Race-specific lung function equations misclassify patients with ILD eligible for care
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Key takeaways:
- Use of race-specific lung function equations resulted in misclassification of patients with ILD eligible for different types of care.
- Misclassification occurred in white, Black and Hispanic/Latino patients.
Race-specific vs. race-neutral lung function equations misclassified more patients with pulmonary fibrosis eligible for trials, therapy and transplantation referral, according to results published in Annals of the American Thoracic Society.
“These findings have significant implications for everyday clinicians,” Ayodeji Adegunsoye, MD, PhD, director of the interstitial lung disease program at The University of Chicago, told Healio.
The transition to race-neutral pulmonary function testing equations can affect clinical decisions with real-world implications on patients' lives, so assessment practices need to be critically evaluated and updated to ensure they are accurate and equitable, he continued.
“As clinicians, we can better tailor our care strategies to meet the patient's individual needs, ultimately improving patient outcomes in our everyday practice,” Adegunsoye said.
In this study, Adegunsoye and colleagues analyzed 1,531 patients with interstitial lung disease from the Pulmonary Fibrosis Foundation patient registry to determine the impact of race-specific vs. race-neutral and race-agnostic equations for calculating percent-predicted FVC on eligibility for ILD clinical trials, antifibrotic therapy and lung transplantation referral.
Researchers used Hankinson’s 1999 criteria for the race-specific equation, Global Lung Function Initiative (GLI)-2022 or GLI-Global criteria for the race-neutral equation and GLI-2012 criteria for the race-agnostic equation.
Of the total cohort, most patients identified as white (n = 1,381; mean age, 68.9 years; 66.04% men), with fewer patients identifying as Black (n = 78; mean age, 57.62 years; 32.05% men) or Hispanic/Latino (n = 72; mean age, 65.18 years; 59.72% men).
To be eligible for an ILD clinical trial, a patient’s percent-predicted FVC had to be over 45% and less than 90%. Use of the race-specific vs. the race-neutral equation to calculate this value resulted in misclassification of 22% of Black patients, 14% of Hispanic/Latino patients and 12% of white patients.
Use of the race-specific vs. race-neutral equation to find percent-predicted FVC also led to misclassification of patients from each racial group eligible for antifibrotic therapy (percent-predicted FVC between > 55% and < 82%), including 21% of Black patients, 19% of white patients and 17% of Hispanic/Latino patients.
“The finding that race-neutral equations could increase the eligibility of Black patients for certain treatments and clinical trials by addressing biases in race-specific equations is noteworthy,” Adegunsoye told Healio.
The group with the highest proportion of patients misclassified for lung transplantation referral (percent-predicted FVC < 70%) using the race-specific equation compared with the race-neutral equation was the Hispanic/Latino cohort (14%), followed by the white cohort (12%) and the Black cohort (6%).
Misclassification was further noted with use of the race-specific equation vs. the race-agnostic equation for ILD clinical trial eligibility (15% of Black patients; 15% of Hispanic/Latino patients; 18% of white patients), antifibrotic therapy eligibility (13% of Black patients, 28% of Hispanic/Latino patients; 26% of white patients) and lung transplantation referral eligibility (4% of Black patients; 18% of Hispanic/Latino patients; 18% of white patients).
“Perhaps the most surprising element was the continued broader implication of these findings for using race in clinical decision-making processes such as medical diagnostics and treatment guidelines,” Adegunsoye said. “It highlights the need for a critical reassessment of practices that may inadvertently contribute to health inequities, making it a significant issue for population health.”
Adegunsoye went on to say that achieving equity will be the focus of further research in this area.
“Informed by these critical insights, I envisage that future studies will increasingly prioritize inclusivity and equity, embracing more nuanced measures of lung function while carefully considering the disease’s impact on the broader population,” Adegunsoye told Healio.
“To offer deeper insights into disease mechanisms and treatment responses that accurately reflect the diversity of patient populations, I expect that such future research will integrate a wider array of genetic, environmental and socioeconomic factors, paving the way for personalized medicine that is both effective and equitable,” he continued. “Hopefully, this would catalyze the development of universally applicable diagnostic and treatment guidelines that improve outcomes across all populations.”