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Chen CW, Shu CC, Han YY, Hsu SHJ, Hwang JS, Su TC. Mediated relationship between Vitamin D deficiency and reduced pulmonary function by copper in Taiwanese young adults. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 285:117034. [PMID: 39270475 DOI: 10.1016/j.ecoenv.2024.117034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 09/06/2024] [Accepted: 09/08/2024] [Indexed: 09/15/2024]
Abstract
BACKGROUND Vitamin D deficiency is prevalent worldwide and associated with worse outcomes in various lung diseases. This study examines the association between vitamin D deficiency and pulmonary function in healthy young adults. METHODS This prospective cohort study (2017-2019) explored the impact of vitamin D deficiency on pulmonary function in a community-based young adult population. Pulmonary function was assessed via spirometry, with serum 25-hydroxyvitamin D [25(OH)D] and urinary copper levels quantified. Multivariate regression was used to estimate the relationship between vitamin D levels and lung function, with mediation analysis evaluating copper's role. RESULTS The study included 1034 participants, average age 33.45 years, 41.93 % male. The median 25(OH)D level was 19.20 ng/mL (Interquartile Range: 13.48-24.90 ng/mL). Over half (54.74 %) had 25(OH)D levels below 20 ng/mL. Higher 25(OH)D levels were associated with better forced vital capacity (FVC) and forced expiratory volume in one second (FEV₁). Trends suggested subgroup differences, but these were not statistically significant, indicating a consistent effect of 25(OH)D on pulmonary function across groups. SEM analysis suggested urinary copper as a mediator between 25(OH)D levels and FVC. CONCLUSION Vitamin D deficiency is significantly associated with reduced pulmonary function in young adults in Taiwan.
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Affiliation(s)
- Ching-Way Chen
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan, ROC; Division of Cardiology, Department of Internal Medicine, National Taiwan, University Hospital Yunlin Branch, Yunlin, Taiwan, ROC
| | - Chin-Chung Shu
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan, ROC
| | - Yin-Yi Han
- Department of Anesthesiology, National Taiwan University Hospital, Taipei, Taiwan, ROC; Department of Traumatology, National Taiwan University Hospital, Taipei, Taiwan, ROC
| | - Sandy Huey-Jen Hsu
- Department of Laboratory Medicine, College of Medicine, National Taiwan University Hospital, National Taiwan University, Taipei, Taiwan, ROC
| | - Jing-Shiang Hwang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan, ROC
| | - Ta-Chen Su
- Department of Environmental and Occupational Medicine, National Taiwan University Hospital, Taipei, Taiwan, ROC; Institute of Environmental and Occupational Health Sciences, College of Public Health, National Taiwan University, Taipei, Taiwan, ROC; Division of Cardiology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan, ROC.
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Myers LC, Quint JK, Hawkins NM, Putcha N, Hamilton A, Lindenauer P, Wells JM, Witt LJ, Shah SP, Lee T, Nguyen H, Gainer C, Walkey A, Mannino DM, Bhatt SP, Barr RG, Mularski R, Dransfield M, Khan SS, Gershon AS, Divo M, Press VG. A Research Agenda to Improve Outcomes in Patients with Chronic Obstructive Pulmonary Disease and Cardiovascular Disease: An Official American Thoracic Society Research Statement. Am J Respir Crit Care Med 2024; 210:715-729. [PMID: 39133888 PMCID: PMC11418885 DOI: 10.1164/rccm.202407-1320st] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2024] Open
Abstract
Background: Individuals with chronic obstructive pulmonary disease (COPD) are often at risk for or have comorbid cardiovascular disease and are likely to die of cardiovascular-related causes. Objectives: To prioritize a list of research topics related to the diagnosis and management of patients with COPD and comorbid cardiovascular diseases (heart failure, atherosclerotic vascular disease, and atrial fibrillation) by summarizing existing evidence and using consensus-based methods. Methods: A literature search was performed. References were reviewed by committee co-chairs. An international, multidisciplinary committee, including a patient advocate, met virtually to review evidence and identify research topics. A modified Delphi approach was used to prioritize topics in real time on the basis of their potential for advancing the field. Results: Gaps spanned the translational science spectrum from basic science to implementation: 1) disease mechanisms; 2) epidemiology; 3) subphenotyping; 4) diagnosis and management; 5) clinical trials; 6) care delivery; 7) medication access, adherence, and side effects; 8) risk factor mitigation; 9) cardiac and pulmonary rehabilitation; and 10) health equity. Seventeen experts participated, and quorum was achieved for all votes (>80%). Of 17 topics, ≥70% agreement was achieved for 12 topics after two rounds of voting. The range of summative Likert scores was -15 to 25. The highest priority was "Conduct pragmatic clinical trials with patient-centered outcomes that collect both pulmonary and cardiac data elements." Health equity was identified as an important topic that should be embedded within all research. Conclusions: We propose a prioritized research agenda with the purpose of stimulating high-impact research that will hopefully improve outcomes among people with COPD and cardiovascular disease.
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Spece LJ, Hee Wai T, Donovan LM, Duan KI, Plumley R, Crothers KA, Thakur N, Baugh A, Hayes S, Picazo F, Feemster LC, Au DH. The Impact of Changing Race-Specific Equations for Lung Function Tests among Veterans with Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc 2024; 21:1272-1280. [PMID: 38820262 DOI: 10.1513/annalsats.202312-1020oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 05/29/2024] [Indexed: 06/02/2024] Open
Abstract
Rationale: The American Thoracic Society recommended a single reference equation for spirometry, but the impact on patients is not known. Objectives: To estimate the effect of changing to a single reference equation among veterans with chronic obstructive pulmonary disease (COPD). Methods: A cross-sectional study was conducted including veterans aged ⩾40 to ⩽89 years with COPD and spirometry results from 21 facilities between 2010 and 2019. We collected race and ethnicity data from the electronic health record. We estimated the percentage change in the number of veterans with lung function meeting clinical thresholds used to determine eligibility for lung resection for cancer, lung volume reduction surgery (LVRS), and lung transplantation referral. We estimated the change for each level of U.S. Department of Veterans Affairs service connection and financial impact. Results: We identified 44,892 veterans (Asian, 0.5%; Black, 11.8%; White, 80.8%; and Hispanic, 1.8%). When changing to a single reference equation, Asian and Black veterans had reduced predicted lung function that could result in less surgical lung resection (4.4% and 11.1%, respectively) while increasing LVRS (1.7% and 3.8%) and lung transplantation evaluation for Black veterans (1.2%). White veterans had increased predicted lung function and could experience increased lung resection (8.1%), with less LVRS (3.3%) and lung transplantation evaluation (0.9%). Some Asian and Black veterans could experience increases in monthly disability payments (+$540.38 and +$398.38), whereas White veterans could see a decrease (-$588.79). When aggregated, Hispanic veterans experienced changes attributable to their racial identity and, because this sample was predominantly Hispanic White, had similar results to White veterans. Conclusions: Changing the reference equation could affect access to treatment and disability benefits, depending on race. If adopted, the use of discrete clinical thresholds needs to be reassessed, considering patient-centered outcomes.
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Affiliation(s)
- Laura J Spece
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
- Department of Medicine, University of Washington, Seattle, Washington
| | - Travis Hee Wai
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
| | - Lucas M Donovan
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
- Department of Medicine, University of Washington, Seattle, Washington
| | - Kevin I Duan
- Department of Medicine, University of Washington, Seattle, Washington
- Division of Respiratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada; and
| | - Robert Plumley
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
| | - Kristina A Crothers
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
- Department of Medicine, University of Washington, Seattle, Washington
| | - Neeta Thakur
- Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California
| | - Aaron Baugh
- Pulmonary, Critical Care, Allergy and Sleep Medicine, University of California, San Francisco, San Francisco, California
| | - Sophia Hayes
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
- Department of Medicine, University of Washington, Seattle, Washington
| | - Fernando Picazo
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
- Department of Medicine, University of Washington, Seattle, Washington
| | - Laura C Feemster
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
- Department of Medicine, University of Washington, Seattle, Washington
| | - David H Au
- Center of Innovation for Veteran-Centered and Value-Driven Care
- VA Puget Sound Health Care System, Seattle, Washington
- Department of Medicine, University of Washington, Seattle, Washington
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Bhavnani D, Lilley T, Rathouz PJ, Beaudenon-Huibregtse S, Davis MF, McCormack MC, Keet CA, Balcer-Whaley S, Newman M, Matsui EC. Indoor allergen exposure and its association to upper respiratory infections and pulmonary outcomes among children with asthma. J Allergy Clin Immunol 2024:S0091-6749(24)00827-3. [PMID: 39168187 DOI: 10.1016/j.jaci.2024.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 08/14/2024] [Accepted: 08/15/2024] [Indexed: 08/23/2024]
Abstract
BACKGROUND Certain environmental allergen exposures are more common in disadvantaged communities and may contribute to differences in susceptibility to upper respiratory infections (URIs). OBJECTIVES We examined associations between indoor allergens and: (1) URI; (2) URI + cold symptoms; (3) URI + cold symptoms + pulmonary eosinophilic inflammation (fraction of exhaled nitric oxide ≥20 ppb); and (4) URI + cold symptoms + reduced lung function (percent predicted forced expiratory volume in 1 second of <80%). METHODS We used data from the Environmental Control as Add-on Therapy for Childhood Asthma (ECATCh) study. Allergen concentrations were measured in air (mouse) and settled dust (mouse, cockroach, dog, and cat). URI was determined by testing nasal mucus for upper respiratory viruses. We evaluated associations between allergen concentrations and URI-associated outcomes accounting for age, sex, study month, season, health insurance, and household size. RESULTS Ninety participants (92% Black, 92% public insurance) with 192 observations were included; 52 (27%) of observations were positive for URI. A doubling in cockroach allergen concentration increased the odds of a URI with cold symptoms by 18% (odds ratio [OR] = 1.18, 95% confidence interval [CI], 0.99-1.40), the odds of a URI + cold symptoms + pulmonary eosinophilic inflammation by 31% (OR = 1.31, 95% CI, 1.10-1.57), and the odds of a URI + cold symptoms + reduced lung function by 45% (OR = 1.45, 95% CI, 1.13-1.85). Mouse allergen concentrations were positively associated with all outcomes. Associations were suggestively stronger among children sensitized to pest allergens. CONCLUSIONS Cockroach and mouse, but not dog or cat, allergen exposure may predispose children with asthma to URIs with colds and lower respiratory outcomes.
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Affiliation(s)
- Darlene Bhavnani
- Department of Population Health, Dell Medical School, University of Texas at Austin, Austin, Tex.
| | - Travis Lilley
- Department of Statistics and Data Sciences, College of Natural Sciences, University of Texas at Austin, Austin, Tex
| | - Paul J Rathouz
- Department of Population Health, Dell Medical School, University of Texas at Austin, Austin, Tex
| | | | - Meghan F Davis
- Department of Molecular and Comparative Pathobiology, Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, Md; Department of Environmental Health & Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Meredith C McCormack
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Md
| | - Corinne A Keet
- Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Susan Balcer-Whaley
- Department of Population Health, Dell Medical School, University of Texas at Austin, Austin, Tex
| | - Michelle Newman
- Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Md
| | - Elizabeth C Matsui
- Department of Population Health, Dell Medical School, University of Texas at Austin, Austin, Tex
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D Almeida S, Norajitra T, Lüth CT, Wald T, Weru V, Nolden M, Jäger PF, von Stackelberg O, Heußel CP, Weinheimer O, Biederer J, Kauczor HU, Maier-Hein K. How do deep-learning models generalize across populations? Cross-ethnicity generalization of COPD detection. Insights Imaging 2024; 15:198. [PMID: 39112910 PMCID: PMC11306482 DOI: 10.1186/s13244-024-01781-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 07/11/2024] [Indexed: 08/10/2024] Open
Abstract
OBJECTIVES To evaluate the performance and potential biases of deep-learning models in detecting chronic obstructive pulmonary disease (COPD) on chest CT scans across different ethnic groups, specifically non-Hispanic White (NHW) and African American (AA) populations. MATERIALS AND METHODS Inspiratory chest CT and clinical data from 7549 Genetic epidemiology of COPD individuals (mean age 62 years old, 56-69 interquartile range), including 5240 NHW and 2309 AA individuals, were retrospectively analyzed. Several factors influencing COPD binary classification performance on different ethnic populations were examined: (1) effects of training population: NHW-only, AA-only, balanced set (half NHW, half AA) and the entire set (NHW + AA all); (2) learning strategy: three supervised learning (SL) vs. three self-supervised learning (SSL) methods. Distribution shifts across ethnicity were further assessed for the top-performing methods. RESULTS The learning strategy significantly influenced model performance, with SSL methods achieving higher performances compared to SL methods (p < 0.001), across all training configurations. Training on balanced datasets containing NHW and AA individuals resulted in improved model performance compared to population-specific datasets. Distribution shifts were found between ethnicities for the same health status, particularly when models were trained on nearest-neighbor contrastive SSL. Training on a balanced dataset resulted in fewer distribution shifts across ethnicity and health status, highlighting its efficacy in reducing biases. CONCLUSION Our findings demonstrate that utilizing SSL methods and training on large and balanced datasets can enhance COPD detection model performance and reduce biases across diverse ethnic populations. These findings emphasize the importance of equitable AI-driven healthcare solutions for COPD diagnosis. CRITICAL RELEVANCE STATEMENT Self-supervised learning coupled with balanced datasets significantly improves COPD detection model performance, addressing biases across diverse ethnic populations and emphasizing the crucial role of equitable AI-driven healthcare solutions. KEY POINTS Self-supervised learning methods outperform supervised learning methods, showing higher AUC values (p < 0.001). Balanced datasets with non-Hispanic White and African American individuals improve model performance. Training on diverse datasets enhances COPD detection accuracy. Ethnically diverse datasets reduce bias in COPD detection models. SimCLR models mitigate biases in COPD detection across ethnicities.
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Affiliation(s)
- Silvia D Almeida
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany.
- Medical Faculty, Heidelberg University, Heidelberg, Germany.
