Using different methods to process forced expiratory volume in one second (FEV 1) data can impact on the interpretation of FEV 1 as an outcome measure to understand the performance of an adult cystic fibrosis centre: A retrospective chart review.

Background: Forced expiratory volume in one second (FEV 1) is an important cystic fibrosis (CF) prognostic marker and an established endpoint for CF clinical trials. FEV 1 is also used in observation studies, e.g. to compare different centre's outcomes. We wished to evaluate whether different methods of processing FEV 1 data can impact on a centre's outcome. Methods: This is a single-centre retrospective analysis of routinely collected data from 2013-2016 which included 208 adults with CF. Year-to-year %FEV 1 change was calculated by subtracting best %FEV 1 at Year 1 from Year 2 (i.e. negative values indicate %FEV 1 decline), and compared using Friedman test. Three methods were used to process %FEV 1 data. First, %FEV 1 calculated with Knudson equation was extracted directly from spirometer machines. Second, FEV 1 volume were extracted then converted to %FEV 1 using clean height data and Knudson equation. Third, FEV 1 volume were extracted then converted to %FEV 1 using clean height data and GLI equation. In addition, %FEV 1 decline calculated using GLI equation was adjusted for baseline %FEV 1 to understand the impact of case-mix adjustment. Results: There was a trend of reduction in %FEV 1 decline with all three data processing methods but the magnitude of %FEV 1 decline differed. Median change in %FEV 1 for 2013-2014, 2014-2015 and 2015-2016 was -2.0, -1.0 and 0.0 respectively using %FEV 1 in Knudson equation whereas the median change was -1.1, -0.9 and -0.3 respectively using %FEV 1 in the GLI equation. A statistically significant p-value (0.016) was only obtained when using %FEV 1 in Knudson equation extracted directly from spirometer machines. Conclusions: Although the trend of reduction in %FEV 1 decline was robust, different data processing methods yielded varying results when %FEV 1 decline was compared using a standard related group non-parametric statistical test. Observational studies with %FEV 1 decline as an outcome measure should carefully consider and clearly specify the data processing methods used.