Radiographic lung volumes predict progression to COPD in smokers with preserved spirometry in SPIROMICS

Abstract

The characteristics that predict progression to overt chronic obstructive pulmonary disease (COPD) in smokers without spirometric airflow obstruction are not clearly defined.We conducted a post hoc analysis of 849 current and former smokers (≥20 pack-years) with preserved spirometry from the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) cohort who had baseline computed tomography (CT) scans of lungs and serial spirometry. We examined whether CT-derived lung volumes representing air trapping could predict adverse respiratory outcomes and more rapid decline in spirometry to overt COPD using mixed-effect linear modelling.Among these subjects with normal forced expiratory volume in 1 s (FEV1) to forced vital capacity (FVC) ratio, CT-measured residual volume (RVCT) to total lung capacity (TLCCT) ratio varied widely, from 21% to 59%. Over 2.5±0.7 years of follow-up, subjects with higher RVCT/TLCCT had a greater differential rate of decline in FEV1/FVC; those in the upper RVCT/TLCCT tertile had a 0.66% (95% CI 0.06%-1.27%) faster rate of decline per year compared with those in the lower tertile (p=0.015) regardless of demographics, baseline spirometry, respiratory symptoms score, smoking status (former versus current) or smoking burden (pack-years). Accordingly, subjects with higher RVCT/TLCCT were more likely to develop spirometric COPD (OR 5.7 (95% CI 2.4-13.2) in upper versus lower RVCT/TLCCT tertile; p<0.001). Other CT indices of air trapping showed similar patterns of association with lung function decline; however, when all CT indices of air trapping, emphysema, and airway disease were included in the same model, only RVCT/TLCCT retained its significance.Increased air trapping based on radiographic lung volumes predicts accelerated spirometry decline and progression to COPD in smokers without obstruction.

Conflict of interest statement

Conflict of interest: S. Zeng reports salary support from United States Department of Veterans Affairs, during the conduct of the study. Conflict of interest: I. Barjaktarevic reports grants from AMGEN, grants and personal fees from GE Healthcare, personal fees from Grifols, AstraZeneca, CSL Behring, Boehringer Ingelheim, Verona Pharma and Fisher and Pykel Healthcare, outside the submitted work. Conflict of interest: R.G. Barr reports grants from NIH, Foundation for the NIH and COPD Foundation, during the conduct of the study; grants from Alpha1 Foundation, personal fees (royalties) from UpToDate, outside the submitted work. Conflict of interest: E.R. Bleecker reports grants from SARP, AsthmaNET, SPIROMICS, Pharmacogenetics and Foundation NIH, involvement in clinical trials administered through Wake Forest School of Medicine for Amgen, AstraZeneca/MedImmune, Boehringer Ingelheim, Genentech/Roche, GlaxoSmithKline, Janssen/Johnson & Johnson, Novartis, Pfizer, Sanofi-Regeneron and Teva, personal fees for consultancy from Amgen, AstraZeneca/MedImmune, Boehringer Ingelheim, Genentech/Roche, GlaxoSmithKline, Knopp, Novartis and Sanofi/Regeneron, outside the submitted work. Conflict of interest: R.P. Bowler reports having served on advistory boards for Boehringer-Ingelheim and Abbott Nutrition, outside the submitted work. Conflict of interest: R.G. Buhr reports personal fees from GlaxoSmithKline, outside the submitted work. Conflict of interest: G.J. Criner has nothing to disclose. Conflict of interest: A.P. Comellas reports grants from NIH, during the conduct of the study; non-financial support for consultancy from VIDA Diagnostics, outside the submitted work. Conflict of interest: C.B. Cooper has nothing to disclose. Conflict of interest: D.J. Couper reports grants from NHLBI (NIH) and COPD Foundation, during the conduct of the study; grants from NHLBI (NIH), outside the submitted work. Conflict of interest: J.L. Curtis reports grants from NIH/NHLBI (U01HL137880), during the conduct of the study; and grants from Department of Veterans Affairs (I01 CX000911), NIH/NIAID (R01 AI120526, R21 AI 117371), Department of Defense (W81XWH-15-1-0705, PR150432) and MedImmune, Corp. Ltd, outside the submitted work. Conflict of interest: M.T. Dransfield reports grants from NIH, during the conduct of the study; grants from Department of Defense, NIH and the American Lung Association, personal fees for consultancy and involvement with contracted clinical trials for Boehringer Ingelheim, GlaxoSmithKline, AstraZeneca, PneumRx/BTG and Boston Scientific, involvement with contracted clinical trials for Novartis, Yungjin and Pulmonx, personal fees for consultancy from Genentech, Quark Pharmaceuticals and Mereo, outside the submitted work. Conflict of interest: M.K. Han reports personal fees from GSK, BI and AZ, non-financial support from Novartis and Sunovion, outside the submitted work. Conflict of interest: N.N. Hansel reports grants and personal fees for consultancy from AstraZeneca and GSK, grants from Boehringer Ingelheim, NIH and COPD Foundation, personal fees for consultancy from Mylan, outside the submitted work. Conflict of interest: E.A. Hoffman reports grants from NIH, during the conduct of the study; and is a founder and shareholder of VIDA Diagnostics, a company commercialising lung image analysis software developed, in part, at the University of Iowa. Conflict of interest: R.J. Kaner reports personal fees from Boehringer Ingelheim, Roche/Genentech, Medimmune/AstraZeneca, Gilead, Celgene and Janssen, outside the submitted work. Conflict of interest: R.E. Kanner has nothing to disclose. Conflict of interest: J.A. Krishnan has nothing to disclose. Conflict of interest: R. Paine III reports grants from NHLBI and COPD Foundation, during the conduct of the study; grants from Department of Veterans Affairs, outside the submitted work. Conflict of interest: S.P. Peters, reports grants from NIH, NHLBI as the PI of the Wake Forest Clinical Site for the SPIROMICS COPD Program, during the conduct of the study. Conflict of interest: S.I. Rennard is employed by AstraZeneca, Cambridge, UK and also retains Professorship and a part-time appointment at the the University of Nebraska Medical Center, Omaha, NE, USA. Conflict of interest: P.G. Woodruff reports personal fees for consultancy from Theravance, AstraZeneca, Regeneron, Sanofi, Genentech, Roche and Janssen, outside the submitted work. Conflict of interest: M. Arjomandi reports salary support from United States Department of Veterans Affairs, grants and salary support from United States National Institute of Health, during the conduct of the study.