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Medical Center, Heidelberg, Germany.
| | - Tobias Norajitra
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Carsten T Lüth
- Interactive Machine Learning Group (IML), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tassilo Wald
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Vivienn Weru
- Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marco Nolden
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Pattern Analysis and Learning Group, Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Paul F Jäger
- Interactive Machine Learning Group (IML), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oyunbileg von Stackelberg
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Diagnostic and Interventional Radiology, University Hospital, Heidelberg, Germany
| | - Claus Peter Heußel
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Diagnostic and Interventional Radiology, University Hospital, Heidelberg, Germany
- Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University Hospital, Heidelberg, Germany
| | - Oliver Weinheimer
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Diagnostic and Interventional Radiology, University Hospital, Heidelberg, Germany
| | - Jürgen Biederer
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Diagnostic and Interventional Radiology, University Hospital, Heidelberg, Germany
- University of Latvia, Faculty of Medicine, Raina Bulvaris 19, Riga, LV-1586, Latvia
- Christian-Albrechts-Universität zu Kiel, Faculty of Medicine, D-24098, Kiel, Germany
| | - Hans-Ulrich Kauczor
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- Diagnostic and Interventional Radiology, University Hospital, Heidelberg, Germany
| | - Klaus Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
- National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Medical Center, Heidelberg, Germany
- Helmholtz Imaging, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Pattern Analysis and Learning Group, Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
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Brems JH, Balasubramanian A, Raju S, Putcha N, Fawzy A, Hansel NN, Wise RA, McCormack MC. Changes in Spirometry Interpretative Strategies: Implications for Classifying COPD and Predicting Exacerbations. Chest 2024; 166:294-303. [PMID: 38537688 PMCID: PMC11317812 DOI: 10.1016/j.chest.2024.03.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/09/2024] [Accepted: 03/21/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND Recent guidelines for spirometry interpretation recommend both race-neutral reference equations and use of z score thresholds to define severity of airflow obstruction. RESEARCH QUESTION How does the transition from race-specific to race-neutral equations impact severity classifications for patients with COPD when using % predicted vs z score thresholds, and do changes in severity correspond to clinical risk? STUDY DESIGN AND METHODS This retrospective cohort study included Black and White patients with COPD and available spirometry from the Johns Hopkins Health System. Global Lung Function Initiative (GLI) 2012 (race-specific) equations and GLI Global (race-neutral) equations were used to determine FEV1 % predicted and z score values. Patients were classified as having mild, moderate, or severe disease according to % predicted or z score thresholds. Associations between a change in severity classification from race-specific to race-neutral with COPD exacerbations and all-cause hospitalizations were evaluated using logistic regression. RESULTS This cohort included 13,324 patients, of whom 9,232 patients (69.3%) were White (mean age, 65.7 years) and 4,092 patients (30.7%) were Black (mean age, 61.1 years). More Black than White patients showed a change in severity classification between approaches when using % predicted thresholds (20.2% vs 6.1%; P < .001), but not with z score thresholds (12.6% vs 12.3%; P = .68). An increased severity classification with a race-neutral approach was associated with increased risk of exacerbation when using z score thresholds (OR, 2.34; 95% CI, 1.51-3.63), but not when using % predicted thresholds (OR, 1.08; 95% CI, 0.61-1.93). A decreased severity classification with a race-neutral approach was associated with lower risk of exacerbation with both % predicted (OR, 0.49; 95% CI, 0.28-0.87) and z score (OR 0.67; 95% CI, 0.50-0.90) thresholds. INTERPRETATION The proportions of Black and White individuals reclassified were similar with z score thresholds, and changes in severity corresponded to clinical risk with z scores. These results support recent recommendations for use of race-neutral equations and z score thresholds for spirometry interpretation.
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Affiliation(s)
- J Henry Brems
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD; Berman Institute of Bioethics (J. H. B.), Johns Hopkins University, Baltimore, MD.
| | - Aparna Balasubramanian
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Sarath Raju
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Ashraf Fawzy
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Nadia N Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Robert A Wise
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Meredith C McCormack
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
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McCormack M, Kaminsky DA. Beyond Diagnostics - Removing Race from Lung-Function Test Interpretation. N Engl J Med 2024; 390:2122-2123. [PMID: 38767237 DOI: 10.1056/nejme2403770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Affiliation(s)
- Meredith McCormack
- From the Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore (M.M.); and the Division of Pulmonary Disease and Critical Care Medicine, University of Vermont Larner College of Medicine, Burlington (D.A.K.)
| | - David A Kaminsky
- From the Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore (M.M.); and the Division of Pulmonary Disease and Critical Care Medicine, University of Vermont Larner College of Medicine, Burlington (D.A.K.)
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Diao JA, He Y, Khazanchi R, Nguemeni Tiako MJ, Witonsky JI, Pierson E, Rajpurkar P, Elhawary JR, Melas-Kyriazi L, Yen A, Martin AR, Levy S, Patel CJ, Farhat M, Borrell LN, Cho MH, Silverman EK, Burchard EG, Manrai AK. Implications of Race Adjustment in Lung-Function Equations. N Engl J Med 2024; 390:2083-2097. [PMID: 38767252 PMCID: PMC11305821 DOI: 10.1056/nejmsa2311809] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
BACKGROUND Adjustment for race is discouraged in lung-function testing, but the implications of adopting race-neutral equations have not been comprehensively quantified. METHODS We obtained longitudinal data from 369,077 participants in the National Health and Nutrition Examination Survey, U.K. Biobank, the Multi-Ethnic Study of Atherosclerosis, and the Organ Procurement and Transplantation Network. Using these data, we compared the race-based 2012 Global Lung Function Initiative (GLI-2012) equations with race-neutral equations introduced in 2022 (GLI-Global). Evaluated outcomes included national projections of clinical, occupational, and financial reclassifications; individual lung-allocation scores for transplantation priority; and concordance statistics (C statistics) for clinical prediction tasks. RESULTS Among the 249 million persons in the United States between 6 and 79 years of age who are able to produce high-quality spirometric results, the use of GLI-Global equations may reclassify ventilatory impairment for 12.5 million persons, medical impairment ratings for 8.16 million, occupational eligibility for 2.28 million, grading of chronic obstructive pulmonary disease for 2.05 million, and military disability compensation for 413,000. These potential changes differed according to race; for example, classifications of nonobstructive ventilatory impairment may change dramatically, increasing 141% (95% confidence interval [CI], 113 to 169) among Black persons and decreasing 69% (95% CI, 63 to 74) among White persons. Annual disability payments may increase by more than $1 billion among Black veterans and decrease by $0.5 billion among White veterans. GLI-2012 and GLI-Global equations had similar discriminative accuracy with regard to respiratory symptoms, health care utilization, new-onset disease, death from any cause, death related to respiratory disease, and death among persons on a transplant waiting list, with differences in C statistics ranging from -0.008 to 0.011. CONCLUSIONS The use of race-based and race-neutral equations generated similarly accurate predictions of respiratory outcomes but assigned different disease classifications, occupational eligibility, and disability compensation for millions of persons, with effects diverging according to race. (Funded by the National Heart Lung and Blood Institute and the National Institute of Environmental Health Sciences.).
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Affiliation(s)
- James A Diao
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Yixuan He
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Rohan Khazanchi
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Max Jordan Nguemeni Tiako
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Jonathan I Witonsky
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Emma Pierson
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Pranav Rajpurkar
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Jennifer R Elhawary
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Luke Melas-Kyriazi
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Albert Yen
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Alicia R Martin
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Sean Levy
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Chirag J Patel
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Maha Farhat
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Luisa N Borrell
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Michael H Cho
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Edwin K Silverman
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Esteban G Burchard
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
| | - Arjun K Manrai
- From the Department of Biomedical Informatics, Harvard Medical School (J.A.D., P.R., L.M.-K., C.J.P., M.F., A.K.M.), the Computational Health Informatics Program, Boston Children's Hospital (J.A.D., A.K.M.), the Analytic and Translational Genetics Unit (Y.H., A.R.M.) and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.F.), Massachusetts General Hospital, Harvard Internal Medicine-Pediatrics Combined Residency Program, Brigham and Women's Hospital, Boston Children's Hospital, and Boston Medical Center (R.K.), the François-Xavier Bagnoud Center for Health and Human Rights, Harvard University (R.K.), the Department of Medicine (M.J.N.T.) and the Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine (M.H.C., E.K.S.), Brigham and Women's Hospital, and the Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center (S.L.), Boston, and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Y.H., A.R.M.) - all in Massachusetts; the Departments of Pediatrics (J.I.W.), Medicine (J.R.E., E.G.B.), and Bioengineering and Therapeutic Sciences (J.R.E., E.G.B.), University of California, San Francisco, San Francisco; the Department of Computer Science, Cornell University, Ithaca (E.P.), and the Department of Population Health Sciences, Weill Cornell Medical College (E.P.), and the Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (L.N.B.), New York - all in New York; the Department of Engineering Science, University of Oxford, Oxford, United Kingdom (L.M.-K.); and the Medical Scientist Training Program, University of Illinois at Chicago, Chicago (A.Y.)
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9
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Wang Z, Lu B, Wu M, Gu T, Xu M, Tang F, Zhang L, Bai S, Zhong S, Yang Q. Reduced sensitivity to thyroid hormones is associated with lung function in euthyroid individuals. Heliyon 2024; 10:e30309. [PMID: 38711649 PMCID: PMC11070858 DOI: 10.1016/j.heliyon.2024.e30309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 04/19/2024] [Accepted: 04/23/2024] [Indexed: 05/08/2024] Open
Abstract
Background The thyroid gland exhibits a subtle interconnection with the lungs. We further investigated the correlation between thyroid hormone sensitivity and lung function in euthyroid individuals. Methods Data on spirometry and mortality for participants aged 19-79 years were extracted from the NHANES database. Obstructive lung function was defined as a forced expiratory volume in 1 s to forced vital capacity ratio (FEV1/FVC) < 0.70, while restrictive lung function was considered when FEV1/FVC ≥0.70 and baseline FVC <80 % predicted. Central and peripheral sensitivities to thyroid hormones were mainly evaluated by Thyroid Feedback Quantile-based Index (TFQI) and Free Triiodothyronine/Free thyroxine (FT3/FT4) ratio. Logistic regression and subgroup analysis were used to examine potential associations between thyroid hormone sensitivity and lung function. The association between TFQI and all-cause mortality risk was also investigated. Results A total of 6539 participants were analyzed, 900 with obstructive lung function and 407 with restrictive lung function. The prevalence of impaired lung function, both obstructive and restrictive, increased with higher TFQI levels. Logistic regression analysis showed that increased TFQI and decreased FT3/FT4 levels were independent risk factors for obstructive and restrictive lung function (P < 0.05). After adjusting for the impact of lung function, TFQI (HR = 1.25, 95 % CI 1.00-1.56, P = 0.048) was an independent risk factor for all-cause mortality. Conclusion Reduced sensitivity to thyroid hormones has been linked to impaired lung function. TFQI and FT3/FT4 are potential epidemiological tools to quantify the role of central and peripheral thyroid resistance in lung function.
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Affiliation(s)
- Zhaoxiang Wang
- Department of Endocrinology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, Jiangsu, 215300, China
| | - Bing Lu
- Department of Endocrinology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, Jiangsu, 215300, China
| | - Menghuan Wu
- Department of Cardiology, Xuyi People's Hospital, Xuyi, Jiangsu, 211700, China
| | - Tian Gu
- Department of Endocrinology, Affiliated Wujin Hospital of Jiangsu University, Changzhou, Jiangsu, 213017, China
- Departmant of Endocrinology, Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, 213017, China
| | - Mengjiao Xu
- Department of Endocrinology, Affiliated Wujin Hospital of Jiangsu University, Changzhou, Jiangsu, 213017, China
- Departmant of Endocrinology, Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, 213017, China
| | - Fengyan Tang
- Department of Endocrinology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, Jiangsu, 215300, China
| | - Li Zhang
- Department of Endocrinology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, Jiangsu, 215300, China
| | - Song Bai
- Department of Cardiology, Xuyi People's Hospital, Xuyi, Jiangsu, 211700, China
| | - Shao Zhong
- Department of Endocrinology, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, Jiangsu, 215300, China
| | - Qichao Yang
- Department of Endocrinology, Affiliated Wujin Hospital of Jiangsu University, Changzhou, Jiangsu, 213017, China
- Departmant of Endocrinology, Wujin Clinical College of Xuzhou Medical University, Changzhou, Jiangsu, 213017, China
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10
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Balasubramanian A, Wise RA, Stanojevic S, Miller MR, McCormack MC. FEV 1Q: a race-neutral approach to assessing lung function. Eur Respir J 2024; 63:2301622. [PMID: 38485146 PMCID: PMC11027150 DOI: 10.1183/13993003.01622-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 02/19/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND Forced expiratory volume in 1 s quotient (FEV1Q) is a simple approach to spirometry interpretation that compares measured lung function to a lower boundary. This study evaluated how well FEV1Q predicts survival compared with current interpretation methods and whether race impacts FEV1Q. METHODS White and Black adults with complete spirometry and mortality data from the National Health and Nutrition Examination Survey (NHANES) III and the United Network for Organ Sharing (UNOS) database for lung transplant referrals were included. FEV1Q was calculated as FEV1 divided by 0.4 L for females or 0.5 L for males. Cumulative distributions of FEV1 were compared across races. Cox proportional hazards models tested mortality risk from FEV1Q adjusting for age, sex, height, smoking, income and among UNOS individuals, referral diagnosis. Harrell's C-statistics were compared between absolute FEV1, FEV1Q, FEV1/height2, FEV1 z-scores and FEV1 % predicted. Analyses were stratified by race. RESULTS Among 7182 individuals from NHANES III and 7149 from UNOS, 1907 (27%) and 991 (14%), respectively, were Black. The lower boundary FEV1 values did not differ between Black and White individuals in either population (FEV1 first percentile difference ≤0.01 L; p>0.05). Decreasing FEV1Q was associated with increasing hazard ratio (HR) for mortality (NHANES III HR 1.33 (95% CI 1.28-1.39) and UNOS HR 1.18 (95% CI 1.12-1.23)). The associations were not confounded nor modified by race. Discriminative power was highest for FEV1Q compared with alternative FEV1 approaches in both Black and White individuals. CONCLUSIONS FEV1Q is an intuitive and simple race-neutral approach to interpreting FEV1 that predicts survival better than current alternative methods.
