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The European Respiratory Society (ERS) and American Thoracic Society (ATS) just published an update to their guidelines on lung function interpretation (Stanojevic S, et al. Eur Respir J. 2022; 60: 2101499). As with any update, the document builds on past work and integrates new advances the field has seen since 2005.
The current iteration comes at a time when academics, clinicians, and epidemiologists are re-analyzing what we think we know about the complex ways race and ethnicity intersect with the practice of medicine. Several experts on lung function testing, many if not most of whom are authors on the ERS/ATS guideline, have written letters or published reviews commenting on the way accounting for race or ethnicity affects lung function interpretation.
Race/ethnicity and lung function was also the topic of an excellent session at the recent CHEST 2022 Annual Meeting in Nashville, Tennessee. Here, we’ll provide a brief review and direct the reader to relevant sources for a more detailed analysis.
Spirometry is an integral part of the diagnosis and management of a wide range of pulmonary conditions. Dr. Aaron Baugh from the University of California San Francisco (UCSF) lectured on the spirometer’s history at CHEST 2022 and detailed its interactions with race over the past 2 centuries. Other authors have chronicled this history, as well (Braun L, et al. Can J Respir Ther. 2015;51[4]:99-101). The short version is that since the British surgeon John Hutchinson created the first spirometer in 1846, race has been a part of the discussion of lung function interpretation.
In 2022, we know far more about the factors that determine lung function than we did in the 19th century. Age, height, and sex assigned at birth all explain a high percentage of the variability seen in FEV1 and FVC. When modeled, race also explains a portion of the variability, and the NHANES III investigators found its inclusion in regression equations, along with age, height, and sex, improved their precision. Case closed, right? Modern medicine is defined by phenotyping, precision, and individualized care, so why shouldn’t race be a part of lung function interpretation?
Well, it’s complicated. As clinicians and academics, we must analyze the root cause of differences in health outcomes between racial groups.
Publications on pulse oximetry (Gottlieb ER, et al. JAMA Intern Med. 2022; 182:849-858) and glomerular filtration rate (Williams WW, et al. N Engl J Med. 2021;385:1804-1806) have revealed some of the ways our use of instruments and equations may exacerbate or perpetuate current disparities. Even small differences in a measure like pulse oximetry could have a profound impact on clinical decisions at the individual and population levels.
The 2022 ERS/ATS lung function interpretation guidelines have abandoned the use of NHANES III as a reference set. They now recommend the equations developed by the Global Lung Initiative (GLI) for referencing to normal for spirometry, diffusion capacity, and lung volumes. For spirometry the GLI was able to integrate data from countries around the world. This allowed ethnicity to be included in their regression equations and, similar to NHANES III, they found ethnicity improved the precision of their equations. They also published an equation that did not account for country of origin that could be applied to individuals of any race/ethnicity (Quanjer PH, et al. Eur Respir J. 2014;43:505-512). This allowed for applying the GLI equations to external data sets with or without ethnicity included as a co-variate.
Given well-established discrepancies in spirometry, it should come as no surprise that applying the race/ethnicity-neutral GLI equations to non-White populations increases the percentage of patients with pulmonary defects (Moffett AT, et al. Am J Respir Crit Care Med. 2021; A1030). Other data suggest that elimination of race/ethnicity as a co-variate improves the association between percent predicted lung function and important outcomes like mortality (McCormack MC, et al. Am J Respir Crit Care Med. 2022;205:723-724). The first analysis implies that by adjusting for race/ethnicity we may be missing abnormalities, and the second suggests accuracy for outcomes is lost. So case closed, right? Let’s abandon race/ethnicity as a co- variate for our spirometry reference equations.
