Prediction of air trapping or pulmonary hyperinflation by forced spirometry in COPD patients: results from COSYCONET

Peter Alter, Jan Orszag, Christina Kellerer, Kathrin Kahnert, Tim Speicher, Henrik Watz, Robert Bals, Tobias Welte, Claus F Vogelmeier, Rudolf A Jörres, Peter Alter, Jan Orszag, Christina Kellerer, Kathrin Kahnert, Tim Speicher, Henrik Watz, Robert Bals, Tobias Welte, Claus F Vogelmeier, Rudolf A Jörres

Abstract

Background: Air trapping and lung hyperinflation are major determinants of prognosis and response to therapy in chronic obstructive pulmonary disease (COPD). They are often determined by body plethysmography, which has limited availability, and so the question arises as to what extent they can be estimated via spirometry.

Methods: We used data from visits 1-5 of the COPD cohort COSYCONET. Predictive parameters were derived from visit 1 data, while visit 2-5 data was used to assess reproducibility. Pooled data then yielded prediction models including sex, age, height, and body mass index as covariates. Hyperinflation was defined as ratio of residual volume (RV) to total lung capacity (TLC) above the upper limit of normal. (ClinicalTrials.gov identifier: NCT01245933).

Results: Visit 1 data from 1988 patients (Global Initiative for Chronic Obstructive Lung Disease grades 1-4, n=187, 847, 766, 188, respectively) were available for analysis (n=1231 males, 757 females; mean±sd age 65.1±8.4 years; forced expiratory volume in 1 s (FEV1) 53.1±18.4 % predicted (% pred); forced vital capacity (FVC) 78.8±18.8 % pred; RV/TLC 0.547±0.107). In total, 7157 datasets were analysed. Among measures of hyperinflation, RV/TLC showed the closest relationship to FEV1 % pred and FVC % pred, which were sufficient for prediction. Their relationship to RV/TLC could be depicted in nomograms. Even when neglecting covariates, hyperinflation was predicted by FEV1 % pred, FVC % pred or their combination with an area under the curve of 0.870, 0.864 and 0.889, respectively.

Conclusions: The degree of air trapping/hyperinflation in terms of RV/TLC can be estimated in a simple manner from forced spirometry, with an accuracy sufficient for inferring the presence of hyperinflation. This may be useful for clinical settings, where body plethysmography is not available.

Conflict of interest statement

Conflict of interest: P. Alter reports grants from German Federal Ministry of Education and Research (BMBF) Competence Network Asthma and COPD (ASCONET); grants from AstraZeneca GmbH; grants and nonfinancial support from Bayer Schering Pharma AG; grants, personal fees and nonfinancial support from Boehringer Ingelheim Pharma GmbH & Co. KG; grants and nonfinancial support from Chiesi GmbH; grants from GlaxoSmithKline; grants from Grifols Deutschland GmbH; grants from MSD Sharp & Dohme GmbH; grants and personal fees from Mundipharma GmbH; grants, personal fees and nonfinancial support from Novartis Deutschland GmbH; and grants from Pfizer Pharma GmbH; grants from Takeda Pharma Vertrieb GmbH & Co. KG, all outside the submitted work. Conflict of interest: J. Orszag has nothing to disclose. Conflict of interest: C. Kellerer has nothing to disclose. Conflict of interest: K. Kahnert has nothing to disclose Conflict of interest: T. Speicher has nothing to disclose. Conflict of interest: H. Watz has nothing to disclose. Conflict of interest: R. Bals reports grants and personal fees from AstraZeneca; grants and personal fees from Boehringer Ingelheim; personal fees from GlaxoSmithKline; personal fees from Grifols; grants and personal fees from Novartis; personal fees from CSL Behring; grants from German Federal Ministry of Education and Research (BMBF) Competence Network Asthma and COPD (ASCONET); grants from Sander Stiftung; grants from Schwiete Stiftung; grants from Krebshilfe; and grants from Mukoviszidose eV, all outside the submitted work. Conflict of interest: T. Welte reports grants from the German Ministry of Research and Education during the conduct of the study, and personal fees from Novartis and Boehringer Ingelheim outside the submitted work. Conflict of interest: C.F. Vogelmeier reports grants and personal fees from AstraZeneca; grants and personal fees from Boehringer Ingelheim; personal fees from CSL Behring; personal fees from Chiesi; grants and personal fees from GlaxoSmithKline; grants and personal fees from Grifols; personal fees from Menarini; personal fees from Mundipharma; grants and personal fees from Novartis; personal fees from Nuvaira; personal fees from OmniaMed; and personal fees from MedUpdate, all outside the submitted work. Conflict of interest: R.A. Jörres reports grants from German Federal Ministry of Education and Research (BMBF) Competence Network Asthma and COPD (ASCONET); grants from AstraZeneca GmbH; grants from Bayer Schering Pharma AG; grants and personal fees from Boehringer Ingelheim Pharma GmbH & Co. KG; grants from Chiesi GmbH; grants and personal fees from GlaxoSmithKline; grants from Grifols Deutschland GmbH; grants from MSD Sharp & Dohme GmbH; grants and personal fees from Mundipharma GmbH; grants and personal fees from Novartis Deutschland GmbH; grants from Pfizer Pharma GmbH; grants from Takeda Pharma Vertrieb GmbH & Co. KG; personal fees from Custo Med GmbH; personal fees from Bosch; personal fees from Siemens; and grants and personal fees from Lufthansa, all outside the submitted work.

Copyright ©ERS 2020.

Figures

FIGURE 1
FIGURE 1
Nomograms in a) males and b) females obtained as in supplementary figure S2, whereby the covariates age, body mass index and height were omitted (i.e. only forced expiratory volume in 1 s (FEV1) % predicted and forced vital capacity (FVC) % predicted were used for prediction of residual volume/total lung capacity).
FIGURE 2
FIGURE 2
Nomograms in a) males and b) females for the prediction of clinically significant air trapping/hyperinflation (residual volume/total lung capacity>upper limit of normal (ULN)) as obtained from the mixed model based on forced expiratory volume in 1 s (FEV1) percentage predicted (% pred) and forced vital capacity (FVC) % pred as predictors, including age, height and body mass index (BMI) as covariates (yellow area). The prediction equations used are the same as those used in supplementary figure S2 and shown in table 2. For the nomogram, a BMI of 25 kg·m−2 was assumed for both sexes, a height of 175 cm for males, and of 165 cm for females. The different lines refer to different values of age. If the patient's combination of FEV1 % pred and FVC % pred is located on the left side of the line for the patient's age, this indicates significant hyperinflation, otherwise not.
FIGURE 3
FIGURE 3
Receiver operating characteristics showing the predictive value of forced expiratory volume in 1 s (FEV1) percentage predicted (% pred) and forced vital capacity (FVC) % pred alone and in combination, as well as the full model including age, height and body mass index as covariates to estimate hyperinflation as defined by an residual volume/total lung capacity ratio above the upper limit of normal. Data from males and females are combined. The results for the a) total population, b) patients of Global Initiative for Chronic Obstructive Lung Disease (GOLD) grades 1 and 2 only.

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Source: PubMed

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