Copyright ©ERS 2019.

Figures

FIGURE 1

Subject flow. CT: computed tomography; SVC: slow vital capacity; VCCT: CT-measured vital capacity; RVCT/TLCCT: CT-measured residual volume to total lung capacity ratio.

FIGURE 2

Correlation between computed tomography-measured residual volume to total lung capacity ratio (RVCT/TLCCT) and forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) or FEV1 in smokers with preserved spirometry. Boxplots show the distribution of RVCT/TLCCT (raw value) by 5% increments in FEV1/FVC % predicted (Panel a), and 5% increments in FEV1 % predicted (Panel b). Subjects were stratified into tertiles of RVCT/TLCCT represented by green, blue and magenta for low, intermediate, and high RVCT/TLCCT strata, respectively. The black line represents the regression line for all the points. r: correlation coefficient; rp: partial correlation, which is the correlation coefficient between the dependent variable and the targeted independent variable with the effect of other controlling random variables removed.

FIGURE 3

Comparison of change in spirometry from different SPIROMICS visits across CT-measured RV/TLC (RVCT/TLCCT) strata. Line graphs of FEV1/FVC values predicted from mixed-effect regression modelling (“fitted values”) through time across RVCT/TLCCT strata. Subjects were stratified into tertiles of RVCT/TLCCT represented by green, blue and magenta for low, intermediate and high RVCT/TLCCT tertiles, respectively. The tick marks on the x-axes represent the time that each spirometry was performed during the course of the study. Panel a shows the change in FEV1/FVC (predicted from the main model) and panel b shows the difference in rate of FEV1/FVC change per year (predicted from the spirometry follow-up time interaction model). FEV1: forced expiratory volume in 1 s; FVC: forced vital capacity.

FIGURE 4

Comparison of change in airflow indices on follow-up spirometry across CT-measured RV/TLC (RVCT/TLCCT) strata. Graphs represent means and 95% confidence intervals for change in airflow indices across RVCT/TLCCT strata relative to the reference group (subjects in the lowest tertile of RVCT/TLCCT) from mixed-effect linear regression modelling with adjustment for age, sex, height, weight, smoking status (former versus current), baseline lung function and time to follow-up spirometry. Subjects were stratified into tertiles of RVCT/TLCCT represented by green, blue and magenta for low, intermediate and high RVCT/TLCCT tertiles, respectively. Ref: reference value; FEV1: forced expiratory volume in 1 s; FVC: forced vital capacity; FEF25–75%: forced expiratory flow at 25–75% of FVC; FEF75%: forced expiratory flow at 75% of FVC.