Impact of bronchodilator responsiveness on lung age in patients with respiratory diseases and/or symptoms: implications for clinical practice from a cross-sectional study

Abstract

Background

Lung age (LA) that expresses lung function as a form of biological age and facilitates clinical interpretation. Bronchodilator responsiveness (BDR) is important for assessing airway reversibility, but its influence on LA remains unclear. This study aimed to evaluate the impact of BDR on LA and to explore its clinical implications.

Methods

In this cross-sectional study, we analyzed participants with respiratory disease and/or symptoms who underwent spirometry and BDR testing between January 2023 and December 2024. LA was calculated using a reference equation established from healthy, non-smoking Chinese adults. Participants were categorized into three groups: normal [the difference between lung age and age (DeltaLA) ≤0], normally high [DeltaLA >0 and ≤ upper limit of normal for DeltaLA (DeltaLAULN)], and abnormally high (DeltaLA > DeltaLAULN). A random forest model was used to identify predictors of post-LA improvement. Nonlinear regression was employed to evaluate associations between DeltaLA and spirometric parameters. Receiver operating characteristic (ROC) analysis was performed to evaluate the ability of difference between ULN and LA (ULNLA) and spirometric measurements to predict a post-bronchodilator forced expiratory volume in one second to forced vital capacity (FEV₁/FVC) ratio <0.7.

Results

Nine thousand three hundred and sixteen participants (mean age 58.6±12.9 years; 69.7% male) were included. After bronchodilator, LA significantly improved and 34.03% of those in normally high LA improved to normal group (all P<0.001); 21.83% of participants in the abnormally high LA group had a significant BDR, compared with 3.68% and 4.02% in the normal and normally high LA groups, respectively (P<0.001). DeltaLA was correlated with FEV₁, forced expiratory flow at 50% of FVC (FEF_50%), forced expiratory flow at 75% of FVC (FEF_75%), and FVC (r=−0.80 to −0.46, all P<0.001). The ability of ULNLA to predict a post-bronchodilator FEV₁/FVC ratio <0.7 was comparable to FEV₁ (area under the curve: 0.84 vs. 0.85).

Conclusions

Pre-bronchodilator LA alone may result in misclassification, whereas post-bronchodilator LA provides a more accurate evaluation. ULNLA demonstrates predictive ability of airflow limitation is comparable to FEV1% predicted.

Highlight box.

Key findings

• Lung age (LA) is significantly influenced by bronchodilator responsiveness (BDR). Approximately one-third of individuals in “normally high” group reverted to “normally” group after bronchodilation, revealing misclassification when using pre-bronchodilator LA alone.

• The difference between lung age and age correlated negatively with spirometric indices, with correlation coefficients ranging from −0.80 to −0.46. The difference between upper limit of normal and LA (ULNLA) demonstrates diagnostic performance comparable to forced expiratory volume in one second (FEV₁)% predicted for identifying post-bronchodilator FEV₁ to forced vital capacity ratio (FEV₁/FVC ratio) <0.7.

What is known and new?

• Spirometric values may improve after bronchodilation; and using pre-bronchodilator measurements may overestimate airflow limitation. LA is a spirometry-derived parameter that helps communicate lung health and raise awareness of airway disease, yet the effect of BDR on LA remains insufficiently characterized.

• This large-scale, real-world study is the first to systematically evaluate how BDR affects LA estimation in patients with respiratory diseases and/or symptoms. We show that BDR can substantially modify LA categories and identifies a subset of individuals whose LA classification normalizes after bronchodilation. Additionally, ULNLA shows good discriminative performance for post-bronchodilator airflow limitation.

What is the implication, and what should change now?

• In the clinical application of LA (e.g., evaluating postoperative prognosis), clinicians should account for the influence of BDR when interpreting LA-based metrics. Additionally, a ULNLA value ≤−19.6 may signal post-bronchodilator airflow limitation (post-bronchodilator FEV₁/FVC ratio <0.7), in which case bronchodilator testing should be recommended.