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Affiliation(s)
- Aparna Balasubramanian
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Robert A Wise
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Sanja Stanojevic
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, NS, Canada
| | - Martin R Miller
- Institute of Applied Health Sciences, University of Birmingham, Birmingham, UK
| | - Meredith C McCormack
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
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11
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Aboelhassan A, Hurst JR. FEV 1Q: what (even) is normal lung function? Eur Respir J 2024; 63:2400354. [PMID: 38575165 DOI: 10.1183/13993003.00354-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 03/10/2024] [Indexed: 04/06/2024]
Affiliation(s)
- Arafa Aboelhassan
- Chest Department, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - John R Hurst
- UCL Respiratory, University College London, London, UK
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12
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Bhavnani D, Wilkinson M, Chambliss SE, Croce EA, Rathouz PJ, Matsui EC. Racial and Ethnic Identity and Vulnerability to Upper Respiratory Viral Infections Among US Children. J Infect Dis 2024; 229:719-727. [PMID: 37863043 PMCID: PMC10938208 DOI: 10.1093/infdis/jiad459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 09/07/2023] [Accepted: 10/17/2023] [Indexed: 10/22/2023] Open
Abstract
BACKGROUND It is unclear whether there are racial/ethnic disparities in the risk of upper respiratory viral infection acquisition and/or lower respiratory manifestations. METHODS We studied all children and children with asthma aged 6 to 17 years in the National Health and Nutrition Examination Survey (2007-2012) to evaluate (1) the association between race/ethnicity and upper respiratory infection (URI) and (2) whether race/ethnicity is a risk factor for URI-associated pulmonary eosinophilic inflammation or decreased lung function. RESULTS Children who identified as Black (adjusted odds ratio [aOR], 1.38; 95% CI, 1.10-1.75) and Mexican American (aOR, 1.50; 95% CI, 1.16-1.94) were more likely to report a URI than those who identified as White. Among those with asthma, Black children were more than twice as likely to report a URI than White children (aOR, 2.28; 95% CI, 1.31-3.95). Associations between URI and pulmonary eosinophilic inflammation or lung function did not differ by race/ethnicity. CONCLUSIONS Findings suggest that there may be racial and ethnic disparities in acquiring a URI but not in the severity of infection. Given that upper respiratory viral infection is tightly linked to asthma exacerbations in children, differences in the risk of infection among children with asthma may contribute to disparities in asthma exacerbations.
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Affiliation(s)
| | | | - Sarah E Chambliss
- Department of Statistics and Data Sciences, College of Natural Sciences, University of Texas at Austin
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13
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Zhang Y, Peng J, Liu L, Cui H, Zang D, Wu Z, Guo D, Liu X, Lu F, Yang J. Prevalence, characteristics and significant predictors for cardiovascular disease of patients with preserved ratio impaired spirometry: A 10-year prospective cohort study in China. Respir Med 2024; 222:107523. [PMID: 38171404 DOI: 10.1016/j.rmed.2023.107523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/29/2023] [Accepted: 12/30/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND AND OBJECTIVE Patients with preserved ratio impaired spirometry (PRIsm) have higher incidence rate of cardiovascular disease (CVD). However, few studies focused on PRIsm in China. We determined the prevalence and characteristics of patients with PRIsm in Chinese population. We also aimed to investigate the significant predictive factors of CVD in PRIsm patients. METHODS In total, 6994 subjects aged from 35 to 70 years old and free of CVD at baseline were categorized into normal (n = 3895), PRIsm (the ratio of forced expired volume in the first second (FEV1) to forced vital capacity (FVC) ≥0.7 and FEV1 <80 % predicted; n = 1997) and obstructive spirometry (FEV1:FVC<0.7; n = 1102). Cox proportional hazards multivariable regression was performed to investigate how baseline characteristics impact CVD incidence. RESULTS In participants with PRIsm, men had a 0.68-fold higher risk of CVD incidence than women (HR, 1.68; 95%CI, 1.09-2.59; p = 0.020). Our study showed that the rate of CVD incidence increased by 6.0 % with every year's increase in age (HR, 1.06; 95%CI, 1.04-1.09; p < 0.001). A 0.1 increase in FEV1/FVC was significantly associated with a 23.0 % decrease in CVD incidence (HR, 0.77; 95%CI, 0.61-0.97; p = 0.028). Family history of CVD greatly increased the risk of cardiovascular disease incidence (HR, 1.83; 95%CI, 1.18-2.83; p = 0.007). Higher BMI was also a significant risk factor of CVD incidence (HR, 1.06; 95%CI, 1.01-1.10; p = 0.013). CONCLUSION The prevalence of PRIsm in China was high. PRIsm subjects should be monitored carefully, especially for the older, male, those with higher BMI, lower FEV1/FVC and family history of CVD.
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Affiliation(s)
- Yerui Zhang
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Jie Peng
- Department of Geriatric Medicine, Qilu Hospital of Shandong University, Key Laboratory of Cardiovascular Proteomics of Shandong Province, Jinan, China
| | - Li Liu
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Huiliang Cui
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Dejin Zang
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Zhenguo Wu
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Dachuan Guo
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Xiaoyu Liu
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China; Department of Cardiology, People Hospital of Huantai County, Zibo, China
| | - Fanghong Lu
- Cardio-Cerebrovascular Control and Research Center, Shandong Academy of Medical Sciences, Jinan, China
| | - Jianmin Yang
- National Key Laboratory for Innovation and Transformation of Luobing Theory, China; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, China; Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China.
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14
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Balasubramanian A, Gearhart AS, Putcha N, Fawzy A, Singh A, Wise RA, Hansel NN, McCormack MC. Diffusing Capacity as a Predictor of Hospitalizations in a Clinical Cohort of Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc 2024; 21:243-250. [PMID: 37870393 PMCID: PMC10848911 DOI: 10.1513/annalsats.202301-014oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 10/19/2023] [Indexed: 10/24/2023] Open
Abstract
Rationale: Chronic obstructive pulmonary disease (COPD) hospitalizations are a major burden on patients. Diffusing capacity of the lung for carbon monoxide (DlCO) is a potential predictor that has not been studied in large cohorts. Objectives: This study used electronic health record data to evaluate whether clinically obtained DlCO predicts COPD hospitalizations. Methods: We performed time-to-event analyses of individuals with COPD and DlCO measurements from the Johns Hopkins COPD Precision Medicine Center of Excellence. Cox proportional hazard methods were used to model time from DlCO measurement to first COPD hospitalization and composite first hospitalization or death, adjusting for age, sex, race, body mass index, smoking status, forced expiratory volume in 1 second (FEV1), history of prior COPD hospitalization, and comorbidities. To identify the utility of including DlCO in risk models, area under the receiver operating curve (AUC) values were calculated for models with and without DlCO. Results were externally validated in a separate analogous cohort. Results: Of 2,793 participants, 368 (13%) had a COPD hospitalization within 3 years. In adjusted analyses, for every 10% decrease in DlCO% predicted, risk of COPD hospitalization increased by 10% (hazard ratio, 1.1; 95% confidence interval, 1.1-1.2; P < 0.001). Similar associations were observed for COPD hospitalizations or death. The model including demographics, comorbidities, FEV1, DlCO, and prior COPD hospitalizations performed well, with an AUC of 0.85 and an AUC of 0.84 in an external validation cohort. Conclusions: Diffusing capacity is a strong predictor of COPD hospitalizations in a clinical cohort of individuals with COPD, independent of airflow obstruction and prior hospitalizations. These findings support incorporation of DlCO in risk assessment of patients with COPD.
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Affiliation(s)
- Aparna Balasubramanian
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Andrew S. Gearhart
- Research and Exploratory Development Department, Applied Physics Laboratory, Johns Hopkins University, Laurel, Maryland; and
| | - Nirupama Putcha
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Ashraf Fawzy
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Anil Singh
- Division of Pulmonary, Critical Care, Allergy, and Sleep, Alleghany Health Network, Highmark Health, Pittsburgh, Pennsylvania
| | - Robert A. Wise
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Nadia N. Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Meredith C. McCormack
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
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15
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Steiling K. Evaluating the Impact of Race-Neutral Interpretation of Preoperative Pulmonary Function. Ann Am Thorac Soc 2024; 21:32-34. [PMID: 38156898 PMCID: PMC10867907 DOI: 10.1513/annalsats.202309-834ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024] Open
Affiliation(s)
- Katrina Steiling
- Division of Pulmonary, Allergy, and Critical Care Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts
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16
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Wang RJ. The Race Arithmetic of the Global Lung Function Initiative Global Reference Equations. Am J Respir Crit Care Med 2024; 209:112-113. [PMID: 37193658 PMCID: PMC10870888 DOI: 10.1164/rccm.202303-0565le] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 05/16/2023] [Indexed: 05/18/2023] Open
Affiliation(s)
- Richard J Wang
- Department of Medicine, University of California, San Francisco, San Francisco, California
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17
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Ekström M, Backman H, Mannino D. Clinical Implications of the Global Lung Function Initiative Race-Neutral Spirometry Reference Equations in Terms of Breathlessness and Mortality. Am J Respir Crit Care Med 2024; 209:104-106. [PMID: 37187171 DOI: 10.1164/rccm.202212-2229le] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023] Open
Affiliation(s)
- Magnus Ekström
- Faculty of Medicine, Department of Clinical Sciences Lund, Respiratory Medicine and Allergology, Lund University, Lund, Sweden
| | - Helena Backman
- Department of Public Health and Clinical Medicine, Section for Sustainable Health, the Obstructive Lung Disease in Northern Sweden Unit, Umeå University, Umeå, Sweden
| | - David Mannino
- Department of Medicine, University of Kentucky College of Medicine, Lexington, Kentucky; and
- COPD Foundation, Washington, District of Columbia
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18
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Regan EA, Lowe ME, Make BJ, Curtis JL, Chen Q(G, Crooks JL, Wilson C, Oates GR, Gregg RW, Baldomero AK, Bhatt SP, Diaz AA, Benos PV, O’Brien JK, Young KA, Kinney GL, Conrad DJ, Lowe KE, DeMeo DL, Non A, Cho MH, Kallet J, Foreman MG, Westney GE, Hoth K, MacIntyre NR, Hanania NA, Wolfe A, Amaza H, Han M, Beaty TH, Hansel NN, McCormack MC, Balasubramanian A, Crapo JD, Silverman EK, Casaburi R, Wise RA. Early Evidence of Chronic Obstructive Pulmonary Disease Obscured by Race-Specific Prediction Equations. Am J Respir Crit Care Med 2024; 209:59-69. [PMID: 37611073 PMCID: PMC10870894 DOI: 10.1164/rccm.202303-0444oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/23/2023] [Indexed: 08/25/2023] Open
Abstract
Rationale: The identification of early chronic obstructive pulmonary disease (COPD) is essential to appropriately counsel patients regarding smoking cessation, provide symptomatic treatment, and eventually develop disease-modifying treatments. Disease severity in COPD is defined using race-specific spirometry equations. These may disadvantage non-White individuals in diagnosis and care. Objectives: Determine the impact of race-specific equations on African American (AA) versus non-Hispanic White individuals. Methods: Cross-sectional analyses of the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) cohort were conducted, comparing non-Hispanic White (n = 6,766) and AA (n = 3,366) participants for COPD manifestations. Measurements and Main Results: Spirometric classifications using race-specific, multiethnic, and "race-reversed" prediction equations (NHANES [National Health and Nutrition Examination Survey] and Global Lung Function Initiative "Other" and "Global") were compared, as were respiratory symptoms, 6-minute-walk distance, computed tomography imaging, respiratory exacerbations, and St. George's Respiratory Questionnaire. Application of different prediction equations to the cohort resulted in different classifications by stage, with NHANES and Global Lung Function Initiative race-specific equations being minimally different, but race-reversed equations moving AA participants to more severe stages and especially between the Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 0 and preserved ratio impaired spirometry groups. Classification using the established NHANES race-specific equations demonstrated that for each of GOLD stages 1-4, AA participants were younger, had fewer pack-years and more current smoking, but had more exacerbations, shorter 6-minute-walk distance, greater dyspnea, and worse BODE (body mass index, airway obstruction, dyspnea, and exercise capacity) scores and St. George's Respiratory Questionnaire scores. Differences were greatest in GOLD stages 1 and 2. Race-reversed equations reclassified 774 AA participants (43%) from GOLD stage 0 to preserved ratio impaired spirometry. Conclusions: Race-specific equations underestimated disease severity among AA participants. These effects were particularly evident in early disease and may result in late detection of COPD.
