Implications of Race Adjustment in Lung-Function Equations

Abstract

Background: Adjustment for race is discouraged in lung-function testing, but the implications of adopting race-neutral equations have not been comprehensively quantified.

Methods: We obtained longitudinal data from 369,077 participants in the National Health and Nutrition Examination Survey, U.K. Biobank, the Multi-Ethnic Study of Atherosclerosis, and the Organ Procurement and Transplantation Network. Using these data, we compared the race-based 2012 Global Lung Function Initiative (GLI-2012) equations with race-neutral equations introduced in 2022 (GLI-Global). Evaluated outcomes included national projections of clinical, occupational, and financial reclassifications; individual lung-allocation scores for transplantation priority; and concordance statistics (C statistics) for clinical prediction tasks.

Results: Among the 249 million persons in the United States between 6 and 79 years of age who are able to produce high-quality spirometric results, the use of GLI-Global equations may reclassify ventilatory impairment for 12.5 million persons, medical impairment ratings for 8.16 million, occupational eligibility for 2.28 million, grading of chronic obstructive pulmonary disease for 2.05 million, and military disability compensation for 413,000. These potential changes differed according to race; for example, classifications of nonobstructive ventilatory impairment may change dramatically, increasing 141% (95% confidence interval [CI], 113 to 169) among Black persons and decreasing 69% (95% CI, 63 to 74) among White persons. Annual disability payments may increase by more than $1 billion among Black veterans and decrease by $0.5 billion among White veterans. GLI-2012 and GLI-Global equations had similar discriminative accuracy with regard to respiratory symptoms, health care utilization, new-onset disease, death from any cause, death related to respiratory disease, and death among persons on a transplant waiting list, with differences in C statistics ranging from -0.008 to 0.011.

Conclusions: The use of race-based and race-neutral equations generated similarly accurate predictions of respiratory outcomes but assigned different disease classifications, occupational eligibility, and disability compensation for millions of persons, with effects diverging according to race. (Funded by the National Heart Lung and Blood Institute and the National Institute of Environmental Health Sciences.).

Figure 1.. Clinical, Occupational, and Financial Outcomes in the United States Calculated with Race-Based versus Race-Neutral Lung-Function Equations.

Shown are outcomes for study participants with regard to obstructive ventilatory impairment (Panel A), nonobstructive ventilatory impairment (Panel B), chronic obstructive pulmonary disease (COPD) of grade 2 or higher on the Global Initiative for Chronic Obstructive Lung Disease (GOLD) scale (Panel C), disqualification from firefighting occupations (Panel D), American Medical Association (AMA) impairment classifications (Panel E), and Department of Veterans Affairs disability payments (Panel E) when lung function was interpreted with the use of race-based Global Lung Function Initiative 2012 (GLI-2012) equations and with race-neutral GLI-Global equations. Data from the National Health and Nutrition Examination Survey (NHANES) 2007–2012 were survey-adjusted to be representative of the U.S. population (see the Supplementary Methods section). Error bars represent 95% confidence intervals for outcome values. Numeric labels represent relative changes between the outcomes projected on the basis of GLI-2012 equations (lighter) and GLI-Global equations (darker); confidence intervals overlapping 0 were not labeled. Because outcome values calculated with the use of GLI-2012 and GLI-Global equations are highly correlated, uncertainties in adjacent bars cannot be used to approximate the uncertainty in their difference.

Figure 2.. Implications of Race-Based Lung-Function Equations for the 2020 U.S. Lung-Transplant Waiting List.

Panel A shows the position on the U.S. lung-transplant waiting list and expected waiting time for 1399 candidates on January 1, 2020. The percent of the predicted forced vital capacity (FVC) was calculated with the use of race-based GLI-2012 equations or race-neutral GLI-Global equations. Positions on the waiting list are ordered according to decreasing lung-allocation score. A lower position on the waiting list and higher lung-allocation score indicate higher priority, with ties broken by accrued wait time. This retrospective analysis is specific to the 2020 waiting list; newer allocation scores do not use spirometry to determine transplant priority. Dark-colored lines indicate candidates who had changes in both waiting-list position and lung-allocation score. Light-colored lines indicate candidates who had changes in waiting-list position but not in lung-allocation score. Gray lines indicate candidates who had no changes in either waiting-list position or lung-allocation score. White candidates were downsampled by 70% to aid visualization. Expected wait time is a linear function of the initial position on the waiting list, allowing dual-axis plotting (Fig. S1). Data are from the Organ Procurement and Transplantation Network (OPTN). Panel B shows demographic, clinical, and waiting-list characteristics of the candidates who were most and least advantaged by the use of GLI-Global equations rather than GLI-2012 equations, with advantage measured as change in expected wait time. OPTN data in the Gender column represent patient-reported gender identification.