Introduction

Pulmonary function tests (PFTs) serve as a cornerstone in the diagnosis and management of chronic respiratory diseases, providing critical insights into disease severity, treatment response and prognostic evaluation (1,2). In China, national policies have increasingly promoted the integration of PFTs into primary care, emphasizing their value in early detection and longitudinal monitoring of airway diseases (3-6). Nevertheless, the interpretation of spirometry—a fundamental component of PFTs—remains challenging for both primary care physicians and patients, limiting its broader implementation in community settings.

To bridge this gap, the concept of lung age (LA) was introduced by Morris and Temple in 1985 (7). LA is derived from spirometric parameters using reference equations (7-10). When LA exceeds a patient’s chronological age, it may reflect accelerated pulmonary aging. For example, a 45-year-old individual with a LA of 65 years is considered to have pulmonary function comparable to that of a much older adult. LA provides an intuitive metric for the public to understand their respiratory health status. Evidence suggests that communicating LA results to patients enhances their awareness of respiratory health and promotes smoking cessation (11-15). LA has also been studied as a prognostic indicator for postoperative outcomes and a tool for monitoring therapeutic efficacy (16-19).

Bronchodilator responsiveness (BDR) testing, which compares pre- and post-bronchodilator spirometric measurements, is widely used to assess the reversibility of airflow limitation. In this study, a significant BDR was defined as an increase of >10% relative to the predicted value for forced expiratory volume in one second (FEV₁) or forced vital capacity (FVC) (20). Notably, the threshold for defining significant BDR varies across guidelines and has evolved over time. Conventional LA may be calculated using pre-bronchodilator values, which may not reflect dynamic changes in lung function after bronchodilator. This approach could potentially overestimate disease severity and limit the clinical applicability of LA in patients with reversible airflow limitation. Therefore, the impact of BDR on LA warrants further investigation. In our study, we aimed to characterize the response of BDR to LA and to evaluate the clinical utility of its derived indices in BDR assessment. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-aw-2382/rc).

Methods

Study design, settings and participants

This cross-sectional observational study was conducted at the First Affiliated Hospital of Guangzhou Medical University between January 2023 and December 2024. The study protocol adhered to the principles of the Declaration of Helsinki and its subsequent amendments, and was approved by the institutional ethics committee of the First Affiliated Hospital of Guangzhou Medical University (approval No. 2020-124). Given the retrospective nature of the study, the requirement for informed consent was waived.

We enrolled patients who underwent both spirometry and BDR testing as part of their clinical evaluation. Testing was performed based on clinical indications, which primarily included suspected or diagnosed respiratory conditions such as asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease (ILD), lung tumors, or bronchiectasis. The cohort also included symptomatic individuals presenting with cough, sputum production, chest tightness, dyspnea, or wheezing who had not yet received a definitive diagnosis.

Inclusion and exclusion criteria

To minimize potential confounding from ethnic variability, the study was restricted to individuals of Chinese ethnicity. Participants were required to be between 18 and 80 years of age with height ranging from 95 to 190 cm, in accordance with established Chinese pulmonary function reference equations (21,22). Individuals with contraindications to spirometry or BDR testing were excluded (20,23).

Measurements and definitions

Spirometry and BDR testing procedures (including equipment calibration, subject preparation, maneuver technique, repeatability, and quality control) adhered to guidelines set by the European Respiratory Society (ERS) and the American Thoracic Society (ATS) (20,23,24). All procedures were conducted by full-time technicians from the hospital’s PFT center. For subjects who underwent multiple tests, only the initial report was included, and only data meeting A-level quality criteria were retained for subsequent analyses. Collected variables included sex, age, height, weight, baseline spirometric measurements, and post-bronchodilator spirometric measurements. The best-measured values from spirometry and BDR testing were used for data analysis. Predicted normal values were derived using the reference equations published by Jian et al. in 2017 and Wang et al. in 2024 (21,22).

