Study: Assessment for COPD Severity Should Be Race-neutral

Yedida Y Bogachkov PhD avatar

by Yedida Y Bogachkov PhD |

Share this article:

Share article via email
pulmonary rehabilitation | COPD News Today | illustration of doctor consulting with patient

The method used for assessing the severity of chronic obstructive pulmonary disease (COPD) and diagnosing other lung diseases should be made race-neutral, as opposed to the current one that includes racial adjustments in defining normal lung function, according to a recent study.

The study found no differences in event or death predictions when using equations that included race/ethnicity terms, as opposed to a race-neutral equation.

The study, “Race/Ethnicity, Spirometry Reference Equations and Prediction of Incident Clinical Events: The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study”, was published in the American Journal of Respiratory and Critical Care Medicine.

COPD is a chronic inflammatory disease, in which the airways become blocked, causing cough with mucus, wheezing, and shortness of breath.

Recommended Reading
heart dysfunction | COPD News Today | illustration of woman walking

Blowing Cool Air on Face Can Ease Breathlessness While Walking

Normal values for forced expiratory volume (FEV1) and forced vital capacity (FVC), two lung function parameters, are currently calculated using equations that include terms for race or ethnicity. According to researchers, this may reinforce health disparities between ethnicities and does not seem to have a clear clinical benefit.

FEV1 is the total amount of air a patient can forcibly exhale in one second, while FVC is the total amount of air exhaled during the FEV test.

Recent research from the University of California San Francisco found evidence that COPD severity may be underestimated in Black patients due to the use of the race-based equations.

The current method of assessing COPD severity is based on data from cross-sectional studies.

These studies, which focus on a particular moment in time, were considered “a fine and innovative approach in the 1840s, but most fields have moved on as longitudinal data became available,” R. Graham Barr, MD, the study’s senior author, said in a university press release.

Barr, who also is a professor of medicine at Columbia University Vagelos College of Physicians and Surgeons, noted the thresholds used for diagnosing type 2 diabetes and high blood pressure are all currently based on long-term prospective cohort studies, which follow a group of patients over time, or clinical trials, rather than cross-sectional studies.

“This type of research is important to evaluate the algorithms and diagnostics that the medical community has historically used to diagnose and treat disease. Accurate algorithms are essential for accurate diagnosis and appropriate treatment,” said Lisa Postow, PhD, program director of the COPD/environment program at the NIH’s National Heart, Lung, and Blood Institute.

In this current long-term study, researchers analyzed data from more than 3,000 adult participants gathered from 2004 to 2006 and followed through 2019. Most participants were white (36%), followed by Black (25%), Hispanic (23%), and Asian (17%).

Over a median of 11.6 years, there were 181 chronic lung respiratory disease-related events and 547 deaths.

Results indicated that FEV1 or FVC values calculated via race/ethnic-based equations did not improve predictions of events or deaths, relative to those predicted by race/ethnic-neutral calculations.

“There was no evidence that race/ethnic-based … equations improved the prediction of clinical events compared to race/ethnic-neutral equations. The inclusion of race/ethnicity in … equations should be reconsidered,” the researchers wrote.

“There is a published race-neutral equation, which we used as a comparison in this paper. The race-neutral equation is available to everyone, and it would be relatively easy to move clinical practice to make the change,” said Arielle Elmaleh-Sachs, MD, a postdoctoral clinical fellow in the division of general medicine at Columbia and the study’s first author.