Addressing Race in Pulmonary Function Testing by Aligning Intent and Evidence With Practice and Perception

Abstract

The practice of using race or ethnicity in medicine to explain differences between individuals is being called into question because it may contribute to biased medical care and research that perpetuates health disparities and structural racism. A commonly cited example is the use of race or ethnicity in the interpretation of pulmonary function test (PFT) results, yet the perspectives of practicing pulmonologists and physiologists are missing from this discussion. This discussion has global relevance for increasingly multicultural communities in which the range of values that represent normal lung function is uncertain. We review the underlying sources of differences in lung function, including those that may be captured by race or ethnicity, and demonstrate how the current practice of PFT measurement and interpretation is imperfect in its ability to describe accurately the relationship between function and health outcomes. We summarize the arguments against using race-specific equations as well as address concerns about removing race from the interpretation of PFT results. Further, we outline knowledge gaps and critical questions that need to be answered to change the current approach of including race or ethnicity in PFT results interpretation thoughtfully. Finally, we propose changes in interpretation strategies and future research to reduce health disparities.

Keywords: pulmonary function test; race or ethnicity; racial disparities; reference equations.

Figure 1

A, B, Graphs showing differences between vs within racial and ethnic groups. A, Data from the Global Lung Function Initiative (GLI) showing differences in FEV₁ between self-identified backgrounds at the same age and average height. (Reprinted with permission from Quanjer et al¹³) B, Data from GLI showing variation in FEV₁. About half of the scatter is accounted for statistically by differences in standing height. The remaining half of the variation remains large compared with the differences between backgrounds in (A). FVC follows the same trend as FEV₁, which leads to a similar ratio of FEV₁ to FVC between backgrounds.

Figure 2

Diagram showing a proposed approach to include PFTs with other factors into clinical decisions. This approach allows clinicians and patients to appreciate the limitations of interpretation based on comparison to reference values and to frame the role of PFTs in decision-making relative to other data about the patient. Multivariate models allow for a Bayesian approach where the inputs capture probabilities of outcomes before PFTs and the output provides probabilities after PFTs, rather than an normal-abnormal dichotomization of PFT results based on fixed thresholds. ∗Use of race can help to identify health inequities and to ensure broad inclusion in research. PFT = pulmonary function test.