A significant BDR was defined as an increase of >10% relative to the predicted value for FEV₁ or FVC after bronchodilator use according to the 2021 ERS/ATS technical standard (20). To assess the robustness of our findings, we performed sensitivity analyses using alternative BDR cutoffs: an increase of ≥12% and ≥200 mL from baseline in either FEV₁ or FVC according to 2005 ERS/ATS technical standard (24); an increase in FEV₁ of ≥12% and ≥200 mL from baseline, or ≥10% of predicted according to the British Thoracic Society (BTS), the National Institute for Health and Care Excellence (NICE), and the Scottish Intercollegiate Guidelines Network (SIGN) asthma joint guideline (25). To simplify the expression, BDR results based on these three definitions are referred to as 2021-BDR, 2005-BDR and 2024-BDR, respectively. Airflow limitation was defined as a post-bronchodilator (FEV₁/FVC) ratio <0.7 (26,27). Preserved ratio impaired spirometry (PRISm) was defined as FEV₁ <80% predicted with a preserved FEV₁/FVC ratio ≥0.70 (28). Obstructive spirometric pattern was defined as FEV₁/FVC <92% predicted but FVC ≥80% predicted; restrictive spirometric pattern was defined as FVC <80% predicted but FEV₁/FVC ≥92% predicted; mixed spirometric pattern was defined as both FEV₁/FVC <92% predicted and FVC <80% predicted (29).

LA was estimated using a reference equation developed by Liang et al., based on a nonlinear regression (spline method) derived from a healthy Chinese non-smoker population (9). The data for this equation were derived from a multicenter, large-sample spirometry study (22,30). The specific formulas are: male LA prediction: LA (years) = 2.25 + 0.49 × height (cm) + ns (FEV₁) + 3.47 × forced expiratory flow at 50% of forced vital capacity (FEF_50%; L/s) − 8.92 × forced expiratory flow at 75% of forced vital capacity (FEF_75%; L/s); female LA prediction: LA (years) = 28.49 + 0.36 × height (cm) + ns (FEV₁) + 4.45 × FEF_50% (L/s)− 12.52 × FEF_75% (L/s), where ns (FEV₁) represents the coefficient of the natural cubic spline of FEV₁, as detailed in the supplementary material in Liang et al.’s article (9).

The difference between LA and age (DeltaLA) was calculated as: DeltaLA (years) = LA − age. The upper limit of normal (ULN) for DeltaLA (DeltaLAULN) was calculated as: DeltaLAULN (years) = 12.243 − 0.323 × age + 1.645 × 7.037 (9). The difference between ULN for LA and LA (ULNLA) was calculated as: ULNLA (years) = ULN − LA. Participants were stratified into three groups based on their DeltaLA relative to DeltaLAULN: normal LA group (DeltaLA ≤0), normally high LA group (DeltaLA >0 and ≤ DeltaLAULN), and abnormally high LA group (DeltaLA > DeltaLAULN).

Statistical analysis

The study sample was randomly split into a training set (80%) for primary analysis and a validation set (20%) for internal validation. Nonlinear regression was used to evaluate the relationship between DeltaLA and spirometric parameters. A random forest model was used to identify predictors of post-LA improvement. Receiver operating characteristic (ROC) analysis was performed to evaluate the ability of ULNLA and spirometric measurements to predict a post-bronchodilator FEV₁/FVC ratio <0.7, with area under the curve (AUC) calculated to assess diagnostic performance.

Normally distributed continuous variables were described using means (standard deviations) and were compared using analysis of variance (ANOVA). Non-normally distributed continuous variables were expressed as medians (interquartile ranges) and were compared using the Wilcoxon rank-sum test. Categorical variables were described using frequencies (percentages) and were compared using Chi-squared test or Fisher’s exact test. A two-sided P value <0.05 was considered statistically significant. Missing data for important variables (<5% missing) were imputed using multiple imputation methods. All statistical analyses and visualizations were performed using R software (version 4.4.1).

Results

Demographic and clinical characteristics in patients with respiratory diagnoses and/or symptoms

A total of 9,316 participants (mean age 58.56 years, 69.70% male) were included in the analysis, with 7,452 assigned to the training set and 1,864 to the validation set. The two sets were well balanced in age, sex, height, smoking status, LA, DeltaLA and all spirometric parameters (all P>0.05, see Table S1). Patients with suspected or diagnosed COPD were predominantly older men, had higher smoking exposure and higher LA and DeltaLA compared to the other three groups and exhibited the most severe airflow limitation (Table 1). Baseline characteristics stratified by spirometric patterns and LA groups are provided in Tables S2,S3.

