The present retrospective observational study evaluated the patients who were regularly followed up for COPD management at a teaching hospital from January 2004 and December 2019. Diagnosis of COPD was made by pulmonologists based on chronic respiratory symptoms, risk factors, and non-fully reversible airflow limitation (post-bronchodilator forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) ratio <0.7). The inclusion criteria comprised patients with: (1) baseline chest computed tomography (CT), (2) baseline and follow-up spirometric assessments, and (3) hospital visits over a 5-year observation period. We excluded the patients who currently had asthma or interstitial lung disease at baseline assessment. The eligible patients were categorized into two groups according to the presence of mucus plug: (1) the no mucus plug group and (2) the mucus plug group. For sensitivity analyses, eligible patients were further categorized based on mucus plug scores of 0, 1–2, and ≥3.

Demographic and clinical characteristics were collected as baseline variables for analysis. These included age, sex, body mass index (BMI), smoking history (current smoking status and pack-years for ever-smokers), underlying medical conditions, respiratory comorbidities, severity of symptom (Modified Medical Research Council [mMRC] grade and COPD assessment test [CAT] score), GOLD group classification (A, B, E), complete blood count, pulmonary function profiles (post-bronchodilator FEV1, FVC, FEV1/FVC ratio, and FEF25–75%), as well as details regarding inhaled therapies.

Blood eosinophil count (BEC) was routinely measured as part of the complete blood count with differential at the point of exacerbation, both in outpatient and inpatient settings. Baseline BEC was obtained from routine blood tests conducted at the time of COPD diagnosis, performed at least two weeks after stabilization and in the absence of recent treatment with oral corticosteroids.

The CT scan protocol was consistent across different periods, maintaining uniformity in the imaging technique. Chest CT scans were performed using a 16-channel multi-detector CT (MDCT) (LightSpeed, GE Healthcare), a 64-channel MDCT (Brilliance, Philips Medical Systems, Cleveland, Ohio), or a 128-channel CT scanner (Ingenuity, Philips Medical Systems, the Netherlands). Radiologic data was acquired in the cranio-caudal direction with a peak voltage of 120kV. The effective milliampere-second ranged between 150 and 200, utilizing an automatic tube current modulation technique.

The mucus plug score was determined by tallying the count of lung segments exhibiting mucus plugs that entirely obstruct middle-to-large-sized airways (approximately 2–10-mm lumen diameter). The presence of mucus plugs was documented in each lobe, with the lingula treated as an independent lobe. Scores range from 0 (indicating no mucus plugs observed in any lung segments) to 18 (suggesting all lung segments are affected). The bronchial classification comprises 18 lung segments, with the right lung having 3, 2, and 5 segments in the upper, middle, and lower lobes, respectively, and the left lung having 2, 2, and 4 segments in the upper lobe, lingula, and lower lobe, respectively. The presence of mucus plugs was specifically defined as a mucus plug score equal to or greater than 1.

Upon scrutinizing baseline chest CT scans, the mucus plug was first identified in each bronchopulmonary segment by thoracic radiologists. A random selection of 100 scans with mucus plugs and 100 scans without mucus plugs were independently assessed by a thoracic radiologist (KNJ) and a pulmonologist (HWL) using the previously described methodology.13 The two readers evaluated the mucus plug scores, and calibration was conducted through discussion until the inter-reader agreement's correlation coefficient reached 0.9 or higher. Subsequently, the mucus plug score was evaluated for the entire chest CT scan. Any disagreements related to the assessment of the mucus plug score were resolved through discussion between the two investigators.

The primary outcomes of interest encompassed exacerbation rates and time to exacerbation events, categorized into moderate-to-severe, severe, eosinophilic, and non-eosinophilic exacerbations. A moderate exacerbation was defined as a flare-up of COPD symptoms requiring antibiotics or systemic corticosteroids. A severe exacerbation was characterized by hospitalization or emergency room visits due to a flare-up of COPD symptoms. Eosinophilic exacerbations were defined by a blood eosinophil count ≥300/μL at the onset of exacerbation, while non-eosinophilic exacerbations were identified by a blood eosinophil count <300/μL. Subgroup analyses were conducted to evaluate hazard ratios for different exacerbation types based on various clinical phenotypes or inhaled therapies. As a secondary outcome, the decline in FEV1 over a 5-year period was assessed.

