It’s Important to Challenge Assumptions in Pulmonary Care, Says Dr Aparna Balasubramanian

Aparna Balasubramanian, MD, assistant professor of medicine, division of pulmonary and critical care, Johns Hopkins School of Medicine, discusses the need to contest previously held beliefs, such as the use of race-specific equations that can help detect chronic obstructive pulmonary disease (COPD). Balasubramanian is attending the CHEST Annual Meeting 2023, where themes of equity are woven throughout the agenda.

Transcript

Some of your studies focus on how disparities impact pulmonary care. One study called "Early Evidence of COPD Obscured by Race-Specific Prediction Equations" found that race-specific equations underestimate disease severity amongst African-Americans, with these effects especially evident in early disease and might result in late COPD detection.

What are some ways race-specific equations can be rectified, and how can they be implemented into clinical practice?

Race-specific equations are a result of observed epidemiologic data that suggest that average lung function is lower among Blacks than in Whites. So generally, the race-specific equations were meant to account for that. But that has led to an assumption that that lower lung function is expected or normal among Black individuals. This study specifically was trying to demonstrate that by using these equations and buying into that assumption, we underestimate disease severity and underdiagnose disease in specifically COPD. The field was really working very hard at trying to identify reasonable alternatives to address this issue, because obviously, we don't want to be propagating a method for interpretation of lung function that is harmful to one specific community, one specific population.

Current recommendations are to use a single reference equation, which is known as GLI Global, or the [Global Lung Function Initiative] global equation, for all races to try and mitigate the kind of selective underestimation that we just described. The benefit of that equation is that it treats low lung function values similarly across all races. Of course, that does sort of fall into a bin of a one-size-fits all. There's a lot of research surrounding alternatives that might be a little bit better that are a bit more conscientious of differences across populations.

I think, generally, the community is trying to think about non–reference equation–based methods for understanding lung function, things like using just FEV₁ [forced expiratory volume in 1 second] in its absolute form, using something like FEV₁Q [FEV₁ quotient] or FEV₁ over height squared, but there's a lot more work that has to be done in that arena. I think the other piece of this, in terms of rectifying the issues surrounding race-specific equations, is understanding how we apply race-specific equations and whether or not absolute thresholds or cutoffs make sense for qualifying for therapies or employment or disability.