Table 1. Clinical characteristics, LA and spirometric data in patients stratified by suspected diagnosis.

Variables	COPD† (n=1,787)	Asthma† (n=883)	ILD† (n=158)	Others† (n=4,624)	P value
Sex
Male	1,660 (92.90)	420 (47.60)	85 (53.80)	3,031 (65.50)	<0.001
Female	127 (7.10)	463 (52.40)	73 (46.20)	1,593 (34.50)
Age (years)	65.51±7.85	51.25±12.99	57.87±12.78	57.12±13.15	<0.001
Height (m)	1.64±0.07	1.62±0.09	1.60±0.08	1.63±0.08	<0.001
Weight (kg)	60.33±9.02	62.12±11.10	60.35±9.90	62.33±10.37	<0.001
Body mass index (kg/m2)	22.29±2.67	23.65±3.28	23.37±2.92	23.29±2.94	<0.001
Smoking status
Ever	860 (62.60)	140 (19.90)	33 (25.80)	1,170 (37.80)	<0.001
Never	513 (37.40)	562 (80.10)	95 (74.20)	1,925 (62.20)
LA data (years)
Pre-LA	108.22±20.51	90.95±17.23	88.56±16.77	80.72±25.68	<0.001
Pre-DeltaLA	42.92±20.17	39.15±17.21	30.66±18.35	23.62±23.07	<0.001
Post-LA	103.81±21.62	81.89±19.49	85.72±17.06	76.57±25.31	<0.001
Post-DeltaLA	38.51±21.10	30.10±17.74	27.81±18.83	19.47±22.39	<0.001
Spirometric data
Pre-FEV1 (L)	1.32±0.59	1.53±0.54	1.64±0.52	1.97±0.79	<0.001
Pre-FVC (L)	2.72±0.74	2.73±0.80	2.17±0.71	2.96±0.89	<0.001
Pre-FEF50% (L/s)	0.73±0.68	0.95±0.61	2.23±1.18	1.82±1.31	<0.001
Pre-FEF75% (L/s)	0.23±0.20	0.28±0.18	0.59±0.37	0.54±0.47	<0.001
Pre-FEV1/FVC ratio	47.68±14.87	55.98±11.82	77.44±14.87	65.97±15.61	<0.001
Post-FEV1 (L)	1.44±0.63	1.78±0.63	1.71±0.52	2.08±0.79	<0.001
Post-FVC (L)	2.87±0.75	2.96±0.84	2.21±0.70	3.04±0.88	<0.001
Post-FEF50% (L/s)	0.91±0.82	1.32±0.84	2.67±1.32	2.18±1.47	<0.001
Post-FEF75% (L/s)	0.30±0.27	0.42±0.28	0.80±0.50	0.69±0.57	<0.001
Post-FEV1/FVC ratio	50.28±15.64	61.01±12.43	80.68±14.63	69.31±15.77	<0.001
PRISm
No	1,715 (96.00)	812 (92.00)	68 (43.00)	4,014 (86.80)	<0.001
Yes	72 (4.00)	71 (8.00)	90 (57.00)	610 (13.20)
Spirometric patterns‡
Obstructive spirometric pattern	911 (51.00)	503 (57.00)	27 (17.10)	2,214 (47.90)	<0.001
Restrictive spirometric pattern	40 (2.2)	19 (2.20)	77 (48.70)	332 (7.20)
Mixed spirometric pattern	817 (45.70)	346 (39.20)	29 (18.40)	1,178 (25.50)
Others	19 (1.1)	15 (1.70)	25 (15.80)	900 (19.50)