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Affiliation(s)
| | - Melissa E. Lowe
- Biostatistics, Duke Cancer Center, Duke University Medical Center, Durham, North Carolina
| | - Barry J. Make
- Division of Pulmonary, Critical Care and Sleep Medicine
| | - Jeffrey L. Curtis
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan
- Medical Service, Veterans Affairs Medical Center, Ann Arbor, Michigan
| | | | - James L. Crooks
- Division of Biostatistics and Bioinformatics
- Department of Immunology and Genomic Medicine, and
- Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado
| | - Carla Wilson
- Research Informatics Services, National Jewish Health, Denver, Colorado
| | | | - Robert W. Gregg
- Department of Epidemiology, University of Florida, Gainesville, Florida
| | - Arianne K. Baldomero
- Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, University of Minnesota, Minneapolis, Minnesota
| | - Surya P. Bhatt
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, Alabama
| | | | | | | | - Kendra A. Young
- Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado
| | - Gregory L. Kinney
- Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado
| | | | - Katherine E. Lowe
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve School of Medicine, Cleveland, Ohio
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Amy Non
- Department of Anthropology, University of California, San Diego, La Jolla, California
| | - Michael H. Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Marilyn G. Foreman
- Division of Pulmonary and Critical Care Medicine, School of Medicine, Morehouse College, Atlanta, Georgia
| | - Gloria E. Westney
- Division of Pulmonary and Critical Care Medicine, School of Medicine, Morehouse College, Atlanta, Georgia
| | - Karin Hoth
- Department of Psychiatry and
- Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa
| | - Neil R. MacIntyre
- Division of Pulmonary, Allergy and Critical Care Medicine, Duke University, Durham, North Carolina
| | - Nicola A. Hanania
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, College of Medicine, Baylor University, Houston, Texas
| | - Amy Wolfe
- Section of Pulmonology and Critical Care, Louisiana State University Health Sciences Center, New Orleans, Louisiana
| | | | - MeiLan Han
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan
| | - Terri H. Beaty
- Department of Epidemiology, Bloomberg School of Public Health, and
| | - Nadia N. Hansel
- Division of Pulmonary and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland; and
| | - Meredith C. McCormack
- Division of Pulmonary and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland; and
| | - Aparna Balasubramanian
- Division of Pulmonary and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland; and
| | | | - Edwin K. Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Richard Casaburi
- Rehabilitation Clinical Trials Center, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, California
| | - Robert A. Wise
- Division of Pulmonary and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland; and
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19
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Okelo SO, Chesley CF, Riley I, Diaz AA, Collishaw K, Schnapp LM, Thakur N. Accelerating Action: Roadmap for the American Thoracic Society to Address Oppression and Health Inequity in Pulmonary and Critical Care Medicine. Ann Am Thorac Soc 2024; 21:17-26. [PMID: 37934586 DOI: 10.1513/annalsats.202305-412ps] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/07/2023] [Indexed: 11/08/2023] Open
Affiliation(s)
- Sande O Okelo
- Division of Pediatric Pulmonology and Sleep Medicine, Department of Pediatrics, University of California, Los Angeles, Los Angeles, California
| | - Christopher F Chesley
- Division of Pulmonary and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Isaretta Riley
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Duke University, Durham, North Carolina
| | - Alejandro A Diaz
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Lynn M Schnapp
- American Thoracic Society, New York, New York
- Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin
| | - Neeta Thakur
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California; and
- Health Equity and Diversity Committee, American Thoracic Society, New York, New York
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20
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Kanj AN, Scanlon PD, Yadav H, Smith WT, Herzog TL, Bungum A, Poliszuk D, Fick E, Lee AS, Niven AS. Application of Global Lung Function Initiative Global Spirometry Reference Equations across a Large, Multicenter Pulmonary Function Lab Population. Am J Respir Crit Care Med 2024; 209:83-90. [PMID: 37523681 PMCID: PMC10870880 DOI: 10.1164/rccm.202303-0613oc] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 07/31/2023] [Indexed: 08/02/2023] Open
Abstract
Rationale: Global Lung Function Initiative (GLI) Global spirometry reference equations were recently derived to offer a "race-neutral" interpretation option. The impact of transitioning from the race-specific GLI-2012 to the GLI Global reference equations is unknown. Objectives: Describe the direction and magnitude of changes in predicted lung function measurements in a population of diverse race and ethnicity using GLI Global in place of GLI-2012 reference equations. Methods: In this multicenter cross-sectional study using a large pulmonary function laboratory database, 109,447 spirometry tests were reanalyzed using GLI Global reference equations and compared with the existing GLI-2012 standard, stratified by self-reported race and ethnicity. Measurements and Main Results: Mean FEV1 and FVC percent predicted increased in the White and Northeast Asian groups and decreased in the Black, Southeast Asian, and mixed/other race groups. The prevalence of obstruction increased by 9.7% in the White group, and prevalences of possible restriction increased by 51.1% and 37.1% in the Black and Southeast Asian groups, respectively. Using GLI Global in a population with equal representation of all five race and ethnicity groups altered the interpretation category for 10.2% of spirometry tests. Subjects who self-identified as Black were the only group with a relative increase in the frequency of abnormal spirometry test results (32.9%). Conclusions: The use of GLI Global reference equations will significantly impact spirometry interpretation. Although GLI Global offers an innovative approach to transition from race-specific reference equations, it is important to recognize the continued need to place these data within an appropriate clinical context.
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Affiliation(s)
- Amjad N. Kanj
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - Paul D. Scanlon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - Hemang Yadav
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - William T. Smith
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - Tyler L. Herzog
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - Aaron Bungum
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - Daniel Poliszuk
- Information Technology, Mayo Clinic, Rochester, Minnesota; and
| | - Edward Fick
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
| | - Augustine S. Lee
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Jacksonville, Florida
| | - Alexander S. Niven
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and
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21
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Sheshadri A, Rajaram R, Baugh A, Castro M, Correa AM, Soto F, Daniel CR, Li L, Evans SE, Dickey BF, Vaporciyan AA, Ost DE. Association of Preoperative Lung Function with Complications after Lobectomy Using Race-Neutral and Race-Specific Normative Equations. Ann Am Thorac Soc 2024; 21:38-46. [PMID: 37796618 PMCID: PMC10867917 DOI: 10.1513/annalsats.202305-396oc] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 10/04/2023] [Indexed: 10/07/2023] Open
Abstract
Rationale: Pulmonary function testing (PFT) is performed to aid patient selection before surgical resection for non-small cell lung cancer (NSCLC). The interpretation of PFT data relies on normative equations, which vary by race, but the relative strength of association of lung function using race-specific or race-neutral normative equations with postoperative pulmonary complications is unknown. Objectives: To compare the strength of association of lung function, using race-neutral or race-specific equations, with surgical complications after lobectomy for NSCLC. Methods: We studied 3,311 patients who underwent lobectomy for NSCLC and underwent preoperative PFT from 2001 to 2021. We used Global Lung Function Initiative equations to generate race-specific and race-neutral normative equations to calculate percentage predicted forced expiratory volume in 1 second (FEV1%). The primary outcome of interest was the occurrence of postoperative pulmonary complications within 30 days of surgery. We used unadjusted and race-adjusted logistic regression models and least absolute shrinkage and selection operator analyses adjusted for relevant comorbidities to measure the association of race-specific and race-neutral FEV1% with pulmonary complications. Results: Thirty-one percent of patients who underwent surgery experienced pulmonary complications. Higher FEV1, whether measured with race-neutral (odds ratio [OR], 0.98 per 1% change in FEV1% [95% confidence interval (CI), 0.98-0.99]; P < 0.001) or race-specific (OR, 0.98 per 1% change in FEV1% [95% CI, 0.98-0.98]; P < 0.001) normative equations, was associated with fewer postoperative pulmonary complications. The area under the receiver operator curve for pulmonary complications was similar for race-adjusted race-neutral (0.60) and race-specific (0.60) models. Using least absolute shrinkage and selection operator regression, higher FEV1% was similarly associated with a lower rate of pulmonary complications in race-neutral (OR, 0.99 per 1% [95% CI, 0.98-0.99]) and race-specific (OR, 0.99 per 1%; 95% CI, 0.98-0.99) models. The marginal effect of race on pulmonary complications was attenuated in all race-specific models compared with all race-neutral models. Conclusions: The choice of race-specific or race-neutral normative PFT equations does not meaningfully affect the association of lung function with pulmonary complications after lobectomy for NSCLC, but the use of race-neutral equations unmasks additional effects of self-identified race on pulmonary complications.
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Affiliation(s)
| | | | - Aaron Baugh
- Division of Pulmonary and Critical Care Medicine, University of California, San Francisco, San Francisco, California; and
| | - Mario Castro
- Division of Pulmonary, Critical Care, and Sleep Medicine, University of Kansas Medical Center, Kansas City, Missouri
| | | | | | | | - Liang Li
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
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22
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Ekström M, Mannino D. The Race to Abandon Ethnicity in Interpreting Pulmonary Function: Further Evidence. Chest 2023; 164:1348-1349. [PMID: 38070955 DOI: 10.1016/j.chest.2023.08.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 08/24/2023] [Indexed: 12/18/2023] Open
Affiliation(s)
- Magnus Ekström
- Department of Clinical Sciences Lund, Respiratory Medicine, Allergology, and Palliative Medicine, Lund University, Lund, Sweden.
| | - David Mannino
- Department of Medicine, University of Kentucky College of Medicine, Lexington, KY; COPD Foundation, Washington, DC
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23
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Laustsen BH, Bønløkke JH, Miller MR. How to account for Inuit ancestry in lung function prediction. Int J Circumpolar Health 2023; 82:2151158. [PMID: 36471626 PMCID: PMC9731580 DOI: 10.1080/22423982.2022.2151158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Rigorous lung function prediction equations for the Inuit are lacking. We used spirometry from 351 Inuit and 29 people of other ancestry obtained during an occupational survey in Greenland to determine how to obtain valid lung function predictions for the Inuit using Global Lung Function Initiative (GLI) equations for Europeans. Standing height for the Inuit was used in the predictions as well as their height modified in line with the known differences in standing to sitting height ratio (SHR) for the Inuit. With recorded height in predicting lung function, mean±SD Inuit z-scores for FVC and FEV1 were significantly higher than predicted (0.81±1.20 and 0.53±1.36, respectively, p<0.0001) which was not true for the non-Inuit participants (-0.01±1.04 and 0.15±1.17, respectively). When using height modified for SHR the mean±SD Inuit z-scores for FVC and FEV1 were no longer significantly different from predicted (0.10±1.10 and -0.12±1.24, respectively). The mean±SD Inuit FEV1/FVC z-scores were not significantly different from the non-Inuit, being respectively -0.45±0.98 and -0.01±1.04. Modified height changed the mean±SD Inuit FEV1/FVC z-scores to -0.39±0.99. Representative lung function predictions from GLI equations can be made for Inuit by using standing height modified for the known differences in SHR between Inuit and those of European ancestry.
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Affiliation(s)
- Birgitte H Laustsen
- Department of Clinical Medicine, Danish Ramazzini Centre, Aalborg University, Aalborg, Denmark,Institute of Nursing & Health Science, Ilisimatusarfik, University of Greenland, Nuuk, Greenland
| | - Jakob H Bønløkke
- Department of Occupational and Environmental Medicine, Danish Ramazzini Centre, Aalborg University Hospital, Aalborg, Denmark
| | - Martin R Miller
- Institute of Applied Birmingham Health Sciences, University of Birmingham, Birmingham, UK,CONTACT Martin R Miller Institute of Applied Birmingham Health Sciences, University of Birmingham, BirminghamUK
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24
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Non AL, Bailey B, Bhatt SP, Casaburi R, Regan EA, Wang A, Limon A, Rabay C, Diaz AA, Baldomero AK, Kinney G, Young KA, Felts B, Hand C, Conrad DJ. Race-Specific Spirometry Equations Do Not Improve Models of Dyspnea and Quantitative Chest CT Phenotypes. Chest 2023; 164:1492-1504. [PMID: 37507005 PMCID: PMC10925545 DOI: 10.1016/j.chest.2023.07.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 07/14/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Race-specific spirometry reference equations are used globally to interpret lung function for clinical, research, and occupational purposes, but inclusion of race is under scrutiny. RESEARCH QUESTION Does including self-identified race in spirometry reference equation formation improve the ability of predicted FEV1 values to explain quantitative chest CT abnormalities, dyspnea, or Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification? STUDY DESIGN AND METHODS Using data from healthy adults who have never smoked in both the National Health and Nutrition Survey (2007-2012) and COPDGene study cohorts, race-neutral, race-free, and race-specific prediction equations were generated for FEV1. Using sensitivity/specificity, multivariable logistic regression, and random forest models, these equations were applied in a cross-sectional analysis to populations of individuals who currently smoke and individuals who formerly smoked to determine how they affected GOLD classification and the fit of models predicting quantitative chest CT phenotypes or dyspnea. RESULTS Race-specific equations showed no advantage relative to race-neutral or race-free equations in models of quantitative chest CT phenotypes or dyspnea. Race-neutral reference equations reclassified up to 19% of Black participants into more severe GOLD classes, while race-neutral/race-free equations may improve model fit for dyspnea symptoms relative to race-specific equations. INTERPRETATION Race-specific equations offered no advantage over race-neutral/race-free equations in three distinct explanatory models of dyspnea and chest CT scan abnormalities. Race-neutral/race-free reference equations may improve pulmonary disease diagnoses and treatment in populations highly vulnerable to lung disease.
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Affiliation(s)
- Amy L Non
- Department of Anthropology, University of California San Diego, La Jolla, CA
| | - Barbara Bailey
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA
| | - Surya P Bhatt
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Richard Casaburi
- Rehabilitation Clinical Trials Center, Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Elizabeth A Regan
- Division of Rheumatology and Department of Medicine, National Jewish Health, Denver, CO
| | - Angela Wang
- Department of Medicine, University of California San Diego, La Jolla, CA
| | | | - Chantal Rabay
- Department of Anthropology, University of California San Diego, La Jolla, CA
| | - Alejandro A Diaz
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Arianne K Baldomero
- Pulmonary, Allergy, Critical Care and Sleep Medicine Section, Minneapolis VA Health Care System, Minneapolis, MN
| | - Greg Kinney
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Kendra A Young
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Ben Felts
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA
| | - Carol Hand
- Advanced Mathematical Computing, San Diego, CA
| | - Douglas J Conrad
- Department of Medicine, University of California San Diego, La Jolla, CA.
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25
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Chan KC, Zhu H, Yu M, Yuen HM, Dai S, Chin HY, Choy J, Chan J, Tsoi D, Siu B, Au CT, Li AM. Applicability of the Global Lung Function Initiative prediction equations in Hong Kong Chinese children. Pediatr Pulmonol 2023; 58:3235-3245. [PMID: 37642271 DOI: 10.1002/ppul.26649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/08/2023] [Accepted: 08/12/2023] [Indexed: 08/31/2023]
Abstract
BACKGROUND AND OBJECTIVE This study aimed to assess the applicability of the Global Lung Function Initiative (GLI) prediction equations for spirometry in Hong Kong children and to develop prediction equations based on the Generalized Additive Models for Location, Scale, and Shape (GAMLSS) modeling. METHODS Healthy Chinese children and adolescents aged 6-17 years old were recruited from randomly selected schools to undergo spirometry. The measurements were transformed to z-score according to the GLI-2012 equations for South East (SE) Asians and the GLI-2022 global race-neutral equations. Prediction equations for spirometric indices were developed with GAMLSS modeling to identify predictors. RESULTS A total of 886 children (477 boys) with a mean age of 12.5 years (standard deviation [SD] 3.3 years) were included. By the GLI-2012 SE Asian equations, positive mean z-scores were observed in forced expiratory volume in 1 s (FEV1 ) (boys: 0.138 ± SD 0.828; girls: 0.206 ± 0.823) and forced vital capacity (FVC) (boys: 0.160 ± 0.930; girls: 0.310 ± 0.895) in both sexes. Negative mean z-scores were observed in FEV1 /FVC ratio (boys: -0.018 ± 0.998; girls: -0.223 ± 0.897). In contrast, negative mean z-scores in FEV1 and FVC, and positive mean z-scores in FEV1 /FVC were observed when adopting the GLI-2022 race-neutral equations. The mean z-scores were all within the range of ±0.5. By GAMLSS models, age and height were significant predictors for all four spirometric indices, while weight was an additional predictor for FVC and FEV1 . CONCLUSION Our study provided data supporting the applicability of the GLI prediction equations in Hong Kong Chinese children. The GLI-2012 equations may underestimate FEV1 and FVC, while the GLI-2022 equations may overestimate the parameters, but the differences lie within the physiological limits. By GAMLSS modeling, weight was an additional predictor for FVC and FEV1 .
