International Journal of Chronic Obstructive Pulmonary Disease最新文献

Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition with limited response to standard anti-inflammatory therapies. Biologics targeting specific inflammatory pathways have emerged as potential treatments, but their efficacy remains variable across distinct COPD endotypes.

Objective: To systematically evaluate the efficacy and trial quality of biologics tested in COPD patients using a multicriteria decision analysis (MCDA) approach, with attention to type 2 (T2) and non-T2 inflammatory targets.

Methods: We assessed 20 trials encompassing 12 biologics and 9294 patients with COPD. Each trial was scored (0-3 per domain, total 12 points) across four domains: exacerbation reduction, lung function improvement, biomarker stratification, and trial design quality.

Results: Dupilumab (anti-IL-4Rα) demonstrated the most robust efficacy in eosinophilic COPD, with consistent reductions in exacerbation rates and improvements in FEV₁, supported by high trial quality. Mepolizumab and benralizumab (anti-IL-5/IL-5R) showed moderate efficacy in biomarker-enriched populations. Anti-alarmins, specifically tozorakimab (anti-IL-33), itepekimab (anti-IL-33/IL-1RL1), astegolimab (anti-ST2), and tezepelumab (anti-TSLP), showed mixed results, with modest lung function gains but largely non-significant effects on exacerbation rates. Agents targeting non-T2 pathways, including infliximab (anti-TNF-α), canakinumab (anti-IL-1β), MEDI8968 (anti-IL-1R1), CNTO6785 (anti-IL-17A), and ABX-IL8 (anti-IL-8), consistently failed to demonstrate clinical efficacy, often due to small sample sizes, early-phase design, and lack of biomarker stratification.

Conclusion: Biologics targeting T2 inflammation offer therapeutic promise in eosinophilic COPD when guided by biomarkers. Conversely, current biologics directed at non-T2 and alarmin pathways yield limited or inconsistent benefits, emphasizing the need for improved phenotyping and targeted intervention strategies in non-eosinophilic COPD.

Chronic Obstructive Pulmonary Disease (COPD) is a prevalent chronic respiratory disorder characterized by airway inflammation and irreversible airflow limitation. Its marked heterogeneity and complexity pose significant challenges to traditional clinical assessments in terms of prognostic prediction and personalized management. In recent years, the exploration of biomarkers has opened new avenues for the precise evaluation of COPD, particularly through multi-biomarker prediction models and integrative multimodal data strategies, which have substantially improved the accuracy and reliability of prognostic assessments. This review summarizes the key biomarkers associated with COPD prognosis, systematically discusses the practical applications and future potential of combined predictive models and multimodal data integration, and evaluates their translational value in clinical practice. As a narrative review, this study aims to provide a scientific foundation for the precision management of patients with COPD.

Purpose: This study aims to identify predictors of long-term survival in patients with chronic obstructive pulmonary disease (COPD) undergoing anatomical resections for non-small cell lung cancer (NSCLC), with focus on COPD severity, to improve perioperative risk stratification and patient care.

Patients and methods: This retrospective study included all patients with NSCLC and COPD undergoing anatomical resections at the Lung Tumor Center Munich between 2011 and 2020. COPD severity was classified by Global Initiative for Obstructive Lung Disease criteria: Group 1 (mild/moderate obstruction, COPD I-II) and Group 2 (severe obstruction, COPD III-IV). The relationship between COPD severity and perioperative parameters was analyzed using Kaplan-Meier and Cox proportional hazard model.

Results: Of 1663 NSCLC patients undergoing anatomical resections, 476 (28.6%) patients with COPD I-IV (40.5% female, median age 67.28 [60.57; 73.27] years) were included. No significant differences were observed between groups in demographics, topography, TNM classification, histology of the primary tumor, and surgical approach. Group 2 experienced more frequently prolonged mechanical ventilation >2 days (p=0.016), air leaks >5 days (p = 0.020), and arrhythmias (p=0.012). Median overall survival (OS) was reduced in Group 2 (43.73 [30.14; 57.33] vs 85.30 [67.46; 103.14] months, p=0.001). Independent predictors of reduced OS included COPD III-IV (p<0.0001), pT_3-4 (p=0.007), pN_1-2 (p<0.0001), preoperative CRP >0.6 mg/dL (p=0.014) and VO₂max <17 mL/min/kg (p=0.040). These predictors increased the risk of death by 1.6 [1.27-1.90], 1.3 [1.06-1.48], 2.1 [1.49-3.03], 1.6 [1.09-2.20] and 1. [1.02-2.00] fold, respectively.