Data are presented as frequency (percentage) or mean ± standard deviation. P values for continuous variables were calculated using the independent samples t-test or the Mann-Whitney U test. P values for categorical variables were calculated using the Chi-squared test. ^†, includes patients with suspected or diagnosed asthma, COPD, ILD, or other respiratory diseases and/or symptoms; ^‡, preserved ratio impaired spirometry was defined as FEV₁ <80% predicted with a preserved FEV₁/FVC ratio ≥0.70; obstructive spirometric pattern was defined as FEV₁/FVC <92% predicted but FVC ≥80% predicted; restrictive spirometric pattern was defined as FVC <80% predicted but FEV₁/FVC ≥92% predicted; mixed spirometric pattern was defined as both FEV₁/FVC <92% predicted and FVC <80% predicted. COPD, chronic obstructive pulmonary disease; DeltaLA, the difference between lung age and age; FEF_50%, forced expiratory flow at 50% of forced vital capacity; FEF_75%, forced expiratory flow at 75% of forced vital capacity; FVC, forced vital capacity; FEV₁, forced expiratory volume in one second; ILD, interstitial lung disease; LA, lung age; Post, post-bronchodilator; Pre, pre-bronchodilator; PRISm, preserved ratio impaired spirometry.

Changes in LA and spirometric data after BDR

Following BDR, LA decreased significantly while FEV₁, FVC, FEF_50%, and FEF_75% showed significant increases. Patients with suspected or confirmed asthma showed greater post-bronchodilator improvement than those with other respiratory conditions (all P<0.001; Table 2). Similar trends were observed across different spirometric patterns (see Table S4). The majority of patients remained in their baseline LA category after bronchodilator, while a clinically relevant proportion (34.03%) of those with normally high LA at baseline improved to normal (Table 3). The weighted kappa coefficient for agreement was 0.857 (P<0.001; see Table S5).

Table 2. Changes in LA and spirometry parameters pre- and post-bronchodilator in patient with suspected or diagnosed asthma, COPD and ILD in the training set.

Variables	LA	FEV1	FVC	FEF50%	FEF75%
In the training set (n=7,542)
Pre-BDR, mean ± SD	88.69±26.13	1.75±0.77	2.86±0.85	1.47±1.23	0.43±0.42
Post-BDR, mean ± SD	83.92±26.26	1.88±0.78	2.98±0.85	1.78±1.39	0.57±0.51
Difference, mean ± SD	4.77±6.57	0.13±0.19	0.12±0.23	0.32±0.41	0.13±0.19
P value	<0.001	<0.001	<0.001	<0.001	<0.001
Asthma (n=883)†
Pre-BDR, mean ± SD	90.80±17.27	1.53±0.54	2.75±0.80	0.95±0.61	0.28±0.18
Post-BDR, mean ± SD	81.53±19.52	1.79±0.64	2.97±0.84	1.32±0.85	0.43±0.28
Difference, mean ± SD	9.27±8.63	0.26±2.26	0.23±0.27	0.39±0.43	0.15±0.16
P value	<0.001	<0.001	<0.001	<0.001	<0.001
COPD (n=1,787)†
Pre-BDR, mean ± SD	108.50±20.24	1.30±0.59	2.72±0.74	0.71±0.64	0.22±0.18
Post-BDR, mean ± SD	104.10±20.32	1.43±0.62	2.87±0.74	0.89±0.79	0.29±0.23
Difference, mean ± SD	4.39±6.00	0.12±0.18	0.16±0.24	0.18±0.32	0.07±0.12
P value	<0.001	<0.001	<0.001	<0.001	<0.001
ILD (n=158)†
Pre-BDR, mean ± SD	88.48±16.78	1.65±0.52	2.16±0.69	2.29±0.23	0.62±0.46
Post-BDR, mean ± SD	85.59±17.12	1.71±0.52	2.19±0.68	2.74±1.35	0.84±0.59
Difference, mean ± SD	2.89±3.85	0.06±0.09	0.03±0.12	0.45±0.43	0.22±0.25
P value	<0.001	<0.001	<0.001	<0.001	<0.001

^†, includes patients with diagnosed or suspected asthma, COPD, ILD. BDR, bronchodilators responsiveness; COPD, chronic obstructive pulmonary disease; ILD, interstitial lung disease; LA, lung age; FEF_50%, forced expiratory flow at 50% of forced vital capacity; FEF_75%, forced expiratory flow at 75% of forced vital capacity; FEV₁, forced expiratory volume in one second; FVC, forced vital capacity; SD, standard deviation.