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Affiliation(s)
- Kate C Chan
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Paediatric Respiratory Research, Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Hub of Paediatric Excellence, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Huichen Zhu
- Department of Statistics, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Michelle Yu
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Hoi-Man Yuen
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Siyu Dai
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Hui-Yen Chin
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jonathan Choy
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jeffrey Chan
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Dana Tsoi
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Brian Siu
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Chun T Au
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Translational Medicine, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Albert M Li
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Laboratory for Paediatric Respiratory Research, Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
- Hong Kong Hub of Paediatric Excellence, The Chinese University of Hong Kong, Hong Kong SAR, China
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26
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Connolly MJ, Donohue PA, Palli R, Khurana S, Cai X, Georas SN. Diagnostic Impact of a Race-Composite Pulmonary Function Test Results Interpretation Strategy. Chest 2023; 164:1290-1295. [PMID: 37421975 PMCID: PMC10635835 DOI: 10.1016/j.chest.2023.06.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 06/09/2023] [Accepted: 06/12/2023] [Indexed: 07/10/2023] Open
Affiliation(s)
- Margaret J Connolly
- Division of Pulmonary and Critical Care Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY.
| | - Patrick A Donohue
- Division of Pulmonary and Critical Care Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY
| | - Rohith Palli
- Internal Medicine Residency Program, University of Rochester School of Medicine and Dentistry, Rochester, NY
| | - Sandhya Khurana
- Division of Pulmonary and Critical Care Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY
| | - Xueya Cai
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY
| | - Steve N Georas
- Division of Pulmonary and Critical Care Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY
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27
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Brems JH, Balasubramanian A, Psoter KJ, Shah P, Bush EL, Merlo CA, McCormack MC. Race-Specific Interpretation of Spirometry: Impact on the Lung Allocation Score. Ann Am Thorac Soc 2023; 20:1408-1415. [PMID: 37315331 PMCID: PMC10559135 DOI: 10.1513/annalsats.202212-1004oc] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 05/26/2023] [Indexed: 06/16/2023] Open
Abstract
Rationale: Interpretation of spirometry using race-specific reference equations may contribute to health disparities via underestimation of the degree of lung function impairment in Black patients. The use of race-specific equations may differentially affect patients with severe respiratory disease via the use of percentage predicted forced vital capacity (FVCpp) when included in the lung allocation score (LAS), the primary determinant of priority for lung transplantation. Objectives: To determine the impact of a race-specific versus a race-neutral approach to spirometry interpretation on the LAS among adults listed for lung transplantation in the United States. Methods: We developed a cohort from the United Network for Organ Sharing database including all White and Black adults listed for lung transplantation between January 7, 2009, and February 18, 2015. The LAS at listing was calculated for each patient under race-specific and race-neutral approaches, using the FVCpp generated from the Global Lung Function Initiative equation corresponding to each patient's race (race-specific) or from the Global Lung Function Initiative "other" (race-neutral) equation. Differences in LAS between approaches were compared by race, with positive values indicating a higher LAS under the race-neutral approach. Results: In this cohort of 8,982 patients, 90.3% were White and 9.7% were Black. The mean FVCpp was 4.4% higher versus 3.8% lower among White versus Black patients (P < 0.001) under a race-neutral compared with a race-specific approach. Compared with White patients, Black patients had a higher mean LAS under both a race-specific (41.9 vs. 43.9; P < 0.001) and a race-neutral (41.3 vs. 44.3; P < 0.001) approach. However, the mean difference in LAS under a race-neutral approach was -0.6 versus +0.6 for White versus Black patients (P < 0.001). Differences in LAS under a race-neutral approach were most pronounced for those in group B (pulmonary vascular disease) (-0.71 vs. +0.70; P < 0.001) and group D (restrictive lung disease) (-0.78 vs. +0.68; P < 0.001). Conclusions: A race-specific approach to spirometry interpretation has potential to adversely affect the care of Black patients with advanced respiratory disease. Compared with a race-neutral approach, a race-specific approach resulted in lower LASs for Black patients and higher LASs for White patients, which may have contributed to racially biased allocation of lung transplantation. The future use of race-specific equations must be carefully considered.
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Affiliation(s)
- J. Henry Brems
- Division of Pulmonary and Critical Care Medicine, Department of Medicine
| | | | - Kevin J. Psoter
- Division of General Pediatrics, Department of Pediatrics, and
| | - Pali Shah
- Division of Pulmonary and Critical Care Medicine, Department of Medicine
| | - Errol L. Bush
- Division of Thoracic Surgery, Department of Surgery, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Christian A. Merlo
- Division of Pulmonary and Critical Care Medicine, Department of Medicine
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28
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Bhatt SP, Nakhmani A, Fortis S, Strand MJ, Silverman EK, Sciurba FC, Bodduluri S. FEV 1/FVC Severity Stages for Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2023; 208:676-684. [PMID: 37339502 PMCID: PMC10515563 DOI: 10.1164/rccm.202303-0450oc] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 06/20/2023] [Indexed: 06/22/2023] Open
Abstract
Rationale: The diagnosis of chronic obstructive pulmonary disease (COPD) is based on a low FEV1/FVC ratio, but the severity of COPD is classified using FEV1% predicted (ppFEV1). Objectives: To test a new severity classification scheme for COPD using FEV1/FVC ratio, a more robust measure of airflow obstruction than ppFEV1. Methods: In COPDGene (Genetic Epidemiology of COPD) (N = 10,132), the severity of airflow obstruction was categorized by Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 1-4 (ppFEV1 of ⩾80%, ⩾50-80%, ⩾30-50%, and <30%). A new severity classification (STaging of Airflow obstruction by Ratio; STAR) was tested in COPDGene-FEV1/FVC ⩾0.60 to <0.70, ⩾0.50 to <0.60, ⩾0.40 to <0.50, and <0.40, respectively, for stages 1-4-and applied to the combined Pittsburgh SCCOR and Emphysema COPD Research Registry for replication (N = 2,017). Measurements and Main Results: The agreements (weighted Bangdiwala B values) between GOLD and the new FEV1/FVC ratio severity stages were 0.89 in COPDGene and 0.88 in the Pittsburgh cohort. In COPDGene and the Pittsburgh cohort, compared with GOLD staging, STAR provided significant discrimination between the absence of airflow obstruction and stage 1 for all-cause mortality, respiratory quality of life, dyspnea, airway wall thickness, exacerbations, and lung function decline. No major differences were noted for emphysema, small airway disease, and 6-minute-walk distance. The STAR classification system identified a greater number of adults with stage 3/4 disease who would be eligible for lung transplantation and lung volume reduction procedure evaluations. Conclusions: The new STAR severity classification scheme provides discrimination for mortality that is similar to the GOLD classification but with a more uniform gradation of disease severity. STAR differentiates patients' symptoms, disease burden, and prognosis better than the existing scheme based on ppFEV1, and is less sensitive to race/ethnicity and other demographic characteristics.
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Affiliation(s)
- Surya P. Bhatt
- UAB Lung Imaging Lab
- Division of Pulmonary, Allergy and Critical Care Medicine, and
| | - Arie Nakhmani
- UAB Lung Imaging Lab
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, Alabama
| | - Spyridon Fortis
- Division of Pulmonary, Critical Care and Occupational Medicine, University of Iowa Hospital, Iowa City, Iowa
| | - Matthew J. Strand
- Division of Biostatistics and Bioinformatics, Office of Academic Affairs, National Jewish Health, Denver, Colorado
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts; and
| | - Frank C. Sciurba
- Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Sandeep Bodduluri
- UAB Lung Imaging Lab
- Division of Pulmonary, Allergy and Critical Care Medicine, and
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Rui W, Yuhang S, Yang L, Yue Y, Ze T, Yujie Z, Xiaochao M, Da Q, Youbin C, Tianyu L. A new method for evaluating lung volume: AI-3D reconstruction. Front Physiol 2023; 14:1217411. [PMID: 37781229 PMCID: PMC10538118 DOI: 10.3389/fphys.2023.1217411] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 08/07/2023] [Indexed: 10/03/2023] Open
Abstract
Objective: This study aims to explore the clinical application of an AI-3D reconstruction system in measuring lung volume and analyze its practical value in donor-recipient size matching in lung transplantation. Methods: The study retrospectively collected data from 75 subjects who underwent a plethysmography examination and lung CT at the First Hospital of Jilin University. General data and information related to lung function, and imaging results were collected. The correlation between actual total lung volume (aTLV), predicted total lung volume (pTLV), and artificial intelligence three-dimensional reconstruction CT lung volume (AI-3DCTVol) was analyzed for the overall, male, and female groups. The correlation coefficient and the absolute error percentage with pTLV and AI-3DCTVol were obtained. Results: In the overall, male, and female groups, there were statistical differences (p <0.05) between the pTLV formula and AI-3D reconstruction compared to the plethysmography examination value. The ICC between pTLV and aTLV for all study participants was 0.788 (95% CI: 0.515-0.893), p <0.001. Additionally, the ICC value between AI-3D reconstruction and aTLV was 0.792 (95% CI: 0.681-0.866), p <0.001. For male study participants, the ICC between pTLV and aTLV was 0.330 (95% CI: 0.032-0.617), p = 0.006. Similarly, the ICC value between AI-3D reconstruction and aTLV was 0.413 (95% CI: 0.089-0.662), p = 0.007. In the case of female research subjects, the ICC between pTLV and aTLV was 0.279 (95% CI: 0.001-0.523), p = 0.012. Further, the ICC value between AI-3D reconstruction and aTLV was 0.615 (95% CI: 0.561-0.870), p <0.001. Conclusion: The AI-3D reconstruction, as a convenient method, has significant potential for application in lung transplantation.
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Affiliation(s)
- Wang Rui
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
- School of Public Health, Jilin University, Changchun, China
| | - Shang Yuhang
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Li Yang
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Yang Yue
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Tang Ze
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Zhao Yujie
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
- Department of Critical Medicine, The First Affiliated Hospital of Jiamusi University, Jiamusi, China
| | - Ma Xiaochao
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Qin Da
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Cui Youbin
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Lu Tianyu
- Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun, China
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Baugh A, Adegunsoye A, Connolly M, Croft D, Pew K, McCormack MC, Georas SN. Towards a Race-Neutral System of Pulmonary Function Test Results Interpretation. Chest 2023; 164:727-733. [PMID: 37414097 PMCID: PMC10504596 DOI: 10.1016/j.chest.2023.06.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 05/27/2023] [Accepted: 06/03/2023] [Indexed: 07/08/2023] Open
Abstract
It has been observed widely that, on average, Black individuals in the United States have lower FVC than White individuals, which is thought to reflect a combination of genetic, environmental, and socioeconomic factors that are difficult to disentangle. Debate therefore persists even after the American Thoracic Society's 2023 guidelines recommending race-neutral pulmonary function test (PFT) result interpretation strategies. Advocates of race-based PFT results interpretation argue that it allows for more precise measurement and will minimize disease misclassification. In contrast, recent studies have shown that low lung function in Black patients has clinical consequences. Furthermore, the use of race-based algorithms in medicine in general is increasingly being questioned for its risk of perpetuating structural health care disparities. Given these concerns, we believe it is time to adopt a race-neutral approach, but note that more research is urgently needed to understand how race-neutral approaches impact PFT results interpretation, clinical decision-making, and patient outcomes. In this brief case-based discussion, we offer a few examples of how a race-neutral PFT results interpretation strategy will impact individuals from racial and ethnic minority groups at different scenarios and stages of life.
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Affiliation(s)
- Aaron Baugh
- University of California, San Francisco, San Francisco, CA.
| | | | | | - Daniel Croft
- University of Rochester Medical Center, Rochester, NY
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Burbank AJ, Atkinson CE, Espaillat AE, Schworer SA, Mills K, Rooney J, Loughlin CE, Phipatanakul W, Hernandez ML. Race-specific spirometry equations may overestimate asthma control in Black children and adolescents. Respir Res 2023; 24:203. [PMID: 37592259 PMCID: PMC10433634 DOI: 10.1186/s12931-023-02505-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/04/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND A growing body of evidence suggests that use of race terms in spirometry reference equations underestimates disease burden in Black populations, which may lead to disparities in pulmonary disease outcomes. Data on asthma-specific health consequences of using race-adjusted spirometry are lacking. METHODS We performed a secondary analysis of 163 children from two observational asthma studies to determine the frequencies of participants with ppFEV1 < 80% (consistent with uncontrolled asthma) or ppFEV1 ≥ 80% using race-specific (GLI-African American or Caucasian) vs. race-neutral (GLI-Global) spirometry and their alignment with indicators of asthma control (Asthma Control Test™, ACT). Comparisons of mean ppFEV1 values were conducted using Wilcoxon matched-pairs signed-rank tests. Two group comparisons were conducted using Wilcoxon rank-sum tests. RESULTS Data from 163 children (100 Black, 63 White) were analyzed. Mean ppFEV1 was 95.4% (SD 15.8) using race-specific spirometry and 90.4% (16.3) using race-neutral spirometry (p < 0.0001). Among 54 Black children with uncontrolled asthma (ACT ≤ 19), 20% had ppFEV1 < 80% using race-specific spirometry compared to 40% using race-neutral spirometry. In Black children with controlled asthma (ACT > 19), 87% had ppFEV1 ≥ 80% using race-specific compared to 67% using race-neutral spirometry. Children whose ppFEV1 changed to ≤ 80% with race-neutral spirometry had lower FEV1/FVC compared to those whose ppFEV1 remained ≥ 80% [0.83 (0.07) vs. 0.77 (0.05), respectively; p = 0.04], suggesting greater airway obstruction. Minimal changes in alignment of ppFEV1 with ACT score were observed for White children. CONCLUSIONS Use of race-specific reference equations in Black children may increase the risk of inappropriately labeling asthma as controlled.
