Race-Specific versus Race-Neutral Pulmonary Function Predicted Values in Patients with Operable Lung Cancer

<b>Rationale:</b> Percent predicted forced expiratory volume in 1 second (FEV<sub>1</sub>pp) is used for surgical risk assessment in patients with lung cancer. FEV<sub>1</sub>pp is adjusted for race, despite concerns regarding inaccurate estimations of lung health. <b>Objectives:</b> To compare prediction of race-specific versus race-neutral FEV<sub>1</sub>pp for pulmonary complications after lung cancer resection. <b>Methods:</b> Patients who underwent lung resection in the Society of Thoracic Surgeons General Thoracic Surgery Database were identified (2002-2008). We used Global Lung Initiative equations to derive race-specific and race-neutral FEV<sub>1</sub>pp and compared their performance to predict pulmonary complications. Postoperative FEV<sub>1</sub>pp was calculated with patients categorized into low- (>60%), intermediate- (30-60%), and high- (<30%) risk groups. <b>Results:</b> Of 24,276 patients, most were White (<i>n</i> = 21,130; 87.0%) or Black (<i>n</i> = 1,912; 7.9%). Race-specific equations reduced the mean FEV<sub>1</sub>pp by 5.3% for White patients and increased it 6.2% for Black patients compared with race-neutral equations. Multivariate models using race-neutral FEV<sub>1</sub>pp performed similarly to race-specific models in predicting pulmonary complications (sublobar resection: C-statistic 0.72; lobectomy: C-statistic 0.65; and bilobectomy/pneumonectomy: C-statistic 0.67; for both models) with similar adjusted odds ratios of FEV<sub>1</sub>pp for both equation types. In 5,422 patients with calculable postoperative FEV<sub>1</sub>pp, 617 (11.4%) were recategorized into a higher (<i>n</i> = 65) or lower (<i>n</i> = 552) risk group when using race-neutral equations. Of those moving into a lower-risk group, 98.0% were White. All patients reclassified into higher-risk groups were Black. <b>Conclusions:</b> Race-neutral FEV<sub>1</sub>pp performed equally well as race-specific equations in predicting pulmonary complications and disentangled the effect of respiratory function from race on outcomes.

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Publication Details

Journal
Annals of the American Thoracic Society
Published
2025-03-28
DOI
https://doi.org/10.1513/annalsats.202408-846oc
Citations
1
Primary Topic
Lung Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.52
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article

Race-Specific versus Race-Neutral Pulmonary Function Predicted Values in Patients with Operable Lung Cancer

David E. Ost, Mark I. Block, Aaron Baugh, Ara Asadur Vaporciyan et al.
1 citations
Annals of the American Thoracic Society
Lung Cancer Diagnosis and Treatment
1.52
article

Race-Specific versus Race-Neutral Pulmonary Function Predicted Values in Patients with Operable Lung Cancer

David E. Ost, Mark I. Block, Aaron Baugh, Ara Asadur Vaporciyan, Ajay Sheshadri, Levi N. Bonnell, Ravi Rajaram, Liang Li, Robert Habib, Elizabeth A. David
article en
1 citations

Abstract

<b>Rationale:</b> Percent predicted forced expiratory volume in 1 second (FEV<sub>1</sub>pp) is used for surgical risk assessment in patients with lung cancer. FEV<sub>1</sub>pp is adjusted for race, despite concerns regarding inaccurate estimations of lung health. <b>Objectives:</b> To compare prediction of race-specific versus race-neutral FEV<sub>1</sub>pp for pulmonary complications after lung cancer resection. <b>Methods:</b> Patients who underwent lung resection in the Society of Thoracic Surgeons General Thoracic Surgery Database were identified (2002-2008). We used Global Lung Initiative equations to derive race-specific and race-neutral FEV<sub>1</sub>pp and compared their performance to predict pulmonary complications. Postoperative FEV<sub>1</sub>pp was calculated with patients categorized into low- (>60%), intermediate- (30-60%), and high- (<30%) risk groups. <b>Results:</b> Of 24,276 patients, most were White (<i>n</i> = 21,130; 87.0%) or Black (<i>n</i> = 1,912; 7.9%). Race-specific equations reduced the mean FEV<sub>1</sub>pp by 5.3% for White patients and increased it 6.2% for Black patients compared with race-neutral equations. Multivariate models using race-neutral FEV<sub>1</sub>pp performed similarly to race-specific models in predicting pulmonary complications (sublobar resection: C-statistic 0.72; lobectomy: C-statistic 0.65; and bilobectomy/pneumonectomy: C-statistic 0.67; for both models) with similar adjusted odds ratios of FEV<sub>1</sub>pp for both equation types. In 5,422 patients with calculable postoperative FEV<sub>1</sub>pp, 617 (11.4%) were recategorized into a higher (<i>n</i> = 65) or lower (<i>n</i> = 552) risk group when using race-neutral equations. Of those moving into a lower-risk group, 98.0% were White. All patients reclassified into higher-risk groups were Black. <b>Conclusions:</b> Race-neutral FEV<sub>1</sub>pp performed equally well as race-specific equations in predicting pulmonary complications and disentangled the effect of respiratory function from race on outcomes.

Annals of the American Thoracic SocietyVol. 22(8)
The University of Texas MD Anderson Cancer Center (US), University of California, San Francisco (US), Society of Thoracic Surgeons (US), University of California System (US), Memorial Healthcare System (US), Department of Physics, Mathematics and Informatics (BY), Pulmonary Associates (US), University of Colorado Denver (US)
Good health and well-being
Openalex Percentile: Top 20%
Lung Cancer Diagnosis and Treatment
1.52
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