Longitudinal Spirometric Trajectory from Normal Lung Function to PRISm and COPD in a Population-Based Korean Cohort

Chronic obstructive pulmonary disease (COPD) develops through heterogeneous lung-function trajectories, but the longitudinal role of preserved ratio impaired spirometry (PRISm) in progression toward COPD remains unclear.

We aimed to characterize long-term spirometric trajectories and transitions from normal spirometry to PRISm or COPD in a population-based cohort.

We analyzed data from the Ansan-Ansung cohort of the Korean Genome and Epidemiology Study. Among medication-free participants with normal baseline spirometry who had classifiable spirometry across seven examinations over approximately 12 years, longitudinal trajectories of forced expiratory volume in 1 second (FEV₁, % predicted) and the FEV₁/FVC ratio were evaluated. Participants were classified into normal maintenance, PRISm, or COPD trajectory groups using a clinically interpretable, rule-based approach. Because post-bronchodilator measurements were not available across all examinations, COPD was operationally defined using pre-bronchodilator spirometry as FEV₁/FVC < 0.70.

Lung-function decline followed heterogeneous trajectories rather than a single linear pathway. Among 1,753 participants, 1,658 (94.6%) remained normal, 21 (1.2%) developed PRISm, and 74 (4.2%) progressed to COPD. Most individuals who developed COPD did so without a preceding sustained PRISm phase. In descriptive baseline comparisons, the COPD trajectory showed greater smoking exposure, higher blood pressure, and more pronounced central adiposity, whereas PRISm was more closely associated with wheeze-related respiratory symptoms and lower baseline lung function. In multivariable logistic regression, older age and current smoking were the strongest independent predictors of progression to COPD.

Progression toward COPD in the general population is heterogeneous, and PRISm is not an obligatory precursor to COPD. Longitudinal spirometric assessment may provide clinically relevant insights beyond single time-point classification in the general population.