Table 3. Changes in LA groups and positive BDR after bronchodilator.

Variables	Pre-LA group, n (%)			P value
	Normal (n=760)	Normally high (n=523)	Abnormally high (n=6,169)
Post-LA group				<0.001
Normal	736 (96.80)	178 (34.03)	116 (1.88)
Normally high	12 (1.60)	329 (62.91)	254 (4.12)
Abnormally high	12 (1.60)	16 (3.06)	5,799 (94.00)
2021-significant BDR	98 (12.89)	76 (14.53)	1,225 (19.86)	<0.001
2005-significant BDR	66 (8.68)	77 (14.72)	1,252 (20.30)	<0.001
2024-significant BDR	87 (11.45)	80 (15.30)	1,283 (20.78)	<0.001

LA was classified into three groups: normal (DeltaLA ≤0), normally high (DeltaLA >0 and ≤ DeltaLAULN), and abnormally high (DeltaLA > DeltaLAULN). The McNemar-Bowker test for symmetry was used to analyze the changes in lung age classification before and after bronchodilators responsiveness test. The results showed: χ²=386.37, df =2, P<0.001. 2021-significant BDR, an increase of >10% relative to the predicted value for forced expiratory volume in one second or forced vital capacity after bronchodilator; 2005-significant BDR, an absolute increase in either forced expiratory volume in one second or forced vital capacity of ≥12% and ≥200 mL from baseline; 2024-significant BDR, an increase in forced expiratory volume in one second of ≥12% and ≥200 mL from baseline, or ≥10% of predicted. BDR, bronchodilator responsiveness; DeltaLA, the difference between lung age and age; post-LA, post-bronchodilator lung age; pre-LA, pre-bronchodilator lung age; ULN, upper limit of normal.

Significant BDR

Patients in the abnormally high group showed a higher prevalence of significant BDR across three definitions (19.86% by the 2021-BDR, 20.30% by the 2005-BDR, and 20.78% by the 2024-BDR) than those in the normal group (12.89%, 8.68%, and 11.45%, respectively) and the normally high group (14.53%, 14.72%, and 15.30%, respectively) (all P<0.001; Table 3). Patients in the abnormally high group after bronchodilation had a higher significant BDR than those in other groups, and patients with suspected or diagnosed asthma had a higher BDR than those with suspected or diagnosed COPD and ILD (Table 4).

Table 4. Changes in LA groups and positive BDR after bronchodilator with suspected or diagnosed asthma, COPD, and ILD.

Characteristics	Post-LA group, n (%)			P value
	Normal	Normally high	Abnormally high
Asthma (n=883)†
2021-significant BDR	13 (1.47)	19 (2.15)	360 (40.77)	<0.001
2005-significant BDR	13 (1.47)	20 (2.27)	383 (43.37)	<0.001
2024-significant BDR	13 (1.47)	20 (2.27)	387 (43.83)	<0.001
COPD (n=1,787)†
2021-significant BDR	10 (0.60)	7 (0.39)	338 (18.94)	<0.001
2005-significant BDR	10 (0.60)	5 (0.30)	288 (16.12)	<0.001
2024-significant BDR	11 (0.62)	6 (0.34)	296 (16.56)	<0.001
ILD (n=158)†
2021-significant BDR	0	0	4 (2.53)	<0.001
2005-significant BDR	0	0	6 (3.80)	<0.001
2024-significant BDR	0	0	5 (3.16)	<0.001

All patients were grouped in the abnormally high group before bronchodilator administration. LA was classified into three groups: normal (DeltaLA ≤0), normally high (DeltaLA >0 and ≤ DeltaLAULN), and abnormally high (DeltaLA > DeltaLAULN). ^†, includes patients with diagnosed or suspected asthma, COPD, ILD; 2021-significant BDR, an increase of >10% relative to the predicted value for forced expiratory volume in one second or forced vital capacity after bronchodilator; 2005-significant BDR, an increase in either forced expiratory volume in one second or forced vital capacity of ≥12% and ≥200 mL from baseline; 2024-significant BDR, an increase in forced expiratory volume in one second of ≥12% and ≥200 mL from baseline, or ≥10% of predicted. BDR, bronchodilator responsiveness; COPD, chronic obstructive pulmonary disease; DeltaLA, the difference between lung age and age; ILD, interstitial lung disease; LA, lung age; ULN, upper limit of normal.