Conclusion: COPD severity independently predicts perioperative morbidity and long-term survival in operable NSCLC patients. Comprehensive assessment of COPD severity can help in identifying high-risk patients and optimizing perioperative care.

Background: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. Previous studies have explored the relationship between different dietary patterns, systemic inflammation index (SII)and the risk of COPD. However, the joint effects and interactions between SII and HEI-2015 in COPD have not been fully investigated. This study aimed to explore the relationships between COPD and SII and HEI-2015.

Methods: Data from the National Health and Nutrition Examination Surveys (NHANES) were utilized.Univariate and multivariate logistic regression analyzed the associations between SII and HEI-2015 with COPD. Restricted cubic spline (RCS) model analyzed the relationship between SII and HEI-2015 and COPD.Use the area enclosed under the ROC curve (AUC) to represent its predicted value. Interaction indices and subgroup analyses were performed. The Kaplan-Meier curve was used to evaluate the impact on mortality of COPD patients.

Results: This study included 10,898 participants.After adjusting,logistic regression analysis showed that higher SII (OR=1.03, 95% CI: 1.01-1.05) were associated with an increased risk of COPD, while higher HEI-2015 (OR=0.97, 95% CI: 0.96-0.99) reduced the risk.The RCS model observed a non-linear relationship between SII and HEI-2015 and COPD risk. Additionally, ROC showed a more significant advantage in predicting COPD prevalence (AUC=0.68). Interaction analysis indicated that SII and HEI-2015 might be independent influencing factors for COPD risk. Kaplan-Meier survival curves showed a lower all-cause mortality rate among in the group with high SII and low HEI-2015 (p < 0.0001).

Conclusion: The results of this study indicate that a higher SII level and a lower HEI-2015 are associated with COPD risk. COPD patients with higher SII levels combined with lower HEI - 2015 levels have a higher all-cause death risk.

Purpose: The ASTER study described the management of chronic obstructive pulmonary disease (COPD) by general practitioners (GPs) in Italy, focusing on the treatment patterns and clinical outcomes of patients over 6 months.

Patients and methods: This multicenter prospective cohort study included patients aged 40-80 years with spirometry-confirmed COPD, post-bronchodilator FEV₁ ≥50% of predicted value, and ≤1 exacerbation in the previous year. Eligible patients had a COPD assessment test (CAT) score of ≥10 and, according to the prescription limits for GPs before Note 99, they could have been treated in the last 3 months before enrollment exclusively with a short or long acting bronchodilator or an corticosteroid/long-acting beta₂-agonist ICS/LABA. Patients were evaluated at enrollment, 3 months, and 6 months, with data collected on treatment, exacerbations, patient-reported outcomes (CAT and mMRC scores), and lung function.

Results: Overall, 385 patients were enrolled, and 344 (89.4%) met the study criteria, of which 332 (96.5%) completed the study. The cohort included patients with mild to moderate COPD, predominantly males (61.9%), and current/former smokers (91%). At baseline, ongoing treatments included LAMA (20.9%), ICS/LABA (13.7%), and LABA (2.9%). However, 62.5% of patients were not treated. By 6 months, only 10.2% of patients were not receiving any treatment and 55.4% were treated with a LABA/LAMA combination. FEV1 showed a mean increase of 140 mL, mMRC ≥ 2 decreased from 54.9% to 23.5%, CAT exhibited a 3.6 point mean decrease, and only 13 patients (3.9%) experienced mild/moderate exacerbations in the last 6 months.

Conclusion: ASTER study highlights the effectiveness of COPD treatment by GPs in Italy. Early detection and proactive management, along with a regular treatment prescription was associated with improved lung function, dyspnea, quality of life, and a reduction in the incidence of exacerbations. Empowering GPs with diagnostic and therapeutic responsibilities, improves care and outcomes of COPD.

