Race-Specific Interpretation of Spirometry: Impact on the Lung Allocation Score

Area of Science:

• Pulmonary Medicine
• Health Disparities Research
• Transplantation Science

Background:

• Race-specific spirometry reference equations may lead to underestimation of lung function impairment in Black patients.
• This underestimation can affect the Lung Allocation Score (LAS), a key factor in lung transplant priority.
• The use of percentage predicted forced vital capacity (FVCpp) in LAS calculations is particularly sensitive to spirometry interpretation.

Purpose of the Study:

• To evaluate the impact of race-specific versus race-neutral spirometry interpretation on the LAS for adult lung transplant candidates in the U.S.
• To determine if race-based equations contribute to disparities in lung transplant allocation.

Main Methods:

• A cohort of White and Black adult lung transplant candidates listed between 2009 and 2015 was analyzed using the United Network for Organ Sharing database.
• Lung Allocation Scores (LAS) were calculated using both race-specific and race-neutral Global Lung Function Initiative (GLFI) equations for FVCpp.
• Differences in LAS between the two approaches were compared across racial groups.

Main Results:

• A race-neutral approach resulted in a higher mean FVCpp for White patients (+4.4%) and a lower mean FVCpp for Black patients (-3.8%) compared to race-specific equations.
• Black patients had a higher mean LAS than White patients under both approaches, but the difference was smaller with a race-neutral approach (-0.6 for White vs. +0.6 for Black patients).
• The disparity in LAS was most pronounced in patients with pulmonary vascular disease (Group B) and restrictive lung disease (Group D).

Conclusions:

• Race-specific spirometry interpretation can adversely affect Black patients with severe respiratory disease by lowering their LAS.
• A race-neutral approach may reduce racial bias in lung transplant allocation by providing more equitable LAS values.
• The continued use of race-specific equations in clinical practice warrants careful consideration due to potential contributions to health disparities.