We collected annual FEV1 values during the 5-year follow-up period. To address any missing values in the annual FEV1 dataset, we employed linear interpolation or extrapolation for imputation. The beta-coefficient, indicative of the linear regression slope, was estimated for each individual by utilizing all available follow-up FEV1 values from the baseline examination to the last follow-up.

In the baseline characteristics, continuous variables were compared using the t-test or Wilcoxon signed-rank test, while categorical variables were compared using the chi-squared test or Fisher's exact test. Propensity-score matching (PSM) was employed to reduce potential confounding and achieve balance between the groups with and without mucus plugs. PSM was performed using the MatchIt package in R. The propensity-score was calculated using logistic regression, with the presence of CT-detected mucus plugs as the dependent variable. The covariables included in the model were age, sex, BMI, smoking history (current smoking status and pack-years for ever-smokers), follow-up duration, comorbidities (heart failure, chronic liver disease, diabetes mellitus, chronic kidney disease, Charlson comorbidity index), respiratory conditions (asthma, pulmonary tuberculosis, non-tuberculous mycobacterial pulmonary disease, bronchiectasis, TB-destroyed lung, and interstitial lung disease), COPD related symptoms (cough, sputum production, dyspnea, CAT scores, and mMRC scale), exacerbation history, GOLD classification, blood test results, pulmonary function test results, and inhaled therapy. Matching was performed using the nearest neighbor method with a caliper of 0.1 and a 1:1 ratio to minimize differences between the mucus plug and no mucus plug groups. This process resulted in 187 patients in each group, based on the availability of suitable matches. The balance of covariables between the matched groups was assessed using standardized mean differences (SMD), with an SMD of less than 0.1 indicating a negligible difference.

Exacerbation rates were compared using chi-squared tests, and time to exacerbation events was analyzed using Kaplan–Meier curves. Hazard ratios for exacerbations were calculated using Cox proportional hazards models. For the multivariable Cox regression analysis, stepwise selection using AIC was employed to identify the optimal set of variables. This method was implemented using the stepAIC function from the MASS package in R, which performs both forward and backward selection to balance model fit and complexity. Subgroup analyses were conducted to explore the impact of mucus plugs on exacerbations in specific patient subgroups. The annual decline in FEV1 was analyzed using repeated measures two-way ANOVA and linear mixed-effect models. All statistical analyses were performed using a predefined significance level (P-value<0.05), and results were reported with 95% confidence intervals.

The demographic characteristics and clinical features of the total study population are delineated in Table 1. Significant differences were observed between the no mucus plug group and the mucus plug group across multiple parameters. Propensity-score matching balanced these disparities in the matched population (187 patients per group), with a median age of 68 years, predominantly male composition, and a median BMI of 22.

In the propensity score-matched population, the mucus plug group experienced more moderate-to-severe exacerbations (89 [47.6%] vs. 109 [58.3%], P-value=0.049) and severe exacerbations (47 [25.1%] vs. 77 [41.2%], P-value=0.002) than the no mucus plug group. The annual rate of moderate-to-severe exacerbations was significantly higher in the mucus plug group (0.51event/year vs. 0.58event/year, P-value=0.035; Fig. 2). Additionally, the mucus plug group exhibited a significantly higher rate of severe exacerbations (0.21event/year vs. 0.24event/year, P-value=0.032).

Fig. 2.

Annual rate of exacerbation according to mucus plug presence in the propensity score-matched population.

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The mucus plug group experienced more non-eosinophilic exacerbations (73 [39.0%] vs. 97 [51.9%], P-value=0.017) compared to the no mucus plug group, while eosinophilic exacerbations were comparable. The annual rate of non-eosinophilic exacerbations was significantly higher in the mucus plug group (0.45event/year vs. 0.52event/year, P-value=0.008). However, the risk of eosinophilic exacerbations did not significantly differ between the two groups (P-value=0.440).