Perhaps, but a few caveats are in order. It’s important to note that doing so would result in a dramatic increase in abnormal findings in otherwise healthy and asymptomatic non-White individuals. This could negatively affect eligibility for employment and military service (Townsend MC, et al. Am J Respir Crit Care Med. 2022;789-790). We’ve also yet to fully explain the factors driving differences in lung function between races. If socioeconomic factors explained the entirety of the difference, it would be easier to argue for elimination of using race/ethnicity in our equations. Currently, the etiology is thought to be multifactorial and is yet to be fully explained (Braun L, et al. Eur Respir J. 2013;41:1362-1370).
The more we look for institutional racism, the more we will find it. As we realize that attaining health and wellness is more difficult for the disenfranchised, we need to ensure our current practices are part of the solution.
The ERS/ATS guidelines suggest eliminating fixed correction factors for race but do not require elimination of race/ethnicity as a co-variate in the equations selected for use. This seems very reasonable given what we know now. As pulmonary medicine academics and researchers, we need to continue to study the impact integrating race/ethnicity has on precision, accuracy, and clinical outcomes. As pulmonary medicine clinicians, we need to be aware of the reference equations being used in our lab, understand how inclusion of race/ethnicity affects findings, and act accordingly, depending on the clinical situation.
Dr. Ghionni is a Pulmonary/Critical Care Fellow, and Dr. Woods is Program Director – PCCM Fellowship and Associate Program Director – IM Residency, Medstar Washington Hospital Center; Dr. Woods is Associate Professor of Medicine, Georgetown University School of Medicine, Washington, DC.
The European Respiratory Society (ERS) and American Thoracic Society (ATS) just published an update to their guidelines on lung function interpretation (Stanojevic S, et al. Eur Respir J. 2022; 60: 2101499). As with any update, the document builds on past work and integrates new advances the field has seen since 2005.
The current iteration comes at a time when academics, clinicians, and epidemiologists are re-analyzing what we think we know about the complex ways race and ethnicity intersect with the practice of medicine. Several experts on lung function testing, many if not most of whom are authors on the ERS/ATS guideline, have written letters or published reviews commenting on the way accounting for race or ethnicity affects lung function interpretation.
Race/ethnicity and lung function was also the topic of an excellent session at the recent CHEST 2022 Annual Meeting in Nashville, Tennessee. Here, we’ll provide a brief review and direct the reader to relevant sources for a more detailed analysis.
Spirometry is an integral part of the diagnosis and management of a wide range of pulmonary conditions. Dr. Aaron Baugh from the University of California San Francisco (UCSF) lectured on the spirometer’s history at CHEST 2022 and detailed its interactions with race over the past 2 centuries. Other authors have chronicled this history, as well (Braun L, et al. Can J Respir Ther. 2015;51[4]:99-101). The short version is that since the British surgeon John Hutchinson created the first spirometer in 1846, race has been a part of the discussion of lung function interpretation.
In 2022, we know far more about the factors that determine lung function than we did in the 19th century. Age, height, and sex assigned at birth all explain a high percentage of the variability seen in FEV1 and FVC. When modeled, race also explains a portion of the variability, and the NHANES III investigators found its inclusion in regression equations, along with age, height, and sex, improved their precision. Case closed, right? Modern medicine is defined by phenotyping, precision, and individualized care, so why shouldn’t race be a part of lung function interpretation?
Well, it’s complicated. As clinicians and academics, we must analyze the root cause of differences in health outcomes between racial groups.
Publications on pulse oximetry (Gottlieb ER, et al. JAMA Intern Med. 2022; 182:849-858) and glomerular filtration rate (Williams WW, et al. N Engl J Med. 2021;385:1804-1806) have revealed some of the ways our use of instruments and equations may exacerbate or perpetuate current disparities. Even small differences in a measure like pulse oximetry could have a profound impact on clinical decisions at the individual and population levels.