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Affiliation(s)
- Allison J Burbank
- Division of Allergy & Immunology, Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
- Children's Research Institute, University of North Carolina, Chapel Hill, NC, USA.
- , 5008B Mary Ellen Jones Building 116 Manning Drive, CB #7231, Chapel Hill, NC, 27599-7231, USA.
| | - Claire E Atkinson
- Division of Allergy & Immunology, Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Andre E Espaillat
- Division of Pediatric Pulmonology, Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Stephen A Schworer
- Division of Allergy & Immunology, Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Katherine Mills
- Children's Research Institute, University of North Carolina, Chapel Hill, NC, USA
| | - Jennifer Rooney
- Boston Children's Hospital and Massachusetts General Hospital, Boston, MA, USA
| | - Ceila E Loughlin
- Division of Pediatric Pulmonology, Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Wanda Phipatanakul
- Division of Asthma, Allergy and Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michelle L Hernandez
- Division of Allergy & Immunology, Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Children's Research Institute, University of North Carolina, Chapel Hill, NC, USA
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Marciniuk DD, Becker EA, Kaminsky DA, McCormack MC, Stanojevic S, Bhakta NR, Bime C, Comondore V, Cowl CT, Dell S, Haynes J, Jaffe F, Mottram C, Sederstrom N, Townsend M, Iaccarino JM. Effect of Race and Ethnicity on Pulmonary Function Testing Interpretation: An American College of Chest Physicians (CHEST), American Association for Respiratory Care (AARC), American Thoracic Society (ATS), and Canadian Thoracic Society (CTS) Evidence Review and Research Statement. Chest 2023; 164:461-475. [PMID: 36972760 PMCID: PMC10475820 DOI: 10.1016/j.chest.2023.03.026] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 03/15/2023] [Accepted: 03/18/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Calls have been made to discontinue the routine use of race and ethnicity in medicine. Specific to respiratory medicine, the use of race- and ethnicity-specific reference equations for the interpretation of pulmonary function test (PFT) results has been questioned. RESEARCH QUESTIONS Three key questions were addressed: (1) What is the current evidence supporting the use of race- and ethnicity-specific reference equations for the interpretation of PFTs? (2) What are the potential clinical implications of the use or nonuse of race and ethnicity in interpreting PFT results? and (3) What research gaps and questions must be addressed and answered to understand better the effect of race and ethnicity on PFT results interpretation and potential clinical and occupational health implications? STUDY DESIGN AND METHODS A joint multisociety (American College of Chest Physicians, American Association for Respiratory Care, American Thoracic Society, and Canadian Thoracic Society) expert panel was formed to undertake a comprehensive evidence review and to develop a statement with recommendations to address the research questions. RESULTS Several assumptions and gaps, both in the published literature and in our evolving understanding of lung health, were identified. It seems that many past perceptions and practices regarding the effect of race and ethnicity on PFT results interpretation are based on limited scientific evidence and measures that lack reliability. INTERPRETATION A need exists for more and better research that will inform our field about these many uncertainties and will serve as a foundation for future recommendations in this area. The identified shortcomings should not be discounted or dismissed because they may enable flawed conclusions, unintended consequences, or both. Addressing the identified research gaps and needs would allow a better-a more informed-understanding of the effects of race and ethnicity on PFT results interpretation.
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Affiliation(s)
- Darcy D Marciniuk
- Division of Respirology, Critical Care and Sleep Medicine, Respiratory Research Center, University of Saskatchewan, Saskatoon, SK.
| | - Ellen A Becker
- Division of Respiratory Care, Department of Cardiopulmonary Sciences Rush University, Chicago, IL
| | - David A Kaminsky
- Pulmonary and Critical Care, University of Vermont Larner College of Medicine, Burlington, VT
| | | | - Sanja Stanojevic
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, NS
| | - Nirav R Bhakta
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA
| | | | - Vikram Comondore
- Division of Respirology, McMaster University, Hamilton, ON; Division of Respirology, William Osler Health System, Brampton, ON
| | - Clayton T Cowl
- Division of Public Health, Infectious Diseases and Occupational Medicine and the Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN
| | - Sharon Dell
- Department of Pediatrics and BC Children's Research Institute, University of British Columbia, Vancouver, BC, Canada
| | - Jeffrey Haynes
- Pulmonary Function Laboratory, Elliot Health System, Manchester, NH
| | - Fred Jaffe
- Temple University Hospital, Philadelphia, PA
| | | | | | - Mary Townsend
- M.C. Townsend Associates, LLC, Pittsburgh, PA; University of Pittsburgh School of Public Health, Pittsburgh, PA
| | - Jonathan M Iaccarino
- American College of Chest Physicians, Chicago, IL; Chobanian and Avedisian School of Medicine, Boston University, Boston, MA
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Moffett AT, Bowerman C, Stanojevic S, Eneanya ND, Halpern SD, Weissman GE. Global, Race-Neutral Reference Equations and Pulmonary Function Test Interpretation. JAMA Netw Open 2023; 6:e2316174. [PMID: 37261830 PMCID: PMC10236239 DOI: 10.1001/jamanetworkopen.2023.16174] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/23/2023] [Indexed: 06/02/2023] Open
Abstract
Importance Race and ethnicity are routinely used to inform pulmonary function test (PFT) interpretation. However, there is no biological justification for such use, and it may reinforce health disparities. Objective To compare the PFT interpretations produced with race-neutral and race-specific equations. Design, Setting, and Participants In this cross-sectional study, race-neutral reference equations recently developed by the Global Lung Function Initiative (GLI) were used to interpret PFTs performed at an academic medical center between January 2010 and December 2020. The interpretations produced with these race-neutral reference equations were compared with those produced using the race and ethnicity-specific reference equations produced by GLI in 2012. The analysis was conducted from April to October 2022. Main Outcomes and Measures The primary outcomes were differences in the percentage of obstructive, restrictive, mixed, and nonspecific lung function impairments identified using the 2 sets of reference equations. Secondary outcomes were differences in severity of these impairments. Results PFTs were interpreted from 2722 Black (686 men [25.4%]; mean [SD] age, 51.8 [13.9] years) and 5709 White (2654 men [46.5%]; mean [SD] age, 56.4 [14.3] years) individuals. Among Black individuals, replacing the race-specific reference equations with the race-neutral reference equations was associated with an increase in the prevalence of restriction from 26.8% (95% CI, 25.2%-28.5%) to 37.5% (95% CI, 35.7%-39.3%) and of a nonspecific pattern of impairment from 3.2% (95% CI, 2.5%- 3.8%) to 6.5% (95% CI, 5.6%-7.4%) and no significant change in the prevalence of obstruction (19.9% [95% CI, 18.4%-21.4%] vs 19.5% [95% CI, 18.0%-21.0%]). Among White individuals, replacing the race-specific reference equations with the race-neutral reference equations was associated with a decrease in the prevalence of restriction from 22.6% (95% CI, 21.5%-23.6%) to 18.0% (95% CI, 17.0%-19.0%), a decrease in the prevalence of a nonspecific pattern of impairment from 8.7% (95% CI, 7.9%-9.4%) to 4.0% (95% CI, 3.5%-4.5%), and no significant change in the percentage with obstruction from 23.9% (95% CI, 22.8%-25.1%) to 25.1% (95% CI, 23.9%- 26.2%). The race-neutral reference equations were associated with an increase in severity in 22.8% (95% CI, 21.2%-24.4%) of Black individuals and a decrease in severity in 19.3% (95% CI, 18.2%-20.3%) of White individuals vs the race-specific reference equations. Conclusions and Relevance In this cross-sectional study, the use of race-neutral reference equations to interpret PFTs resulted in a significant increase in the number of Black individuals with respiratory impairments along with a significant increase in the severity of the identified impairments. More work is needed to quantify the effect these reference equations would have on diagnosis, referral, and treatment patterns.
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Affiliation(s)
- Alexander T. Moffett
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
| | - Cole Bowerman
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Sanja Stanojevic
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Nwamaka D. Eneanya
- Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Renal-Electrolyte and Hypertension Division, Department of Medicine, University of Pennsylvania, Philadelphia
| | - Scott D. Halpern
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia
| | - Gary E. Weissman
- Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Medicine, University of Pennsylvania, Philadelphia
- Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia
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Ferryman K, Brems JH. How Materialized Oppression Contributes to Bioethics. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2023; 23:1-5. [PMID: 37011350 DOI: 10.1080/15265161.2023.2186628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
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Bowerman C, Bhakta NR, Brazzale D, Cooper BR, Cooper J, Gochicoa-Rangel L, Haynes J, Kaminsky DA, Lan LTT, Masekela R, McCormack MC, Steenbruggen I, Stanojevic S. A Race-neutral Approach to the Interpretation of Lung Function Measurements. Am J Respir Crit Care Med 2023; 207:768-774. [PMID: 36383197 DOI: 10.1164/rccm.202205-0963oc] [Citation(s) in RCA: 76] [Impact Index Per Article: 76.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Rationale: The use of self-reported race and ethnicity to interpret lung function measurements has historically assumed that the observed differences in lung function between racial and ethnic groups were because of thoracic cavity size differences relative to standing height. Very few studies have considered the influence of environmental and social determinants on pulmonary function. Consequently, the use of race and ethnicity-specific reference equations may further marginalize disadvantaged populations. Objectives: To develop a race-neutral reference equation for spirometry interpretation. Methods: National Health and Nutrition Examination Survey (NHANES) III data (n = 6,984) were reanalyzed with sitting height and the Cormic index to investigate whether body proportions were better predictors of lung function than race and ethnicity. Furthermore, the original GLI (Global Lung Function Initiative) data (n = 74,185) were reanalyzed with inverse-probability weights to create race-neutral GLI global (2022) equations. Measurements and Main Results: The inclusion of sitting height slightly improved the statistical precision of reference equations compared with using standing height alone but did not explain observed differences in spirometry between the NHANES III race and ethnic groups. GLI global (2022) equations, which do not require the selection of race and ethnicity, had a similar fit to the GLI 2012 "other" equations and wider limits of normal. Conclusions: The use of a single global spirometry equation reflects the wide range of lung function observed within and between populations. Given the inherent limitations of any reference equation, the use of GLI global equations to interpret spirometry requires careful consideration of an individual's symptoms and medical history when used to make clinical, employment, and insurance decisions.
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Affiliation(s)
- Cole Bowerman
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Nirav R Bhakta
- Pulmonary, Critical Care, Allergy, and Sleep Medicine, University of California San Francisco, San Francisco, California
| | - Danny Brazzale
- Department of Respiratory and Sleep Medicine, Austin Hospital, Heidelberg, Germany
| | - Brendan R Cooper
- Lung Function & Sleep, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Julie Cooper
- Lung Function & Sleep, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Laura Gochicoa-Rangel
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Jeffrey Haynes
- Pulmonary Function Laboratory, Elliot Health System, Manchester, New Hampshire
| | - David A Kaminsky
- Pulmonary Disease and Critical Care Medicine, University of Vermont College of Medicine, Burlington, Vermont
| | | | - Refiloe Masekela
- Department of Paediatrics and Child Health, Faculty of Health Sciences, School of Clinical Medicine, University of Kwazulu-Natal, Durban, South Africa
| | - Meredith C McCormack
- Division of Pulmonary and Critical Care, Johns Hopkins School of Medicine, Baltimore, Maryland; and
| | | | - Sanja Stanojevic
- Department of Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
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Grant T, Lilley T, McCormack MC, Rathouz PJ, Peng R, Keet CA, Rule A, Davis M, Balcer-Whaley S, Newman M, Matsui EC. Indoor environmental exposures and obstructive lung disease phenotypes among children with asthma living in poor urban neighborhoods. J Allergy Clin Immunol 2023; 151:716-722.e8. [PMID: 36395986 PMCID: PMC9992008 DOI: 10.1016/j.jaci.2022.08.032] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 08/04/2022] [Accepted: 08/31/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Air trapping is an obstructive phenotype that has been associated with more severe and unstable asthma in children. Air trapping has been defined using pre- and postbronchodilator spirometry. The causes of air trapping are not completely understood. It is possible that environmental exposures could be implicated in air trapping in children with asthma. OBJECTIVE We investigated the association between indoor exposures and air trapping in urban children with asthma. METHODS Children with asthma aged 5 to 17 years living in Baltimore and enrolled onto the Environmental Control as Add-on Therapy for Childhood Asthma study were evaluated for air trapping using spirometry. Aeroallergen sensitization was assessed at baseline, and spirometry was performed at 0, 3, and 6 months. Air trapping was defined as an FVC z score of less than -1.64 or a change in FVC with bronchodilation of ≥10% predicted. Logistic normal random effects models were used to evaluate associations of air trapping and indoor exposures. RESULTS Airborne and bedroom floor mouse allergen concentrations were associated with air trapping but not airflow limitation (odds ratio 1.19, 95% confidence interval 1.02-1.37, P = .02 per 2-fold increase in airborne mouse allergen; odds ratio 1.23, 95% confidence interval 1.07-1.41, P = .003 per 2-fold increase in bedroom floor mouse allergen). Other indoor exposures (cockroach, cat, dog, dust mite, particulate matter, and nicotine) were not associated with air trapping or airflow limitation. CONCLUSION Mouse allergen exposure, but not other indoor exposure, was associated with air trapping in urban children with asthma.
