Worldwide patterns of bronchodilator responsiveness: results from the Burden of Obstructive Lung Disease study

Abstract

Rationale: Criteria for a clinically significant bronchodilator response (BDR) are mainly based on studies in patients with obstructive lung diseases. Little is known about the BDR in healthy general populations, and even less about the worldwide patterns.

Methods: 10 360 adults aged 40 years and older from 14 countries in North America, Europe, Africa and Asia participated in the Burden of Obstructive Lung Disease study. Spirometry was used before and after an inhaled bronchodilator to determine the distribution of the BDR in population-based samples of healthy non-smokers and individuals with airflow obstruction.

Results: In 3922 healthy never smokers, the weighted pooled estimate of the 95th percentiles (95% CI) for bronchodilator response were 284 ml (263 to 305) absolute change in forced expiratory volume in 1 s from baseline (ΔFEV(1)); 12.0% (11.2% to 12.8%) change relative to initial value (%ΔFEV(1i)); and 10.0% (9.5% to 10.5%) change relative to predicted value (%ΔFEV(1p)). The corresponding mean changes in forced vital capacity (FVC) were 322 ml (271 to 373) absolute change from baseline (ΔFVC); 10.5% (8.9% to 12.0%) change relative to initial value (ΔFVC(i)); and 9.2% (7.9% to 10.5%) change relative to predicted value (ΔFVC(p)). The proportion who exceeded the above threshold values in the subgroup with spirometrically defined Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 2 and higher (FEV(1)/FVC <0.7 and FEV(1)% predicted <80%) were 11.1%, 30.8% and 12.9% respectively for the FEV(1)-based thresholds and 22.6%, 28.6% and 22.1% respectively for the FVC-based thresholds.

Conclusions: The results provide reference values for bronchodilator responses worldwide that confirm guideline estimates for a clinically significant level of BDR in bronchodilator testing.

Figure 1

Absolute change in forced expiratory volume in 1 s (FEV₁) in ml after bronchodilator (ΔFEV₁) expressed as 95th percentile with 95% CI in healthy non-smokers. Those sites whose estimates are most stable get greater weight (right-hand column) in constructing the pooled estimate of 284 ml. We observed significant heterogeneity across sites (p=0.008), with 54% of the overall variability in the data attributable to site–site variability.

Figure 2

Percentage change in forced expiratory volume in 1 s (FEV₁) relative to initial baseline, after bronchodilator (BDR FEV_1i) expressed as 95th percentile with 95% CI in healthy non-smokers. The pooled estimate is 12% with no evidence of cross-site heterogeneity.

Figure 3

Percentage change in forced expiratory volume in 1 s (FEV₁) relative to predicted FEV₁, after bronchodilator (%ΔFEV_1p) expressed as 95th percentile with 95% CI in healthy non-smokers. The pooled estimate is 10% with no evidence of cross-site heterogeneity.

Figure 4

Absolute change in forced vital capacity (FVC) after bronchodilator (BDR FVC, ml) expressed as 95th percentile with 95% CI in healthy non-smokers. Those sites whose estimates are most stable get greater weight (right-hand column) in constructing the pooled estimate of 322 ml. We observed significant heterogeneity across sites (p<0.0001), with 75% of the overall variability in the data attributable to site–site variability.

Figure 5

Percentage change in forced vital capacity (FVC) relative to initial baseline, after bronchodilator (BDR FVC_1i) expressed as 95th percentile with 95% CI in healthy non-smokers. Those sites whose estimates are most stable get greater weight (right-hand column) in constructing the pooled estimate of 11%. We observed significant heterogeneity across sites (p<0.0001), with 66% of the overall variability in the data attributable to site–site variability.

Figure 6

Percentage change in forced vital capacity (FVC) relative to predicted FVC, after bronchodilator (BDR FVC_p) expressed as 95th percentile with 95% CI in healthy non-smokers. Those sites whose estimates are most stable get greater weight (right-hand column) in constructing the pooled estimate of 9%. We observed significant heterogeneity across sites (p<0.0001), with 80% of the overall variability in the data attributable to site–site variability.