The 2022 ERS/ATS lung function interpretation guidelines have abandoned the use of NHANES III as a reference set. They now recommend the equations developed by the Global Lung Initiative (GLI) for referencing to normal for spirometry, diffusion capacity, and lung volumes. For spirometry the GLI was able to integrate data from countries around the world. This allowed ethnicity to be included in their regression equations and, similar to NHANES III, they found ethnicity improved the precision of their equations. They also published an equation that did not account for country of origin that could be applied to individuals of any race/ethnicity (Quanjer PH, et al. Eur Respir J. 2014;43:505-512). This allowed for applying the GLI equations to external data sets with or without ethnicity included as a co-variate.
Given well-established discrepancies in spirometry, it should come as no surprise that applying the race/ethnicity-neutral GLI equations to non-White populations increases the percentage of patients with pulmonary defects (Moffett AT, et al. Am J Respir Crit Care Med. 2021; A1030). Other data suggest that elimination of race/ethnicity as a co-variate improves the association between percent predicted lung function and important outcomes like mortality (McCormack MC, et al. Am J Respir Crit Care Med. 2022;205:723-724). The first analysis implies that by adjusting for race/ethnicity we may be missing abnormalities, and the second suggests accuracy for outcomes is lost. So case closed, right? Let’s abandon race/ethnicity as a co- variate for our spirometry reference equations.
Perhaps, but a few caveats are in order. It’s important to note that doing so would result in a dramatic increase in abnormal findings in otherwise healthy and asymptomatic non-White individuals. This could negatively affect eligibility for employment and military service (Townsend MC, et al. Am J Respir Crit Care Med. 2022;789-790). We’ve also yet to fully explain the factors driving differences in lung function between races. If socioeconomic factors explained the entirety of the difference, it would be easier to argue for elimination of using race/ethnicity in our equations. Currently, the etiology is thought to be multifactorial and is yet to be fully explained (Braun L, et al. Eur Respir J. 2013;41:1362-1370).
The more we look for institutional racism, the more we will find it. As we realize that attaining health and wellness is more difficult for the disenfranchised, we need to ensure our current practices are part of the solution.
The ERS/ATS guidelines suggest eliminating fixed correction factors for race but do not require elimination of race/ethnicity as a co-variate in the equations selected for use. This seems very reasonable given what we know now. As pulmonary medicine academics and researchers, we need to continue to study the impact integrating race/ethnicity has on precision, accuracy, and clinical outcomes. As pulmonary medicine clinicians, we need to be aware of the reference equations being used in our lab, understand how inclusion of race/ethnicity affects findings, and act accordingly, depending on the clinical situation.
Dr. Ghionni is a Pulmonary/Critical Care Fellow, and Dr. Woods is Program Director – PCCM Fellowship and Associate Program Director – IM Residency, Medstar Washington Hospital Center; Dr. Woods is Associate Professor of Medicine, Georgetown University School of Medicine, Washington, DC.
The European Respiratory Society (ERS) and American Thoracic Society (ATS) just published an update to their guidelines on lung function interpretation (Stanojevic S, et al. Eur Respir J. 2022; 60: 2101499). As with any update, the document builds on past work and integrates new advances the field has seen since 2005.
The current iteration comes at a time when academics, clinicians, and epidemiologists are re-analyzing what we think we know about the complex ways race and ethnicity intersect with the practice of medicine. Several experts on lung function testing, many if not most of whom are authors on the ERS/ATS guideline, have written letters or published reviews commenting on the way accounting for race or ethnicity affects lung function interpretation.
Race/ethnicity and lung function was also the topic of an excellent session at the recent CHEST 2022 Annual Meeting in Nashville, Tennessee. Here, we’ll provide a brief review and direct the reader to relevant sources for a more detailed analysis.
Spirometry is an integral part of the diagnosis and management of a wide range of pulmonary conditions. Dr. Aaron Baugh from the University of California San Francisco (UCSF) lectured on the spirometer’s history at CHEST 2022 and detailed its interactions with race over the past 2 centuries. Other authors have chronicled this history, as well (Braun L, et al. Can J Respir Ther. 2015;51[4]:99-101). The short version is that since the British surgeon John Hutchinson created the first spirometer in 1846, race has been a part of the discussion of lung function interpretation.
