (FEV1%) and FEV1z-scores.

The MEGA cohort is a multicenter, real-life cohort of asthma patients with varying severity levels. A retrospective review identified 445 patients with complete lung function data. Asthma was diagnosed following GINA guidelines as our previous MEGA studies.9,10 Patient demographics, asthma severity (per GINA guidelines), control (Asthma Control Test [ACT]), exacerbation frequency, lung function, and biomarker levels were analyzed. Lung function was categorized into quartiles for three metrics: FEV1Q, FEV1%, and FEV1z-scores. Receiver-operating characteristic (ROC) curves were used to evaluate the predictive capability of these metrics for asthma severity and control. Adjustments were made for age, sex, body mass index (BMI), and smoking status. Diagnostic accuracy was assessed through spirometric evidence of airway obstruction (defined by FEV1/FVC ratio≤70% and FEV1/FVC z-score≤−1.64), bronchial hyperresponsiveness (assessed by a methacholine challenge with a PC20<4mg/dL), poor asthma control (an ACT score≤19), and exacerbation history in the predicting year.

Quantitative variables were summarized using means and standard deviations, while qualitative variables were reported as absolute and relative frequencies. Correlations were analyzed using Pearson's or Spearman's methods. The area under the curve (AUC) with a 95% confidence interval (CI) was calculated, and thresholds were determined to maximize the Youden index. Sensitivity and specificity values for the thresholds were also calculated. Odds ratios were derived using logistic regression models, adjusted for confounders (severe asthma, last year exacerbation or severe exacerbation, Emergency-room (ER) visit, hospital admission and control). Statistical analyses were performed with GraphPad Instat 6 and R software. The significance level was set at 0.05.

The mean patient age was 48.5 years, with 66.2% being female. Lung function patterns indicated normal function in 56.8%, obstruction in 23.6%, and air trapping in 19.5% that corresponded to a mean (standard deviation) FEV1Q value of 6.63 (1.5), 4.52 (1.58) and 5.86 (2.13), respectively. Severe asthma was diagnosed in 37.7%, moderate in 33.1%, mild in 17.7%, and intermittent in 4.9%. Demographic and clinical characteristics from our patients were previously published.9,10

Results showed significant but weak correlations between FEV1Q and all measured demographic and clinical characteristics (r values between −0.35 and 0.35), except for a moderate correlation with age (r=−0.53, p<0.001). No significant correlations were found between FEV1Q and inflammatory biomarkers (Table 1). Lower FEV1Q values, represented by the first quartile, were significantly associated with increased risks of severe asthma, exacerbations, emergency room visits, hospital admissions, and poor asthma control. Multivariate logistic regression confirmed that these significant associations were independent of age, sex, BMI, and smoking status (Table 2). Moreover, the odds ratios for the first quartile of FEV1Q were higher to those for the same quartile of FEV1% and the FEV1z-score across all outcomes. This finding indicates that lower FEV1Q values were associated with a greater risk of all previously mentioned outcomes than lower values of FEV1% and FEV1z-score.

The diagnostic accuracy of FEV1Q for asthma control and exacerbations was modest, with AUC values of 0.67 and 0.69, respectively. Optimal thresholds yielded sensitivities of 60% and 59%, and specificities of 70% and 100%, for asthma control and exacerbations, respectively with FEV1Q cut-off values of <5.23 for asthma control and <5.60 for exacerbations. The AUC values for bronchial hyperresponsiveness (0.63, 95% CI: 0.53–0.72) and airway obstruction (FEV1/FVC ratio: 0.49, 95% CI: 0.44–0.54; FEV1/FVC z-score: 0.60, 95% CI: 0.55–0.65) were also assessed with similar results. See Table 1S and Fig. 1 Supplement.

This study supports that FEV1Q is a predictor of asthma severity, exacerbations, hospital admissions, and poor control even more than FEV1% and FEV1z-score, in line with COPD studies6–8 and healthy-aged subjects,11 independently of patient's demographic characteristics. This finding can be explained by the fact that FEV1Q standardizes lung function using the relevant sex-specific lower limit, providing a measure of the remaining FEV1 capacity for the subject, in contrast to other assessments as FEV1% and FEV1z-score that focus on the lung function that the individual may have already lost based on the deviation of an individual's measurements from a predicted and determined value (2). Nevertheless, while FEV1Q outperforms FEV1% and FEV1z-score for most outcomes in this study, its AUC (0.67–0.69) is modest and the undefined cut-offs limit its diagnostic accuracy.

Up to now, FEV1Q predictive involvement has been evaluated in different diseases3,5 but not in asthma. In the Hegendörfer et al. study,8 just 14% of the population had respiratory diseases such as asthma or COPD. However, since both diseases were evaluated together, the ability to generalize the findings to each disease individually was limited. Huang et al.7 evaluated FEV1Q's role in COPD. They demonstrated that this parameter predicted severe COPD exacerbations, whereas in our study, FEV1Q was a significant predictor of exacerbations but not specifically of the severe ones (p>0.05). Differences in the clinical characteristics and lung function measurements between asthma and COPD can account for the discrepancies. These findings emphasize the value of assessing the influence of this parameter in each disease and for each outcome.

As described in some studies in asthma with FEV1 predicted,9 a correlation between inflammatory biomarkers and lung function tests, such as FEV1Q, is not always found.

We analyzed patient's data retrospectively which could be one study limitation. Furthermore, as a methacholine challenge was an inclusion criterion for MEGA, not all patients from the MEGA cohort have data compiled about lung function which is required for our study and therefore, our study population is lower than the total MEGA cohort which can be another study limitation. However, with our criteria selection, we ensured the correct evaluation of the selected parameters even though the results could not represent all the studied patients.

In conclusion, this is the first study to evaluate FEV1Q's role in predicting asthma-specific outcomes. Despite its limitations, FEV1Q outperformed traditional lung function metrics in predicting asthma severity, exacerbations, and hospitalizations. Future research is needed to establish clear thresholds and validate these findings across diverse populations.