LAUSR

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 centre outcome. Methods: This is a single-centre retrospective analysis of routinely collected data from 2013-2016 among 208 adults. Year-to-year %FEV 1 change was calculated by subtracting best %FEV 1 at Year 1 from Year 2 (i.e. negative values indicate fall in %FEV 1), 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, year-to-year variation in %FEV 1 calculated using GLI equation was adjusted for baseline %FEV 1 to understand the impact of case-mix adjustment. Results: Year-to-year fall in %FEV 1 reduced with all three data processing methods but the magnitude of this change 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 reduced year-to-year fall in %FEV 1 was robust, different data processing methods yielded varying results when year-to-year variation in %FEV 1 was compared using a standard related group non-parametric statistical test. Observational studies with year-to-year variation in %FEV 1 as an outcome measure should carefully consider and clearly specify the data processing methods used.