Novel regression equations predicting lung age from varied spirometric parameters

Although lung age calculated backward from regression formulas constructed for FEV1 estimation is widely used, it possesses a couple of faults. We developed novel equations predicting lung age from varied spirometric parameters (spirometry-derived lung age (SDL-age)). Applying multiple regression analysis, equations predicting SDL-age were invented using data from 8015 never-smokers with normal spirometry (group I). Validation was made based on data from 6398 never-smokers with normal spirometry (group II). Equations were further applied for 446 subjects with airflow limitation. FEV1, FEV1/FVC, FEF50, and PEF were selected as explanatory variables for reference value of SDL-age. Normal limits of difference between SDL-age and chronological-age were ±13.4 years in the male and ±15.0 years in the female. Established equations predicted SDL-age of group II. SDL-age was older than chronological-age only in subjects with severe airflow limitation. Novel regression equations allowing prediction of reference value of SDL-age and normal limits of difference between SDL-age and chronological-age were elaborated in both genders.

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► Lung age is widely used to promote smoking cessation and to enlighten COPD patients.
► Regression equations for lung age proposed by Morris possess a couple of defects.
► This study provides novel equations allowing reliable prediction of lung age.
► Next, ethnic-specific equations for lung age should be established in each race.