Purpose: Chronic obstructive pulmonary disease (COPD) is associated with frailty and leads to poor outcomes. The relationship between COPD and cardiovascular events is well established. However, the impact of frailty on cardiovascular events in COPD patients remains unknown. We aimed to evaluate the long-term association between frailty, assessed using the hospital frailty risk score (HFRS), and major adverse cardiovascular events (MACE) in COPD patients.

Patients and methods: We recruited Japanese patients with COPD between 2013 and 2023 from Sado-Himawari Net, a regional electronic health record system in Sado City, Niigata Prefecture, Japan. MACE were defined as a composite of acute coronary syndrome, heart failure, and stroke. We classified the participants into four frailty categories according to HFRS: no-frailty with HFRS=0, low with HFRS >0 and <5, intermediate with HFRS ≥5 and <15, and high with HFRS ≥15. We used a Cox regression model adjusted for age, sex, inhaled treatments, and comorbidities to evaluate the hazard ratio (HR) for MACE.

Results: We recruited 1527 patients with COPD. In multivariable analysis, COPD was associated with MACE as follows: no-frailty versus low HFRS (HR, 1.47 [95% confidence interval, 1.01-2.14], p<0.05), intermediate HFRS (HR 2.00 [1.34-2.97], p<0.001), and high HFRS (HR 2.62 [1.50-4.59], p<0.001). Similar relationships were observed even after adjusting for the severity of airflow limitation and COPD exacerbation.

Conclusion: Frailty was independently associated with MACE in COPD patients during the 10-year follow-up period. Frailty assessment supports the identification of patients with COPD at risk of MACE.

Background: Cardiac arrhythmias are commonly seen in patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD), but their prevalence, risk factors, and prognostic significance are still not fully understood.

Objective: To estimate the prevalence of arrhythmias in patients with AECOPD, identify related clinical factors, and assess their influence on in-hospital mortality.

Methods: A systematic search of PubMed, Embase, Web of Science, CENTRAL, and Cochrane Reviews was conducted to identify observational studies and randomized controlled trials. A random-effects meta-analysis using the DerSimonian-Laird method was performed. Subgroup and sensitivity analyses were conducted to explore heterogeneity, and publication bias was assessed using Egger's and Begg's tests.

Results: Twenty-eight studies were included. The pooled prevalence of arrhythmias in AECOPD patients was 15% (95% CI: 12-18%), with considerable heterogeneity (I² = 99.93%). Prevalence was higher in studies from developed countries, particularly those with larger sample sizes and older populations. Advanced age (WMD = 2.79 years) and elevated C-reactive protein levels (WMD = 5.32) were associated with increased arrhythmia risk. Use of long-acting beta-agonists (LABAs) was associated with a reduced risk (OR = 0.42), although the causal mechanism remains uncertain. Arrhythmias were significantly associated with increased in-hospital mortality (RR = 3.33, 95% CI: 3.27-3.38). In a predefined subgroup analysis, atrial fibrillation (AF) was also linked to a higher risk of death (RR = 3.70, 95% CI: 2.40-5.70). Sensitivity analyses confirmed the robustness of these findings, and no significant publication bias was detected.

Conclusion: Arrhythmias are common during AECOPD and are associated with increased short-term mortality, especially in patients with AF. Aging and systemic inflammation appear to be key contributors. While LABA use may have a protective association, this finding requires cautious interpretation. Standardized ECG monitoring and individualized risk stratification are warranted to improve patient outcomes.

Background: Chronic obstructive pulmonary disease (COPD) is a major health concern in Korea, with a higher burden of acute exacerbations (AE-COPD) compared to Western populations. Environmental exposures such as smoking and air pollution are known contributors, but the impact of urban green space remains underexplored.

