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Reconsidering the Utility of Race-Specific Lung Function Prediction Equations.
Baugh, Aaron D; Shiboski, Stephen; Hansel, Nadia N; Ortega, Victor; Barjaktarevic, Igor; Barr, R Graham; Bowler, Russell; Comellas, Alejandro P; Cooper, Christopher B; Couper, David; Criner, Gerard; Curtis, Jeffrey L; Dransfield, Mark; Ejike, Chinedu; Han, MeiLan K; Hoffman, Eric; Krishnan, Jamuna; Krishnan, Jerry A; Mannino, David; Paine, Robert; Parekh, Trisha; Peters, Stephen; Putcha, Nirupama; Rennard, Stephen; Thakur, Neeta; Woodruff, Prescott G.
Afiliación
  • Baugh AD; University of California San Francisco, San Francisco, California.
  • Shiboski S; University of California San Francisco, San Francisco, California.
  • Hansel NN; Johns Hopkins University, Baltimore, Maryland.
  • Ortega V; Wake Forest School of Medicine, Winston-Salem, North Carolina.
  • Barjaktarevic I; David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.
  • Barr RG; Columbia University Medical Center, Columbia University, New York, New York.
  • Bowler R; National Jewish Health, Denver, Colorado.
  • Comellas AP; Carver College of Medicine, University of Iowa, Iowa City, Iowa.
  • Cooper CB; Johns Hopkins University, Baltimore, Maryland.
  • Couper D; Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina.
  • Criner G; Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania.
  • Curtis JL; University of Michigan, Ann Arbor, Michigan.
  • Dransfield M; Veterans Administration Ann Arbor Healthcare System, Ann Arbor, Michigan.
  • Ejike C; University of Alabama, Birmingham, Alabama.
  • Han MK; Johns Hopkins University, Baltimore, Maryland.
  • Hoffman E; University of Michigan, Ann Arbor, Michigan.
  • Krishnan J; Carver College of Medicine, University of Iowa, Iowa City, Iowa.
  • Krishnan JA; Weill Cornell Medicine, New York, New York.
  • Mannino D; University of Illinois at Chicago, Chicago, Illinois.
  • Paine R; University of Kentucky, Lexington, Kentucky.
  • Parekh T; University of Utah, Salt Lake City, Utah; and.
  • Peters S; University of Alabama, Birmingham, Alabama.
  • Putcha N; Wake Forest School of Medicine, Winston-Salem, North Carolina.
  • Rennard S; Johns Hopkins University, Baltimore, Maryland.
  • Thakur N; University of Nebraska, Omaha, Nebraska.
  • Woodruff PG; University of California San Francisco, San Francisco, California.
Am J Respir Crit Care Med ; 205(7): 819-829, 2022 04 01.
Article en En | MEDLINE | ID: mdl-34913855
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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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfisema Pulmonar / Enfermedad Pulmonar Obstructiva Crónica Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Am J Respir Crit Care Med Asunto de la revista: TERAPIA INTENSIVA Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfisema Pulmonar / Enfermedad Pulmonar Obstructiva Crónica Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Am J Respir Crit Care Med Asunto de la revista: TERAPIA INTENSIVA Año: 2022 Tipo del documento: Article