TY - JOUR
T1 - Comparing Spirometric Reference Values From Childhood to Old Age Estimated by LMS and Linear Regression Models
JO - Archivos de Bronconeumología
T2 -
AU - Martínez-Briseño,David
AU - Gochicoa-Rangel,Laura
AU - Torre-Bouscoulet,Luis
AU - Cid-Juárez,Silvia
AU - Fernández-Plata,Rosario
AU - Martínez-Valdeavellano,Luisa
AU - Chapela-Lara,Sofía
AU - del Río-Hidalgo,Rodrigo
AU - Pérez-Padilla,Rogelio
SN - 03002896
M3 - 10.1016/j.arbres.2019.12.033
DO - 10.1016/j.arbres.2019.12.033
UR - https://archbronconeumol.org/en-comparing-spirometric-reference-values-from-articulo-S030028962030020X
AB - BackgroundProper reference values for lung function testing are essential for achieving adequate interpretations. The LMS procedure (lambda, mu, sigma) permits continuous analyses of entire populations avoiding gaps in the transition between childhood and adulthood. It also allows more precise calculations of average values, dispersion, and 5th percentiles, which are usually considered the lower limit of normality. The objective of this study was to compare our results fitted with the LMS method with standard multiple linear regression, and with those from international Global Lung Function Initiative (GLI) equations. MethodsData from 9835 healthy residents of the metropolitan area of Mexico City aged 8–80 years were compiled from several studies: EMPECE, PLATINO, adult Mexican workers and two unpublished studies. The LMS procedure and multiple linear regression models were fit to obtain reference equations using R software. ResultsResiduals from the LMS models had a median closer to zero, and smaller dispersion than those from the linear model, but differences although statistically significant were very small and of questionable practical relevance. For example, for females and ln(FEV1), median residual was −0.001 with p25 of −0.08 and p75 of 0.08 for LMS, compared with 0.004 (−0.08, 0.09) [p<0.05] for the linear model. Average spirometric values for a given height for our population, were higher than those predicted by the GLI study. ConclusionContinuous reference equations for the Mexican population calculated using the LMS technique showed slightly better fit than linear regression models.
ER -