Clinical Indicators for Asthma-COPD Overlap: A Systematic Review and Meta-Analysis

Asthma and chronic obstructive pulmonary disease (COPD) are distinct respiratory conditions, but some patients exhibit features of both, known as asthma-COPD overlap (ACO). Identifying ACO is clinically important because treatment strategies differ between asthma, COPD, and ACO. Prior research has shown that certain clinical indicators may distinguish ACO from pure asthma or COPD, but findings have been inconsistent. This gap motivated a systematic review and meta-analysis to clarify which indicators are most useful for diagnosing ACO. The study aimed to synthesize evidence from multiple sources to provide a clearer diagnostic framework. No prior work had resolved the variability in reported indicators for ACO. This uncertainty drove the need for a comprehensive analysis of available data. The lack of consensus in clinical indicators has limited the accuracy of ACO diagnosis. This review sought to address that limitation by evaluating a wide range of potential markers. The goal was to determine which indicators consistently differentiate ACO from asthma or COPD. The findings could help clinicians make more informed decisions in diagnosing and managing ACO.

The purpose of this study was to evaluate the diagnostic value of various clinical indicators for asthma-COPD overlap (ACO). The researchers aimed to determine which indicators are most effective in distinguishing ACO from pure asthma or COPD. They focused on respiratory function tests, inflammatory markers, and immunological parameters. The motivation for this work was the lack of consensus in clinical indicators for ACO diagnosis. Prior studies had produced conflicting results, making it difficult to establish a reliable diagnostic framework. The researchers sought to synthesize the available evidence to provide clearer guidance for clinicians. By pooling data from multiple studies, they aimed to increase the reliability of their findings. The study also aimed to assess the consistency of reported indicators across different populations and settings. The goal was to identify a set of indicators that could be used confidently in clinical practice.

The researchers conducted a systematic review and meta-analysis to evaluate clinical indicators for asthma-COPD overlap (ACO). They searched multiple databases, including PubMed, EMBASE, Ovid, and Web of Science, to identify relevant studies. Inclusion criteria focused on studies that reported clinical indicators for ACO compared to asthma or COPD. The researchers used random-effects models to calculate pooled standardized mean differences (SMDs) with 95% confidence intervals (CIs). This approach allowed them to account for variability between studies. They analyzed respiratory function tests, inflammatory markers, and immunological parameters. The study design ensured that results were weighted by study quality and sample size. The meta-analysis included 48 eligible studies, providing a broad dataset for analysis. The methods emphasized transparency and reproducibility by following standard systematic review protocols.

The study found that asthma-COPD overlap (ACO) patients had lower levels of forced expiratory volume in the first second (FEV1)% predicted compared to pure asthma patients. The pooled standardized mean difference (SMD) was -1.09 with a 95% confidence interval of -1.3 to -0.87. ACO patients also had lower diffusion lung capacity for carbon monoxide (DLCO)% predicted (SMD = -0.83, 95% CI -1.24 to -0.42). Fractional exhaled nitric oxide (FeNO) levels were lower in ACO compared to asthma (SMD = -0.23, 95% CI -0.36 to -0.11). Induced sputum neutrophil levels were higher in ACO compared to asthma (SMD = 0.51, 95% CI 0.21 to 0.81). Circulating YKL-40 levels were elevated in ACO compared to asthma (SMD = 0.96, 95% CI 0.27 to 1.64). Relative to COPD alone, ACO patients had higher FEV1% predicted (SMD = 0.15, 95% CI 0.05 to 0.26). DLCO% predicted was also higher in ACO compared to COPD (SMD = 0.38, 95% CI 0.16 to 0.6).

The authors concluded that asthma-COPD overlap (ACO) patients have distinct clinical profiles compared to those with pure asthma or COPD. The findings suggest that FEV1% predicted, DLCO% predicted, FeNO, serum total IgE, blood eosinophils, induced sputum eosinophils, and circulating YKL-40 may be useful indicators for diagnosing ACO. These markers could help clinicians differentiate ACO from asthma or COPD. The results highlight the importance of using a combination of clinical indicators rather than relying on a single parameter. The study supports the use of standardized mean differences to quantify differences between groups. The authors propose that these findings may inform future clinical guidelines for diagnosing ACO. However, they caution that these indicators should be interpreted in the context of a patient’s overall clinical presentation. The study does not claim that these markers are essential for diagnosis but suggests they may be helpful in clinical decision-making.