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Affiliation(s)
- Torie Grant
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Md; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Md
| | - Travis Lilley
- Department of Population Health, Dell Medical School at UT Austin, Austin, Tex
| | - Meredith C McCormack
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Md
| | - Paul J Rathouz
- Department of Population Health, Dell Medical School at UT Austin, Austin, Tex
| | - Roger Peng
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Corinne A Keet
- Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Ana Rule
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Pubilc Health, Baltimore, Md
| | - Meghan Davis
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Pubilc Health, Baltimore, Md
| | - Susan Balcer-Whaley
- Department of Population Health, Dell Medical School at UT Austin, Austin, Tex
| | - Michelle Newman
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Md
| | - Elizabeth C Matsui
- Department of Population Health, Dell Medical School at UT Austin, Austin, Tex; Department of Pediatrics, Dell Medical School at UT Austin, Austin, Tex.
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Rotella K, Apter AJ, Davis CM, Nyenhuis SM, Ramsey NB. Race-Specific Reference Equations Are Worse Than Universal Equations at Predicting Chronic Obstructive Pulmonary Disease Outcomes. THE JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. IN PRACTICE 2023; 11:664-665. [PMID: 36759083 DOI: 10.1016/j.jaip.2022.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 10/20/2022] [Accepted: 11/07/2022] [Indexed: 02/10/2023]
Affiliation(s)
- Karina Rotella
- Department of Pediatrics, Division of Allergy and Immunology, Elliot and Roslyn Jaffe Food Allergy Institute, Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, New York, NY
| | - Andrea J Apter
- Section of Allergy and Immunology, Division of Pulmonary, Allergy, Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa
| | - Carla M Davis
- Division of Immunology, Allergy, and Retrovirology, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
| | - Sharmilee M Nyenhuis
- Department of Pediatrics and Medicine, Section of Allergy and Immunology, University of Chicago, Chicago, Ill
| | - Nicole B Ramsey
- Department of Pediatrics, Division of Allergy and Immunology, Elliot and Roslyn Jaffe Food Allergy Institute, Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, New York, NY.
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Zhang Y, Cheng C, Wei F, Wu Z, Cui H, Liu L, Lu F, Peng J, Yang J. Reduced peak expiratory flow predicts increased risk of cardiovascular disease: A 10-year prospective cohort study in Eastern China. Respir Med Res 2023; 83:100988. [PMID: 36634554 DOI: 10.1016/j.resmer.2022.100988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/29/2022] [Accepted: 12/10/2022] [Indexed: 01/12/2023]
Abstract
BACKGROUND The correlation between impaired lung function and cardiovascular diseases (CVD) has attracted more and more attention. We aimed to assess the longitudinal association between decreased peak expiratory flow (PEF) and cardiovascular risk among Eastern Chinese general population. METHODS In total, 6295 participants aged>30 years and free of CVD at baseline were followed for up to 10 years in Eastern China. The adjusted hazard ratios (HRs) for CVD and mortality associated with decreased PEF were analyzed. RESULTS Among all participants, 421 CVD incident events were reported during 10-year follow-up, and a total of 272 participants died during the follow-up period, 94 of them from CVD. The HRs in the lowest group of PEF (PEF ≤218.33 L/min) were 1.31 (95% confidence interval [CI]:1.01 to 1.68) for high CVD incidence (172 vs 116), 2.43 (95% CI:1.72 to 3.42) for all-cause mortality (156 vs 48), and 3.94 (95% CI:1.96 to 7.92) for CVD mortality (59 vs 10) when compared with the highest group (PEF ≥321.68 L/min). CONCLUSION The decreased PEF was associated with increased CVD incidence, CVD and all-cause mortality in Eastern Chinese general population.
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Affiliation(s)
- Yerui Zhang
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Cheng Cheng
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China; Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, 110004, China
| | - Fang Wei
- Jinan Central hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Zhenguo Wu
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Huiliang Cui
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Li Liu
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China
| | - Fanghong Lu
- Cardio-Cerebrovascular Control and Research Center, Shandong Academy of Medical Sciences, Jinan, China
| | - Jie Peng
- Department of Geriatric Medicine, Qilu Hospital of Shandong University, Key Laboratory of Cardiovascular Proteomics of Shandong Province, Jinan, China.
| | - Jianmin Yang
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, The State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China.
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Kitazawa H, Jiang A, Nohra C, Ota H, Wu JKY, Ryan CM, Chow CW. Changes in interpretation of spirometry by implementing the GLI 2012 reference equations: impact on patients tested in a hospital-based PFT lab in a large metropolitan city. BMJ Open Respir Res 2022; 9:9/1/e001389. [PMID: 36600407 PMCID: PMC9743406 DOI: 10.1136/bmjresp-2022-001389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 11/18/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The Global Lung Function Initiative (GLI-2012) focused on race/ethnicity as an important factor in determining reference values. This study evaluated the effects of changing from Canadian reference equations developed from an all-Caucasian cohort with European ancestry to the GLI-2012 on the interpretation of spirometry in a multiethnic population and aimed to identify the ethnic groups affected by discrepant interpretations. METHODS Clinically indicated spirometry in a multiethnic population (aged 20-80 years) collected from 2018 to 2021 was analysed. The predicted and lower limit of normal (LLN) values were calculated using three sets of reference equations: Canadian, GLI-race/ethnic-based (GLI-Race) and GLI-race/ethnic-neutral (GLI-Other). We compared the prevalence of concordance in the abnormal diagnoses (defined as <LLN) for forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and FEV1/FVC among the three reference values, and evaluated whether race/ethnicity was associated with discordance. RESULTS Data from 406 participants were evaluated (non-Caucasian 43.6%). There was 85%-87% concordance for normal/abnormal FVC and FEV1 interpretations among the Canadian, GLI-Race and GLI-Other reference equations. In all ethnic groups, application of the Canadian references for interpretation led to a higher prevalence of abnormal (<LLN) FVC and FEV1compared with GLI-Race and GLI-Other. This trend was more prominent in Black, South-East Asian and Mixed/other ethnic groups when comparing the Canadian to the GLI-Race equations. In contrast, the discordance rates were similar among ethnic groups when compared with the GLI-Other reference equations. Interpretation of FEV1/FVC had a high rate of agreement among all equations. CONCLUSION Interpretation using Canadian reference equations was associated with a higher prevalence of restrictive physiology compared with the GLI-2012 equations, particularly if the GLI-Race were used. These observations were mostly found in non-white Caucasian groups, highlighting the need to choose reference equations that reflect closely the ethnic mix of the population being evaluated in order to optimise patient management.
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Affiliation(s)
- Haruna Kitazawa
- Department of Medicine, University Health Network, Toronto, Ontario, Canada,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Annie Jiang
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Cynthia Nohra
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Honami Ota
- Department of Medicine, University Health Network, Toronto, Ontario, Canada
| | - Joyce K Y Wu
- Department of Medicine, University Health Network, Toronto, Ontario, Canada,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Clodagh M Ryan
- Department of Medicine, University Health Network, Toronto, Ontario, Canada,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada,Sleep Research Laboratory, Toronto Rehabilitation Institute University Health Network, Toronto, Ontario, Canada
| | - Chung-Wai Chow
- Department of Medicine, University Health Network, Toronto, Ontario, Canada,Department of Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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40
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Schuyler AJ, Wenzel SE. Historical Redlining Impacts Contemporary Environmental and Asthma-related Outcomes in Black Adults. Am J Respir Crit Care Med 2022; 206:824-837. [PMID: 35612914 PMCID: PMC9799280 DOI: 10.1164/rccm.202112-2707oc] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 05/25/2022] [Indexed: 01/02/2023] Open
Abstract
Rationale: Environmental threats and poorly controlled asthma disproportionately burden Black people. Some have attributed this to socioeconomic or biologic factors; however, racism, specifically historical redlining, a U.S. discriminatory mortgage lending practice in existence between the 1930s and the 1970s, may have actuated and then perpetuated poor asthma-related outcomes. Objectives: To link historical redlining (institutional racism) to contemporary environmental quality- and lung health-related racial inequity. Methods: Leveraging a broadly recruited asthma registry, we geocoded 1,034 registry participants from Pittsburgh/Allegheny County, Pennsylvania, to neighborhoods subjected to historical redlining, as defined by a 1930s Home Owners' Loan Corporation (HOLC) map. Individual-level clinical/physiologic data, residential air pollution, demographics, and socioeconomic factors provided detailed characterization. We determined the prevalence of uncontrolled and/or severe asthma and other asthma-related outcomes by HOLC (neighborhood) grade (A-D). We performed a stratified analysis by self-identified race to assess the distribution of environmental and asthma risk within each HOLC grade. Measurements and Main Results: The registry sampling overall reflected Allegheny County neighborhood populations. The emissions of carbon monoxide, filterable particulate matter <2.5 μm, sulfur dioxide, and volatile organic compounds increased across HOLC grades (all P ⩽ 0.004), with grade D neighborhoods encumbered by the highest levels. The persistent, dispersive socioenvironmental burden peripherally extending from grade D neighborhoods, including racialized access to healthy environments (structural racism), supported a long-term impact of historical/HOLC redlining. The worst asthma-related outcomes, including uncontrolled and/or severe asthma (P < 0.001; Z = 3.81), and evidence for delivery of suboptimal asthma care occurred among registry participants from grade D neighborhoods. Furthermore, elevated exposure to filterable particulate matter <2.5 μm, sulfur dioxide, and volatile organic compound emissions (all P < 0.050) and risk of uncontrolled and/or severe asthma (relative risk [95% confidence interval], 2.30 [1.19, 4.43]; P = 0.009) demonstrated inequitable distributions within grade D neighborhood boundaries, disproportionately burdening Black registry participants. Conclusions: The racist practice of historical/HOLC redlining profoundly contributes to long-term environmental and asthma-related inequities in Black adults. Acknowledging the role racism has in these outcomes should empower more specific and novel interventions targeted at reversing these structural issues.
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Affiliation(s)
- Alexander J. Schuyler
- University of Pittsburgh Asthma and Environmental Lung Health Institute@UPMC and
- Department of Environmental & Occupational Health, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Sally E. Wenzel
- University of Pittsburgh Asthma and Environmental Lung Health Institute@UPMC and
- Department of Environmental & Occupational Health, School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
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41
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Miller MR, Graham BL, Thompson BR. Race/Ethnicity and Reference Equations for Spirometry. Am J Respir Crit Care Med 2022; 206:790-792. [PMID: 35503241 PMCID: PMC9799116 DOI: 10.1164/rccm.202201-0197le] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Martin R. Miller
- University of BirminghamBirmingham, United Kingdom,Corresponding author (e-mail: )
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42
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Townsend MC, Cowl CT. U.S. Occupational Historical Perspective on Race and Lung Function. Am J Respir Crit Care Med 2022; 206:789-790. [PMID: 35503517 PMCID: PMC9799108 DOI: 10.1164/rccm.202203-0565le] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Mary C. Townsend
- M.C. Townsend Associates, LLCPittsburgh, Pennsylvania,University of Pittsburgh School of Public HealthPittsburgh, Pennsylvania,Corresponding author (e-mail: )
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McCormack M, Balasubramanian A, Wise RA, Keet CA, Matsui EC, Peng RD. Reply by McCormack et al. to Townsend and Cowl, and to Miller et al.. Am J Respir Crit Care Med 2022; 206:795-796. [PMID: 35503239 PMCID: PMC9799112 DOI: 10.1164/rccm.202202-0378le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Affiliation(s)
- Meredith McCormack
- Johns Hopkins UniversityBaltimore, Maryland,Corresponding author (e-mail: )
| | | | | | | | | | - Roger D. Peng
- Johns Hopkins Bloomberg School of Public HealthBaltimore, Maryland
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Ramsey NB, Apter AJ, Israel E, Louisias MM, Noroski LM, Nyenhuis SM, Ogbogu PU, Perry TT, Wang J, Davis CM. Reply to "How to deconstruct 'race' and spirometry". THE JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. IN PRACTICE 2022; 10:2489-2491. [PMID: 36087950 DOI: 10.1016/j.jaip.2022.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 07/11/2022] [Indexed: 06/15/2023]
Affiliation(s)
- Nicole B Ramsey
- Department of Pediatrics, Division of Allergy and Immunology, Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, Elliot and Roslyn Jaffe Food Allergy Institute, New York, NY.