In the Kaplan–Meier curve, the mucus plug group demonstrated a shortened time to moderate-to-severe exacerbations (P-value=0.040) and severe exacerbations (P-value=0.001) compared to the no mucus plug group (Fig. 3). The mucus plug group also showed a shortened time to non-eosinophilic exacerbations (P-value=0.009), but there was no significant difference in the time to eosinophilic exacerbation events between the two groups. Conversely, eosinophilic exacerbations tended to occur less frequently in the mucus plug group, as observed in the total population (Supplementary Information 2). Especially, mucus plug score of ≥3 showed a significant increase in both moderate-to-severe exacerbation (P-value=0.040), severe exacerbation (P-value<0.001), and non-eosinophilic exacerbation (P-value=0.026) in comparison to those with mucus plug score of 0 (Fig. 4).

Fig. 3.

Time to exacerbation event according to the presence or absence of mucus plug in the propensity score-matched population.

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Fig. 4.

Time to exacerbation event according to the mucus plug scores in the propensity score-matched population.

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Mucus plug presence was associated with an increased hazard for moderate-to-severe exacerbations (HR=1.343 [95% CI, 1.015–1.777]), severe exacerbations (HR=1.769 [95% CI, 1.231–2.543]), and non-eosinophilic exacerbations (HR=1.494 [95% CI, 1.102–2.024]) (Supplementary Information 3–5). However, the hazard for eosinophilic exacerbations was decreased in the mucus plug group without statistical significance (HR=0.747 [95% CI, 0.354–1.580], Supplementary Information 6).

In subgroup analyses, an elevated risk of these exacerbations was observed in COPD patients with chronic bronchitis, emphysema, high blood neutrophil count (≥5000/μL), low blood lymphocyte count (<2000/μL), high blood neutrophil/lymphocyte ratio (NLR) (≥2.3), or low blood eosinophil count (<300/μL or <100/μL). Additionally, among patients using ICS/LABA/LAMA, the hazard of non-eosinophilic exacerbations was significantly increased in those with mucus plug. In COPD patients with a history of asthma or a low blood NLR, or those using ICS/LABA, there was a tendency for an increase in eosinophilic exacerbations in the presence of mucus plug, although statistical significance was not reached.

In multivariable Cox regression model, the presence of mucus plugs was related with an increased hazard for moderate-to-severe exacerbation (adjusted HR=1.502 [95% CI 1.116–2.020]), severe exacerbation (adjusted HR=2.106 [95% CI, 1.429–3.103]), and non-eosinophilic exacerbation (adjusted HR=1.551 [95% CI, 1.132–2.125]), while it is not significantly associated with eosinophilic exacerbation (Supplementary Information 7).

In the analysis according to mucus plug score, mucus plug score of ≥3 is significantly associated with an increased hazard of moderate-to-severe exacerbation, severe exacerbation, and non-eosinophilic exacerbation compared to mucus plug score of ≥0 (Supplementary Information 8).

The median change in FEV1 over 5 years was −50 (interquartile range [IQR], −468 to 265) mL in the no mucus plug group and −122 (IQR, −450 to 185) mL in the mucus plug group (Fig. 5). The annual FEV1 decline was significantly higher in the mucus plug group (repeated measures two-way ANOVA, P-value=0.014). In linear mixed-effect model, annual FEV1 decline rate (mL/year) was significantly accelerated in the mucus plug group (β-coefficient=−62 [95% CI, −120 to −5], P-value=0.035). In particular, a mucus plug score of ≥3 demonstrated a significant association with an accelerated decline in FEV1 compared to a mucus plug score of 0 (β-coefficient=−79 [95% CI, −148 to −10], P-value=0.026). However, there was no statistically significant difference observed for mucus plug scores of 1–2 (β-coefficient=−43 [95% CI, −116 to 29], P-value=0.241).

Fig. 5.

Annual rate of FEV1 change according to mucus plug presence in the propensity score-matched population. FEV1, forced expiratory volume in one second.

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