In 2022, we know far more about the factors that determine lung function than we did in the 19th century. Age, height, and sex assigned at birth all explain a high percentage of the variability seen in FEV1 and FVC. When modeled, race also explains a portion of the variability, and the NHANES III investigators found its inclusion in regression equations, along with age, height, and sex, improved their precision. Case closed, right? Modern medicine is defined by phenotyping, precision, and individualized care, so why shouldn’t race be a part of lung function interpretation?
Well, it’s complicated. As clinicians and academics, we must analyze the root cause of differences in health outcomes between racial groups.
Publications on pulse oximetry (Gottlieb ER, et al. JAMA Intern Med. 2022; 182:849-858) and glomerular filtration rate (Williams WW, et al. N Engl J Med. 2021;385:1804-1806) have revealed some of the ways our use of instruments and equations may exacerbate or perpetuate current disparities. Even small differences in a measure like pulse oximetry could have a profound impact on clinical decisions at the individual and population levels.
The 2022 ERS/ATS lung function interpretation guidelines have abandoned the use of NHANES III as a reference set. They now recommend the equations developed by the Global Lung Initiative (GLI) for referencing to normal for spirometry, diffusion capacity, and lung volumes. For spirometry the GLI was able to integrate data from countries around the world. This allowed ethnicity to be included in their regression equations and, similar to NHANES III, they found ethnicity improved the precision of their equations. They also published an equation that did not account for country of origin that could be applied to individuals of any race/ethnicity (Quanjer PH, et al. Eur Respir J. 2014;43:505-512). This allowed for applying the GLI equations to external data sets with or without ethnicity included as a co-variate.
Given well-established discrepancies in spirometry, it should come as no surprise that applying the race/ethnicity-neutral GLI equations to non-White populations increases the percentage of patients with pulmonary defects (Moffett AT, et al. Am J Respir Crit Care Med. 2021; A1030). Other data suggest that elimination of race/ethnicity as a co-variate improves the association between percent predicted lung function and important outcomes like mortality (McCormack MC, et al. Am J Respir Crit Care Med. 2022;205:723-724). The first analysis implies that by adjusting for race/ethnicity we may be missing abnormalities, and the second suggests accuracy for outcomes is lost. So case closed, right? Let’s abandon race/ethnicity as a co- variate for our spirometry reference equations.
Perhaps, but a few caveats are in order. It’s important to note that doing so would result in a dramatic increase in abnormal findings in otherwise healthy and asymptomatic non-White individuals. This could negatively affect eligibility for employment and military service (Townsend MC, et al. Am J Respir Crit Care Med. 2022;789-790). We’ve also yet to fully explain the factors driving differences in lung function between races. If socioeconomic factors explained the entirety of the difference, it would be easier to argue for elimination of using race/ethnicity in our equations. Currently, the etiology is thought to be multifactorial and is yet to be fully explained (Braun L, et al. Eur Respir J. 2013;41:1362-1370).
The more we look for institutional racism, the more we will find it. As we realize that attaining health and wellness is more difficult for the disenfranchised, we need to ensure our current practices are part of the solution.
The ERS/ATS guidelines suggest eliminating fixed correction factors for race but do not require elimination of race/ethnicity as a co-variate in the equations selected for use. This seems very reasonable given what we know now. As pulmonary medicine academics and researchers, we need to continue to study the impact integrating race/ethnicity has on precision, accuracy, and clinical outcomes. As pulmonary medicine clinicians, we need to be aware of the reference equations being used in our lab, understand how inclusion of race/ethnicity affects findings, and act accordingly, depending on the clinical situation.
Dr. Ghionni is a Pulmonary/Critical Care Fellow, and Dr. Woods is Program Director – PCCM Fellowship and Associate Program Director – IM Residency, Medstar Washington Hospital Center; Dr. Woods is Associate Professor of Medicine, Georgetown University School of Medicine, Washington, DC.