| | - Andrea J Apter
- Department of Medicine, Division of Allergy and Immunology, University of Pennsylvania, Philadelphia, Pa
| | - Elliot Israel
- Division of Pulmonary and Critical Care, Harvard Medical School, Brigham Women's Hospital, Boston, Mass; Division of Allergy and Immunology, Harvard Medical School, Brigham Women's Hospital, Boston, Mass
| | - Margee M Louisias
- Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass; Division of Immunology, Boston Children's Hospital, Boston, Mass
| | - Lenora M Noroski
- Division of Pediatric Allergy, Immunology, and Retrovirology of Texas Children's Hospital of the Baylor College of Medicine, Houston, Texas
| | - Sharmilee M Nyenhuis
- Department of Pediatrics, Section of Allergy/Immunology, University of Chicago, Chicago, Ill
| | - Princess U Ogbogu
- University Hospitals Rainbow Babies and Children's Hospital, Cleveland, Ohio; Department of Pediatrics, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Tamara T Perry
- Department of Pediatrics, Division of Allergy and Immunology, University of Arkansas for Medical Sciences and Arkansas Children's Research Institute, Little Rock, Ark
| | - Julie Wang
- Department of Pediatrics, Division of Allergy and Immunology, Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, Elliot and Roslyn Jaffe Food Allergy Institute, New York, NY
| | - Carla M Davis
- Division of Pediatric Allergy, Immunology, and Retrovirology of Texas Children's Hospital of the Baylor College of Medicine, Houston, Texas
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45
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The Contribution of Anthropometry and Socioeconomic Status to Racial Differences in Measures of Lung Function. Chest 2022; 162:635-646. [DOI: 10.1016/j.chest.2022.04.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 04/13/2022] [Accepted: 04/15/2022] [Indexed: 11/19/2022] Open
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46
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Liu GY, Khan SS, Colangelo LA, Meza D, Washko GR, Sporn PHS, Jacobs DR, Dransfield MT, Carnethon MR, Kalhan R. Comparing Racial Differences in Emphysema Prevalence Among Adults With Normal Spirometry: A Secondary Data Analysis of the CARDIA Lung Study. Ann Intern Med 2022; 175:1118-1125. [PMID: 35849828 PMCID: PMC9673050 DOI: 10.7326/m22-0205] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Computed tomography (CT) imaging complements spirometry and may provide insight into racial disparities in respiratory health. OBJECTIVE To determine the difference in emphysema prevalence between Black and White adults with different measures of normal spirometry results. DESIGN Observational study using clinical data and spirometry from the CARDIA (Coronary Artery Risk Development in Young Adults) study obtained in 2015 to 2016 and CT scans done in 2010 to 2011. SETTING 4 U.S. centers. PARTICIPANTS Population-based sample of Black and White adults. MEASUREMENTS Self-identified race and visually identified emphysema on CT in participants with different measures of "normal" spirometry results, calculated using standard race-specific and race-neutral reference equations. RESULTS A total of 2674 participants (485 Black men, 762 Black women, 659 White men, and 768 White women) had both a CT scan and spirometry available for analysis. Among participants with a race-specific FEV1 between 80% and 99% of predicted, 6.5% had emphysema. In this group, emphysema prevalence was 3.9-fold (95% CI, 2.1- to 7.1-fold; 15.5% vs. 4.0%) higher among Black men than White men and 1.9-fold (CI, 1.0- to 3.8-fold; 6.6% vs. 3.4%) higher among Black women than White women. Among participants with a race-specific FEV1 between 100% and 120% of predicted, 4.0% had emphysema. In this category, Black men had a 6.4-fold (CI, 2.2- to 18.7-fold; 13.9% vs. 2.2%) higher prevalence of emphysema than White men, whereas Black and White women had a similar prevalence of emphysema (2.6% and 2.0%, respectively). The use of race-neutral equations to identify participants with an FEV1 percent predicted between 80% and 120% attenuated racial differences in emphysema prevalence among men and eliminated racial differences among women. LIMITATION No CT scans were obtained during the most recent study visit (2015 to 2016) when spirometry was done. CONCLUSION Emphysema is often present before spirometry findings become abnormal, particularly among Black men. Reliance on spirometry alone to differentiate lung health from lung disease may result in the underrecognition of impaired respiratory health and exacerbate racial disparities. PRIMARY FUNDING SOURCE National Institutes of Health.
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Affiliation(s)
- Gabrielle Y Liu
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (G.Y.L., D.M., P.H.S.S.)
| | - Sadiya S Khan
- Division of Cardiology, Department of Medicine, and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (S.S.K.)
| | - Laura A Colangelo
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (L.A.C.)
| | - Daniel Meza
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (G.Y.L., D.M., P.H.S.S.)
| | - George R Washko
- Applied Chest Imaging Laboratory and Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, Massachusetts (G.R.W.)
| | - Peter H S Sporn
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (G.Y.L., D.M., P.H.S.S.)
| | - David R Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota (D.R.J.)
| | - Mark T Dransfield
- Lung Health Center, University of Alabama at Birmingham, Birmingham, Alabama (M.T.D.)
| | - Mercedes R Carnethon
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.R.C., R.K.)
| | - Ravi Kalhan
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, and Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (M.R.C., R.K.)
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Fawzy A, Wu TD, Wang K, Robinson ML, Farha J, Bradke A, Golden SH, Xu Y, Garibaldi BT. Racial and Ethnic Discrepancy in Pulse Oximetry and Delayed Identification of Treatment Eligibility Among Patients With COVID-19. JAMA Intern Med 2022; 182:730-738. [PMID: 35639368 PMCID: PMC9257583 DOI: 10.1001/jamainternmed.2022.1906] [Citation(s) in RCA: 135] [Impact Index Per Article: 67.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
IMPORTANCE Pulse oximetry guides triage and therapy decisions for COVID-19. Whether reported racial inaccuracies in oxygen saturation measured by pulse oximetry are present in patients with COVID-19 and associated with treatment decisions is unknown. OBJECTIVE To determine whether there is differential inaccuracy of pulse oximetry by race or ethnicity among patients with COVID-19 and estimate the association of such inaccuracies with time to recognition of eligibility for oxygen threshold-specific COVID-19 therapies. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study of clinical data from 5 referral centers and community hospitals in the Johns Hopkins Health System included patients with COVID-19 who self-identified as Asian, Black, Hispanic, or White. EXPOSURES Concurrent measurements (within 10 minutes) of oxygen saturation levels in arterial blood (SaO2) and by pulse oximetry (SpO2). MAIN OUTCOMES AND MEASURES For patients with concurrent SpO2 and SaO2 measurements, the proportion with occult hypoxemia (SaO2<88% with concurrent SpO2 of 92%-96%) was compared by race and ethnicity, and a covariate-adjusted linear mixed-effects model was produced to estimate the association of race and ethnicity with SpO2 and SaO2 difference. This model was applied to identify a separate sample of patients with predicted SaO2 levels of 94% or less before an SpO2 level of 94% or less or oxygen treatment initiation. Cox proportional hazards models were used to estimate differences by race and ethnicity in time to recognition of eligibility for guideline-recommended COVID-19 therapies, defined as an SpO2 level of 94% or less or oxygen treatment initiation. The median delay among individuals who ultimately had recognition of eligibility was then compared. RESULTS Of 7126 patients with COVID-19, 1216 patients (63 Asian [5.2%], 478 Black [39.3%], 215 Hispanic [17.7%], and 460 White [37.8%] individuals; 507 women [41.7%]) had 32 282 concurrently measured SpO2 and SaO2. Occult hypoxemia occurred in 19 Asian (30.2%), 136 Black (28.5%), and 64 non-Black Hispanic (29.8%) patients compared with 79 White patients (17.2%). Compared with White patients, SpO2 overestimated SaO2 by an average of 1.7% among Asian (95% CI, 0.5%-3.0%), 1.2% among Black (95% CI, 0.6%-1.9%), and 1.1% among non-Black Hispanic patients (95% CI, 0.3%-1.9%). Separately, among 1903 patients with predicted SaO2 levels of 94% or less before an SpO2 level of 94% or less or oxygen treatment initiation, compared with White patients, Black patients had a 29% lower hazard (hazard ratio, 0.71; 95% CI, 0.63-0.80), and non-Black Hispanic patients had a 23% lower hazard (hazard ratio, 0.77; 95% CI, 0.66-0.89) of treatment eligibility recognition. A total of 451 patients (23.7%) never had their treatment eligibility recognized, most of whom (247 [54.8%]) were Black. Among the remaining 1452 (76.3%) who had eventual recognition of treatment eligibility, Black patients had a median delay of 1.0 hour (95% CI, 0.23-1.9 hours; P = .01) longer than White patients. There was no significant median difference in delay between individuals of other racial and ethnic minority groups and White patients. CONCLUSIONS AND RELEVANCE The results of this cohort study suggest that racial and ethnic biases in pulse oximetry accuracy were associated with greater occult hypoxemia in Asian, Black, and non-Black Hispanic patients with COVID-19, which was associated with significantly delayed or unrecognized eligibility for COVID-19 therapies among Black and Hispanic patients. This disparity may contribute to worse outcomes among Black and Hispanic patients with COVID-19.
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Affiliation(s)
- Ashraf Fawzy
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Tianshi David Wu
- Section of Pulmonary, Critical Care, and Sleep Medicine, Baylor College of Medicine, Houston, Texas.,Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas
| | - Kunbo Wang
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland
| | - Matthew L Robinson
- Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jad Farha
- Department of Medicine, Johns Hopkins Bayview Medical Center, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Amanda Bradke
- Department of Medicine, Rush University Medical Center, Chicago, Illinois
| | - Sherita H Golden
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Yanxun Xu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland
| | - Brian T Garibaldi
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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Graham BL, Miller MR, Thompson BR. Addressing the effect of ancestry on lung volume. Eur Respir J 2022; 59:59/6/2200882. [PMID: 35714993 DOI: 10.1183/13993003.00882-2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 11/05/2022]
Affiliation(s)
- Brian L Graham
- Division of Respirology, Critical Care and Sleep Medicine, University of Saskatchewan, Saskatoon, SK, Canada
| | - Martin R Miller
- Institute of Applied Health Sciences, University of Birmingham, Birmingham, UK
| | - Bruce R Thompson
- Melbourne School of Health Science, University of Melbourne, Victoria, Australia
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49
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Ramsey NB, Apter AJ, Israel E, Louisias M, Noroski LM, Nyenhuis SM, Ogbogu PU, Perry TT, Wang J, Davis CM. Deconstructing the Way We Use Pulmonary Function Test Race-Based Adjustments. THE JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. IN PRACTICE 2022; 10:972-978. [PMID: 35184982 DOI: 10.1016/j.jaip.2022.01.023] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 01/08/2022] [Accepted: 01/21/2022] [Indexed: 06/14/2023]
Abstract
Race is a social construct. It is used in medical diagnostic algorithms to adjust the readout for spirometry and other diagnostic tests. The authors review historic evidence about the origins of race adjustment in spirometry, and recent attention to the lack of scientific evidence for their continued use. Existing reference values imply that White patients have better lung function than non-White patients. They perpetuate the historical assumptions that human biological functions of the lung should be calculated differently on the basis of racial-skin color without considering the difficulty of using self-identified race. More importantly, they fail to consider the important effects of environmental exposures, socioeconomic differences, health care access, and prenatal factors on lung function. In addition, the use of "race adjustment" implies a White standard to which other non-White values need "adjustment." Because of the spirometric guidelines in place, the current diagnostic prediction adjustment practice may have untoward effects on patients not categorized as "White," including underdiagnosis in asthma and restrictive lung disease, undertreatment with lung transplant, undercompensation in workers compensation cases, and other unintended consequences. Individuals, institutions, national organizations, and policymakers should carefully consider the historic basis, and reconsider the current role of an automated, race-based adjustment in spirometry.
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Affiliation(s)
- Nicole B Ramsey
- Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, Department of Pediatrics, Division of Allergy and Immunology, The Elliot and Roslyn Jaffe Food Allergy Institute, New York, NY.
| | - Andrea J Apter
- University of Pennsylvania, Department of Medicine, Division of Allergy & Immunology, Philadelphia, Pa
| | - Elliot Israel
- Harvard Medical School, Brigham Women's Hospital, Divisions of Pulmonary & Critical Care and Allergy & Immunology, Boston, Mass
| | - Margee Louisias
- Brigham and Women's Hospital, Division of Allergy and Clinical Immunology, Harvard Medical School, Boston, Mass; Boston Children's Hospital, Division of Immunology, Boston, Mass
| | - Lenora M Noroski
- Division of Immunology, Allergy, and Retrovirology, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
| | - Sharmilee M Nyenhuis
- University of Illinois at Chicago, Department of Medicine, Division of Pulmonary, Critical Care, Sleep and Allergy, Chicago, Ill
| | - Princess U Ogbogu
- University Hospitals Rainbow Babies and Children's Hospital, Cleveland, Ohio; Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Tamara T Perry
- University of Arkansas for Medical Sciences and Arkansas Children's Research Institute, Little Rock, Ark
| | - Julie Wang
- Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, Department of Pediatrics, Division of Allergy and Immunology, The Elliot and Roslyn Jaffe Food Allergy Institute, New York, NY
| | - Carla M Davis
- Division of Immunology, Allergy, and Retrovirology, Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
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Baugh AD, Shiboski S, Hansel NN, Ortega V, Barjaktarevic I, Barr RG, Bowler R, Comellas AP, Cooper CB, Couper D, Criner G, Curtis JL, Dransfield M, Ejike C, Han MK, Hoffman E, Krishnan J, Krishnan JA, Mannino D, Paine R, Parekh T, Peters S, Putcha N, Rennard S, Thakur N, Woodruff PG. Reconsidering the Utility of Race-Specific Lung Function Prediction Equations. Am J Respir Crit Care Med 2022; 205:819-829. [PMID: 34913855 PMCID: PMC9836221 DOI: 10.1164/rccm.202105-1246oc] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 12/15/2021] [Indexed: 02/04/2023] Open
Abstract
Rationale: African American individuals have worse outcomes in chronic obstructive pulmonary disease (COPD). Objectives: To assess whether race-specific approaches for estimating lung function contribute to racial inequities by failing to recognize 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 modeled the relationship between FEV1, FVC, and other COPD outcomes, including the COPD Assessment Test, St. George's Respiratory Questionnaire, computed tomography percent emphysema, airway wall thickness, and 6-minute-walk test. 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 American individuals were calculated to have better lung function than non-Hispanic White individuals (FEV1, 76.8% vs. 71.8% predicted; P = 0.02). Using universally applied equations, African American individuals were calculated to have worse lung function. Using Hankinson's Non-Hispanic White equation, FEV1 was 64.7% versus 71.8% (P < 0.001). Using the Global Lung Initiative's Other race equation, FEV1 was 70.0% versus 77.9% (P < 0.001). Prediction errors from linear regression were less for universally applied equations compared with race-specific equations when examining FEV1% predicted with the COPD Assessment Test (P < 0.01), St. George's Respiratory Questionnaire (P < 0.01), and airway wall thickness (P < 0.01). Although African American participants 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 underestimate COPD severity in African American individuals.Clinical trial registered with www.clinicaltrials.gov (NCT01969344).
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Affiliation(s)
- Aaron D. Baugh
- University of California San Francisco, San Francisco, California
| | - Stephen Shiboski
- University of California San Francisco, San Francisco, California
| | | | - Victor Ortega
- Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Igor Barjaktarevic
- David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - R. Graham Barr
- Columbia University Medical Center, Columbia University, New York, New York
| | | | | | | | - David Couper
- Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina
| | - Gerard Criner
- Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania
| | - Jeffrey L. Curtis
- University of Michigan, Ann Arbor, Michigan
- Veterans Administration Ann Arbor Healthcare System, Ann Arbor, Michigan
| | | | | | | | - Eric Hoffman
- Carver College of Medicine, University of Iowa, Iowa City, Iowa
| | | | | | | | | | | | - Stephen Peters
- Wake Forest School of Medicine, Winston-Salem, North Carolina
| | | | | | - Neeta Thakur
- University of California San Francisco, San Francisco, California
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