Methods: We conducted a cohort study using the Korean National Health Insurance Service-National Sample Cohort (2006-2019), including 5,171 patients aged ≥40 years with at least two COPD-related prescriptions within one year. Urban green space exposure was defined as the proportion of designated park area to total district area (2017 KOSIS data) and categorized into quartiles. Cox proportional hazards models estimated associations with AE-COPD and all-cause mortality, adjusting for demographic and clinical factors. Subgroup analyses were conducted by age, sex, income, comorbidities, BMI, smoking, and physical activity.

Results: Among 5,171 COPD patients (mean age, 67.5 years; 60.7% male), 1,431 AE-COPD events occurred over 40,486 person-years. AE-COPD incidence declined from 35.4 to 31.3 per 1,000 person-years across green space quartiles. Compared to the lowest quartile, the highest quartile showed a lower AE-COPD risk (adjusted hazard ratio [aHR], 0.75; 95% CI, 0.58-0.96; p for trend = 0.016). Stronger trends were observed in younger adults, men, high-income individuals, and those with comorbidities, though interaction tests were not significant. In a health screening subgroup (n = 3,318), patterns were consistent. No significant association was found with all-cause mortality.

Conclusion: Greater urban green space coverage may be associated with reduced AE-COPD risk. However, results should be interpreted with cautiously given model limitations and exploratory nature of subgroup findings.

Objective: This study aimed to develop and validate a deep learning radiomics (DLR) nomogram for individualized CHD risk assessment in the COPD population.

Methods: This retrospective study included 543 COPD patients from two different centers. Comprehensive clinical and imaging data were collected for all participants. In Center 1, 398 patients were randomly allocated into a training set and an internal validation set at a 7:3 ratio. An external test set was established using 145 patients from Center 2. Radiomics features were extracted from computed tomography (CT) images, and deep learning features were generated using ResNet50. By integrating traditional clinical data, radiomics features, and three-dimensional (3D) deep learning features, a combined predictive model was developed to estimate the risk of CHD in COPD patients.

Results: Validation cohort AUCs revealed the nomogram's optimal predictive performance (Internal: 0.800; External: 0.761) compared to clinical (0.759, 0.661), radiomics (0.752, 0.666), and DLR (0.767, 0.732) models. This integrative approach demonstrated a 9.1% and 13.4% relative AUC improvement over clinical and radiomics models in external validation. DCA corroborated these findings, showing the nomogram provides the highest net benefit for clinical decision-making across probability thresholds in COPD patients at risk for CHD.

Conclusion: The nomogram model, which integrates clinical, radiomics, and deep learning features, exhibits promising performance in predicting CHD risk among COPD patients. It may offer valuable insights for early intervention and management strategies for CHD.

Background: Chronic obstructive pulmonary disease (COPD) frequently co-occurs with autoimmune diseases (ADs), yet their shared genetic basis remains incompletely understood. This study aimed to evaluate genetic correlations between COPD and seven ADs and identify shared genetic risk loci underlying this comorbidity.

Methods: We integrated summary statistics from large-scale genome-wide association studies (GWAS) of COPD and seven ADs in European populations. Genetic correlations were assessed using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL). Pleiotropic loci were identified via the Pleiotropic Analysis under Composite Null Hypothesis (PLACO) and annotated through the FUMA platform. Multidimensional enrichment analyses were conducted using MAGMA and Metascape, and complementary evidence for the identification of pleiotropic genes was provided by summary-based Mendelian randomization (SMR) and transcriptome-wide association studies (TWAS).

Results: Significant genetic correlations were observed between COPD and five of the seven ADs analyzed. Joint analyses identified 57 shared risk loci, including 17q12 and 16p11.2, with 22 loci supported by colocalization evidence. MAGMA identified 162 pleiotropic genes, such as ORMDL3, GSDMB, and MAPK3. Pathway analyses demonstrated enrichment in immune-related processes, particularly T cell activation and regulation of immune responses. SMR and TWAS further implicated ORMDL3, PGAP3, MAPK3, and GMPPB as putative contributors to shared disease susceptibility. However, additional experimental validation is warranted to substantiate these associations.

Conclusion: This study highlights shared genetic loci and immune pathways linking COPD and ADs in European ancestry populations. Findings lay the groundwork for future research but require functional validation and replication in diverse cohorts to establish causality.