Key result
Race-specific lung function equations underestimate COPD severity in African Americans compared to race-neutral algorithms.
Why the study?
Evidence suggests race inclusion in clinical algorithms may perpetuate inequities, prompting an assessment of literature on the negative impact of race-based pulmonary function prediction equations in African Americans with COPD.
Do race-neutral lung function testing algorithms improve diagnostic accuracy and severity classification in African American adults with COPD compared to race-specific algorithms?
Do race-neutral lung function testing algorithms improve diagnostic accuracy and severity classification in African American adults with COPD compared to race-specific algorithms?
Eliminating race-based reference values in pulmonary function tests potentially reduces the underestimation of COPD severity in African Americans.
Aim: Increasing evidence suggests that the inclusion of self-identified race in clinical decision algorithms may perpetuate longstanding inequities. Until recently, most pulmonary function tests utilized separate reference equations that are race/ethnicity based. Purpose: We assess the magnitude and scope of the available literature on the negative impact of race-based pulmonary function prediction equations on relevant outcomes in African Americans with COPD. Methods: We performed a scoping review utilizing an English language search on PubMed/Medline, Embase, Scopus, and Web of Science in September 2022 and updated it in December 2023. We searched for publications regarding the effect of race-specific vs race-neutral, race-free, or race-reversed lung function testing algorithms on the diagnosis of COPD and COPD-related physiologic and functional measures. Joanna Briggs Institute (JBI) guidelines were utilized for this scoping review. Eligibility criteria: The search was restricted to adults with COPD. We excluded publications on other lung disorders, non-English language publications, or studies that did not include African Americans. The search identified publications. Ultimately, six peer-reviewed publications and four conference abstracts were selected for this review. Results: Removal of race from lung function prediction equations often had opposite effects in African Americans and Whites, specifically regarding the severity of lung function impairment. Symptoms and objective findings were better aligned when race-specific reference values were not used. Race-neutral prediction algorithms uniformly resulted in reclassifying severity in the African Americans studied. Conclusion: The limited literature does not support the use of race-based lung function prediction equations. However, this assertion does not provide guidance for every specific clinical situation. For African Americans with COPD, the use of race-based prediction equations appears to fall short in enhancing diagnostic accuracy, classifying severity of impairment, or predicting subsequent clinical events. We do not have information comparing race-neutral vs race-based algorithms on prediction of progression of COPD. We conclude that the elimination of race-based reference values potentially reduces underestimation of disease severity in African Americans with COPD.
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Davidson et al. (2024) conducted a review in Chronic Obstructive Pulmonary Disease (COPD). Race-specific pulmonary function prediction equations vs. Race-neutral or universal prediction equations was evaluated on Diagnosis and severity classification of COPD. The use of race-specific pulmonary function prediction equations in African Americans with COPD leads to inadequate characterization and underestimation of disease severity compared to race-neutral algorithms.
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