Research Questions Commonly used race-based formula to define lung disease


New results from a long-term epidemiological study reveal that one of the oldest race-based diagnostic formulas in medicine is no better than a race-neutral equation, suggesting that the formula used to diagnose lung disease should be changed.

The study, led by researchers at Columbia University Vagelos College of Physicians and Surgeons, was published Dec. 16 in the American Journal of Respiratory and Critical Care Medicine.

The race-based formula is used to determine the severity of COPD (chronic obstructive pulmonary disease) and to diagnose other lung diseases. Although it is based on an old methodology, it is still recommended for use in the United States and worldwide.

Because the formula includes racial adjustments in defining normal lung function, black people may be less likely to be treated with medications for COPD or diagnosed with other serious lung conditions compared to white people who have the same test results on a spirometer, an instrument that measures the air capacity of the lungs. (In an accompanying article in the same issue, UCSF researchers found that fewer black patients with COPD and other lung diseases are correctly diagnosed because of the race-based formula).

History of the formula

The history of the formula is almost 200 years old.

“The current approach to defining normal lung function dates back to the 1840s, when the inventor of the spirometer, John Hutchinson, used the spirometer to measure lung capacity in approximately 4,000 people and used a cross-sectional approach to determine which values disease and which values ​​were normal,” said the study’s senior author, R. Graham Barr, MD, DrPH, the Hamilton Southworth Professor of Medicine at Columbia University Vagelos College of Physicians and Surgeons and chief of the Department of General Medicine. Columbia University Irving Medical Center Barr is also a professor of epidemiology at Columbia’s Mailman School of Public Health.

A similar cross-sectional study in the United States, conducted right after the Civil War, found differences in lung capacity between “healthy” black and white military personnel. Pro-slavery doctors interpreted these observations as a biological difference, which they used to advocate for slavery. (Read more about spirometry and race in the New York Times’ 1619 Project). This cross-cutting approach to defining normal lung function persists to this day in the guidelines recommending the inclusion of terms for race in the currently used diagnostic formula.

But cross-sectional studies only look at participants at a single point in time, rather than following the same people over time, which is a more modern and relevant method of determining which measurements fall within the healthy range and which may signify disease. . Barr says the cross-sectional study “was a fine and innovative approach in the 1840s, but most fields have moved on as longitudinal data became available.” For example, the thresholds used to diagnose type 2 diabetes, hyperlipidemia, and hypertension are based on long-term prospective cohort studies or clinical trials.

New Approach

Since the early 2000s, Barr and a team of collaborators from multiple institutions have followed a group of several thousand patients and collected a wealth of data on spirometry measurements and the long-term development of lung disease. With that data, they were able to compare the race-based formula with a race-neutral formula to see which could better predict lung problems.

The results were unequivocal: Stratifying the risk of lung disease in patients based on race was no better than that obtained with the race-neutral spirometry formula and in some cases the race-neutral spirometry formula yielded better predictions.

“This kind of research is important to evaluate the algorithms and diagnostics that the medical community has used in the past to diagnose and treat disease,” said Lisa Postow, PhD, the COPD/Environmental Program Director at the National Heart, Lung. , and Blood Institute at the NIH. “Accurate algorithms are essential for accurate diagnosis and appropriate treatment.”

Changing formulas can be simple and easy. “There is a published race-neutral equation, which we used as a comparison in this article,” says first author Arielle Elmaleh-Sachs, MD, a postdoctoral clinical researcher in the Division of General Medicine at Columbia. “The race-neutral equation is available to everyone, and it would be relatively easy to move clinical practice to make the change.”



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