Functional Predictors Discriminating Asthma–COPD Overlap (ACO) from Chronic Obstructive Pulmonary Disease (COPD)

Abstract

Background

A significant proportion of patients with obstructive lung disease have clinical and functional features of both asthma and chronic obstructive pulmonary disease (COPD), referred to as the asthma–COPD overlap (ACO). The distinction of these phenotypes, however, is not yet well-established due to the lack of defining clinical and/or functional criteria. The aim of our investigations was to assess the discriminating power of various lung function parameters on the assessment of ACO.

Methods

From databases of 4 pulmonary centers, a total of 540 patients (231 males, 309 females), including 372 patients with asthma, 77 patients with ACO and 91 patients with COPD, were retrospectively collected, and gradients among combinations of explanatory variables of spirometric (FEV₁, FEV₁/FVC, FEF_25-75), plethysmographic (sR_eff, sG_eff, the aerodynamic work of breathing at rest; sWOB), static lung volumes, including trapped gases and measurements of the carbon monoxide transfer (DL_CO, K_CO) were explored using multiple factor analysis (MFA). The discriminating power of lung function parameters with respect to ACO was assessed using linear discriminant analysis (LDA).

Results

LDA revealed that parameters of airway dynamics (sWOB, sR_eff, sG_eff) combined with parameters of static lung volumes such as functional residual capacity (FRC_pleth) and trapped gas at FRC (V_TG^FRC) are valuable and potentially important tools discriminating between asthma, ACO and COPD. Moreover, sWOB significantly contributes to the diagnosis of obstructive airway diseases, independent from the state of pulmonary hyperinflation, whilst the diffusion capacity for carbon monoxide (DL_CO) significantly differentiates between the 3 diagnostic classes.

Conclusion

The complexity of COPD with its components of interaction and their heterogeneity, especially in discrimination from ACO, may well be differentiated if patients are explored by a whole set of target parameters evaluating, interactionally, flow limitation, airway dynamics, pulmonary hyperinflation, small airways dysfunction and gas exchange disturbances assessing specific functional deficits.

Keywords:

• COPD
• COPD and coexisting asthma
• ACO
• aerodynamic work of breathing
• airway dynamics
• pulmonary hyperinflation
• small airways dysfunction
• precision medicine
• multiple factor analysis
• MFA
• linear discriminant analysis
• LDA

Abbreviations

ACO, asthma–COPD overlap; ATS, American Thoracic Society; AUC, area under the curve (ROC analysis); BDR, bronchodilator response; COPD, chronic obstructive pulmonary disease; DL_CO, carbon monoxide diffusion capacity; ∆V_pleth, plethysmographic shift volume: EELV, end-expiratory lung volume; ERS, European Respiratory Society; FEF_25-75, forced expiratory flow between 25 and 75% vital capacity; FeNO, fraction of exhaled nitric oxide; FEV₁, forced expiratory volume in 1 second; FVC, forced vital capacity; FRC_pleth, plethysmographic functional residual capacity; FRC_He, functional residual capacity obtained by helium dilution technique; FVC, forced vital capacity; IC, inspiratory capacity; KCO, carbon monoxide transfer factor; LDA, linear discriminant analysis; LLN, loser limit of normal; Ln, natural logarithm; MFA, multiple factor analysis; MMEF, maximal mid-expiratory flow; P_amb, ambient pressure; P_H2O, water pressure; PHI, pulmonary hyperinflation; ROC, receiver operating characteristics; RV_He, total lung capacity obtained by helium dilution technique; RV_pleth, plethysmographic residual volume; SAD, small airways dysfunction; SD, standard deviation; sG_aw, specific airway conductance (angle method); sG_eff, effective specific airway conductance (integral method); sR_eff, effective specific airway resistance (integral method); sWOB, effective resistive work of breathing (integral method); TLC_He, total lung capacity obtained by helium dilution technique; TLC_pleth, plethysmographic total lung capacity; ULN, upper limit of normal; VC, vital capacity; VIF, variance inflation factor; V’, flow; V_T, tidal volume; V_TG^TLC, trapped gas on the level TLC, defined as TLC_pleth – TLC_HE; V_TG^FRC, trapped gas on the level FRC, defined as FRC_pleth – FRC_HE; V_TG^RV, trapped gas on the level RV, defined as RV_pleth – RV_HE.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Informed Consent

The study was planned according to the Federal Law of Human Research, conceptualized by the Swiss Ethics Committee on Research involving humans, and approved by the Governmental Ethics Committees of the State of Berne, Zürich, and St. Gallen. Master-files have been stored and secured in the REDCap-system of the Clinical Trial Unit, Medical Faculty, University of Berne, Switzerland. Written informed consent was waived because of the retrospective study design, which is following the institutional and national policies concerning research approvals.

Acknowledgment

We are grateful to the staff of all study centers, especially to the study nurses for their excellent and enduring work in data collection, and we would like to thank Prof. Sabina Gallati from Human Genetics of Hirslanden Precise, Zürich, for the critical reviews of the manuscript.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors have no conflicts of interests to declare in this work.

Additional information

Funding

No funding was received.