Predictors of LA improvement after BDR

In the training set, 548 individuals (7.35%) demonstrated an improvement in LA after BDR, among whom 231 (42.20%) were female (see Table S6). Random forest analysis identified pre-LA, pre-FEF_50% and age as the three most important predictors of LA improvement. The model demonstrated robust performance, with an out-of-bag (OOB) error rate of 6.92% and internal validation accuracy of 92.6% (see Table S7).

Correlations and predictive performance for post-bronchodilator FEV1/FVC ratio <0.7

DeltaLA showed negative nonlinear correlations with these parameters, including FEV₁ (r=−0.80), FEF_50% (r=−0.70), FEF_75% (r=−0.60) and FVC (r=−0.46; all P<0.001; Figure 1). In the training set, the optimal cutoff value for FEV₁/FVC% predicted in identifying post-bronchodilator FEV₁/FVC ratio <0.7 was 78.15, with corresponding values of −19.60 for ULNLA and 64.08 for FEV₁% predicted (Table S8 and Figure 2A). Internal validation confirmed FEV₁/FVC% predicted as the most accurate discriminator (AUC =0.98), whereas ULNLA and FEV₁% predicted showed comparable performance (AUC: 0.84 vs. 0.85; Table S8 and Figure 2B). Subgroup analyses in patients with suspected asthma or COPD are provided in Tables S9,S10 and Figures S1,S2.

Figure 1.

Correlation between DeltaLA and FEV₁, FVC, FEF_50%, FEF_75% before and after bronchodilator responsiveness. Post-DeltaLA, difference between lung age and age after bronchodilator responsiveness; Post-FEF₅₀, forced expiratory flow at 50% of forced vital capacity after bronchodilator responsiveness; Post-FEF₇₅, forced expiratory flow at 75% of forced vital capacity after bronchodilator responsiveness; Post-FEV₁, forced expiratory volume in one second after bronchodilator responsiveness; Post-FVC, forced vital capacity after bronchodilator responsiveness; Pre-DeltaLA, difference between lung age and age before bronchodilator responsiveness; Pre-FEF₅₀, forced expiratory flow at 50% of forced vital capacity before bronchodilator responsiveness; Pre-FEF₇₅, forced expiratory flow at 75% of forced vital capacity before bronchodilator responsiveness; Pre-FEV₁, forced expiratory volume in one second before bronchodilator responsiveness; Pre-FVC, forced vital capacity before bronchodilator responsiveness.

Figure 2.

The ability of ULNLA and %predicted of spirometric parameters before bronchodilator to predict groups with and without FEV₁/FVC ratio <0.7 after bronchodilation. (A) In the training set. (B) In the validation set. Pre-FEF_50%pred, forced expiratory flow at 50% of forced vital capacity percent predicted before bronchodilator responsiveness; Pre-FEF_75%pred, forced expiratory flow at 75% of forced vital capacity percent predicted before bronchodilator responsiveness; Pre-FEV₁%pred, forced expiratory volume in one second percent predicted before bronchodilator responsiveness; Pre-FEV₁/FVC%pred, forced expiratory volume in one second to forced vital capacity ratio percent predicted before bronchodilator responsiveness; Pre-FVC%pred, forced vital capacity percent predicted before bronchodilator responsiveness; Pre-ULNLA, the difference between the upper limit of the normal for lung age and lung age before bronchodilator responsiveness.

Discussion

Our findings demonstrated that LA was significantly influenced by BDR. DeltaLA showed negative nonlinear correlations with FEV₁, FEF_50%, FEF_75% and FVC. Random forest analysis identified pre-LA, pre-FEF_50%, and age as the three most important predictors of LA improvement. Furthermore, ROC analysis showed that the ability of ULNLA and FEV₁% predicted showed comparable performance for post-bronchodilator FEV₁/FVC ratio <0.7.

