Reconsidering the Utility of Race-Specific Lung Function Prediction Equations

Aaron Baugh(University of California, San Francisco), Stephen Shiboski(University of California, San Francisco), Nadia N. Hansel(Johns Hopkins University), Victor E. Ortega(Wake Forest University), Igor Barjaktarević(University of California, Los Angeles), R. Graham Barr(Columbia University Irving Medical Center), Russell P. Bowler(National Jewish Health), Alejandro P. Comellas(University of Iowa), Christopher B. Cooper(Johns Hopkins University), David Couper(University of North Carolina at Chapel Hill), Gerard J. Criner(Temple University), Jeffrey L. Curtis(University of Michigan), Mark T. Dransfield(University of Alabama at Birmingham), Chinedu Ejike(Johns Hopkins University), MeiLan K. Han(University of Michigan), Eric A. Hoffman(University of Iowa), Jamuna K. Krishnan(Cornell University), Jerry A. Krishnan(Cornell University), David M. Mannino(University of Kentucky), Robert Paine(University of Utah), Trisha M. Parekh(University of Alabama at Birmingham), Stephen P. Peters(Wake Forest University), Nirupama Putcha(Johns Hopkins University), Stephen I. Rennard(University of Nebraska at Omaha), Neeta Thakur(University of California, San Francisco), Prescott G. Woodruff(University of California, San Francisco)
American Journal of Respiratory and Critical Care Medicine
December 16, 2021
Cited by 109Open Access
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Abstract

Abstract Rationale African American individuals have worse outcomes in chronic obstructive pulmonary disease (COPD). Objectives To assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognize pathological decrements and considering them normal. Methods In a cohort with and at risk for COPD, we assessed whether lung function prediction equations applied in a race-specific versus universal manner better modeled the relationship between FEV1, FVC, and other COPD outcomes, including the COPD Assessment Test, St. George’s Respiratory Questionnaire, computed tomography percent emphysema, airway wall thickness, and 6-minute-walk test. We related these outcomes to differences in FEV1 using multiple linear regression and compared predictive performance between fitted models using root mean squared error and Alpaydin’s paired F test. Measurements and Main Results Using race-specific equations, African American individuals were calculated to have better lung function than non-Hispanic White individuals (FEV1, 76.8% vs. 71.8% predicted; P = 0.02). Using universally applied equations, African American individuals were calculated to have worse lung function. Using Hankinson’s Non-Hispanic White equation, FEV1 was 64.7% versus 71.8% (P < 0.001). Using the Global Lung Initiative’s Other race equation, FEV1 was 70.0% versus 77.9% (P < 0.001). Prediction errors from linear regression were less for universally applied equations compared with race-specific equations when examining FEV1% predicted with the COPD Assessment Test (P < 0.01), St. George’s Respiratory Questionnaire (P < 0.01), and airway wall thickness (P < 0.01). Although African American participants had greater adversity (P < 0.001), less adversity was only associated with better FEV1 in non-Hispanic White participants (P for interaction = 0.041). Conclusions Race-specific equations may underestimate COPD severity in African American individuals.Clinical trial registered with www.clinicaltrials.gov (NCT01969344).


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