A long-term epidemiological study reveals that one of the oldest, racially-based diagnostic formulas in medicine – used globally to define the severity of COPD (chronic obstructive pulmonary disease) – is no better than a race-neutral equation, and should be changed.
The study, led by researchers at Columbia University Vagelos College of Physicians and Surgeons, was published in the American Journal of Respiratory and Critical Care Medicine.
The race-based formula is used to define the severity of COPD (chronic obstructive pulmonary disease) and diagnose other lung diseases. Though it is based on old methodology, it is still recommended for use in the United States and globally.
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 disorders compared with white people with the same test results on a spirometer, an instrument that measures the lungs’ air capacity. (In an accompanying paper in the same issue, UCSF researchers found that fewer black patients with COPD and other lung diseases are diagnosed correctly because of the race-based formula).
History of the formula
The history of the formula is nearly 200 years old. “The current approach to defining normal lung function goes back to the 1840s, when the inventor of the spirometer, John Hutchinson, used the spirometer to measure lung capacity in about 4,000 people and used a cross-sectional approach to define which values indicated disease and which values were normal,” said the study’s senior author, Dr R. Graham Barr, Hamilton Southworth professor of medicine at Columbia University Vagelos College of Physicians and Surgeons and chief of the Division of General Medicine at Columbia University Irving Medical Center. Barr also is professor of epidemiology at Columbia’s Mailman School of Public Health.
A similar cross-sectional study in the United States performed right after the Civil War found differences in lung capacity between “healthy” black and white military personnel. Pro-slavery physicians interpreted these observations as a biologic difference, which they used to argue in favour of slavery.
This cross-sectional approach to defining normal lung function persists to this day in the guidelines that recommend the inclusion of terms for race in the currently used diagnostic formula.
But cross-sectional studies look only at participants at a single point in time, instead of following the same people over time, which is a more modern and relevant method to determine which measurements fall in the healthy range and which may signify disease. Barr says that 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, hyperlipidaemia, and hypertension are based upon long-term prospective cohort studies or clinical trials.
Since the early 2000s, Barr and a multi-institution team of collaborators have been following a group of several thousand patients, and amassed a trove of data on spirometry measurements and long-term development of lung disease. That data allowed them to compare the race-based formula with a race-neutral one to see which was better at predicting lung problems.
The results were unambiguous: stratifying patients’ risk of lung disease based on race was no better than those obtained with the race-neutral spirometry formula and, in some instances, the race-neutral spirometry formula yielded better predictions.
“This type of research is important to evaluate the algorithms and diagnostics that the medical community has historically used to diagnose and treat disease,” said Lisa Postow, PhD, director of the COPD/environment programme at the National Heart, Lung, and Blood Institute at the National Institutes of Health (NIH). “Accurate algorithms are essential for accurate diagnosis and appropriate treatment.”
Changing formulas could be straightforward and easy. “There is a published race-neutral equation, which we used as a comparison in this paper,” said first author Dr Arielle Elmaleh-Sachs, postdoctoral clinical fellow 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.”
Reconsidering the Utility of Race-Specific Lung Function Prediction Equations
Aaron Baugh, Stephen Shiboski, Nadia Hansel, Victor Ortega, Igor Barjakteravic, R. Graham Barr, Russell Bowler, Alejandro Comellas, Christopher Cooper, David Couper, Gerard Criner, Jeffrey Curtis, Mark Dransfield, Chinedu Ejike, Meilan Han, Eric Hoffman, Jamuna Krishnan, Jerry Krishnan, David Mannino, Robert Paine, Trisha Parekh, Stephen Peters, Nirupama Putcha, Stephen Rennard, Neeta Thakur, Prescott Woodruff.
Published in the American Journal of Respiratory and Critical Care Medicine on 15 December 2021
Rationale: African Americans have worse outcomes in chronic obstructive pulmonary disease (COPD).
Objective: Assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognise pathological decrements and considering them normal. Methods: In a cohort with and at-risk-for COPD, we assessed whether lung function prediction equations applied in a race-specific versus universal manner better modelled the relationship between forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and other COPD outcomes, including COPD Assessment Test (CAT), St George’s Respiratory Questionnaire (SGRQ), CT percent emphysema, airway wall thickness (Pi10) and six-minute walk test (6MWT).
We related these outcomes to differences in FEV1 using multiple linear regression, and compared predictive performance between fitted models using root mean squared error and Alpaydin’s paired F test.
Measurements and Main Results: Using race-specific equations, African Americans were calculated to have better lung function than non-Hispanic whites ([FEV1] 76.2% vs. 71.3% predicted, P=0.02). Using universally-applied equations, African Americans were calculated to have worse lung function. Using NHW-H, FEV1 was 61.4%% versus 71.3%; (P<0.001). Using GLI-O, FEV1 was 69.4% versus 77.4% (P<0.001). Prediction errors from linear regression were less for universally-applied equations compared with race-specific equations when comparing FEV1 %predicted with CAT (P<0.01), SGRQ (P<0.01) and Pi10 (P<0.01). While African Americans had greater adversity (P<0.001), less adversity was only associated with better FEV1 in non-Hispanic white participants (P-for-interaction=0.041).
Conclusions: Race-specific equations may under-estimate COPD severity in African Americans.
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