LA has gained acceptance among primary care providers as a practical tool for communicating lung health status to patients (31). Previous studies have shown that bronchodilators can partially relieve lung hyperinflation and exert a greater effect on FVC than on FEV₁ (32). Reliance on pre-bronchodilator spirometric parameters for disease classification may lead to an overestimate of COPD prevalence (33). In our study, 34.03% of patients with normally high LA at baseline improved to normal LA after BDR testing, consistent with previous findings in specific COPD subgroups (34,35). Post-bronchodilator spirometric parameters have been reported to better true disease phenotype and prognosis (36). We found that 21.83% of patients with abnormally high LA exhibited a significant BDR. Patients with suspected or diagnosed asthma exhibited relatively a higher positive BDR compared to those with suspected or diagnosed COPD and ILD, which aligns with the known pathophysiology of more reversible airway obstruction in asthma. These associations were robust to different definitions of BDR positivity in sensitivity analyses, supporting the importance of accounting for BDR when interpreting LA in clinical practice.

Small airway dysfunction is increasingly recognized as an early marker of airway disease, often preceding abnormalities in FEV₁ or the FEV₁/FVC ratio (37,38), and is closely linked to disease progression and treatment response (39). Although LA was calculated from spirometric parameters including parameters reflecting both large and small airways, we observed a discordant relationship between DeltaLA and FEF_75% in some individuals, who exhibited low DeltaLA despite low FEF_75%, suggesting that DeltaLA may not fully capture functional impairment localized to the smallest airways. Notably, no additional lung function tests specifically targeting peripheral airway function were performed in this study, such as impulse oscillometry and multiple-breath nitrogen washout. Therefore, the assessment of the smallest airways relied solely on spirometry, which is known to have limited sensitivity for early peripheral airway abnormalities (40).

Our analysis showed that despite this “translation” into an age-based metric, LA retained discriminatory power similar to a key traditional spirometric index (FEV₁% predicted) for identifying persistent airflow limitation. This finding may be of particular interest in contexts like screening or patient communication, where a simple, intuitive metric like LA (“your lungs are 20 years older than you are”) could be a powerful tool for engagement, while still providing a statistically robust indication of underlying obstruction. Previous studies support the broader utility of LA-based metrics. LA helped to predict postoperative pulmonary complications and survival in patients undergoing lung cancer surgery (41). Similarly, DeltaLA has been associated with postoperative outcomes in esophageal cancer patients, in whom a greater DeltaLA (particularly ≥15) correlates with increased complications and reduced survival (17).

This study had several notable strengths. To our knowledge, it is the first study to assess the impact of BDR on LA estimation. Moreover, we performed comprehensive subgroup analyses based on both clinical diagnosis and spirometric patterns. The findings across these subgroups were similar to those observed in the overall heterogeneous cohort, supporting the robustness of our results. Furthermore, all spirometric measurements underwent rigorous quality control and using an LA reference equation derived from the Chinese population, thereby minimizing potential bias related to ethnic differences. Nevertheless, several limitations should also be acknowledged. First, detailed information on pre-test use of inhaled medications, as well as potentially influential variables such as environmental exposures, quantitative smoking metrics and clinical comorbidities, was not available for analysis, which may have confounded BDR results. Second, as a derived parameter dependent on reference equations, LA is subject to inherent limitations in accuracy and generalizability. Therefore, we do not propose replacing conventional spirometric parameters with LA; it should be considered a complementary tool in clinical assessment.

Conclusions

In summary, pre-bronchodilator LA alone may result in misclassification, whereas post-bronchodilator LA provides a more accurate evaluation. ULNLA demonstrates predictive ability of airflow limitation is comparable to FEV₁% predicted.

Supplementary

The article’s supplementary files as

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments, and was approved by the institutional ethics committee of the First Affiliated Hospital of Guangzhou Medical University (approval No. 2020-124). Given the retrospective nature of the investigation, the requirement for informed consent was waived.

Data Sharing Statement

Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-aw-2382/dss

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DOI: 10.21037/jtd-2025-aw-2382