Predictive modeling of COPD exacerbation rates using baseline risk factors

Urban-rural and socio-economic differences in inhaled corticosteroid treatment for chronic obstructive pulmonary disease: A nationwide register-based cross-sectional study

BACKGROUND

Urban-rural disparities within chronic obstructive pulmonary disease (COPD) have been documented in USA, but not in Europe. Inhaled corticosteroids (ICS) are widely used in COPD despite strict recommendations. We aimed to investigate urban-rural and socioeconomic differences in ICS treatment for COPD.

METHODS

A Danish nationwide register-based cross-sectional study. All patients alive on the December 31, 2018 with a J44 ICD-10 diagnosis code (COPD) were included (99,057 patients). Daily average ICS dose was calculated from the accumulated ICS use during 2018 based on redeemed prescriptions. Patients were divided into groups: No ICS, low dose ICS, medium dose ICS, high dose ICS. A multinomial logistic regression model including educational level, co-habitation status, age, and sex was performed with "No ICS" as reference group.

RESULTS

Compared to capital municipalities, living in other municipality types was associated with an increased probability of receiving medium and high dose ICS treatment, and increasing odds ratios (ORs) were seen with increasing ICS dose (medium dose ICS: ORs between 1.31 (95 % confidence interval (CI) 1.24-1.38) and 1.35 (95%CI 1.28-1.41), high dose ICS: ORs between 1.73 (95%CI 1.59-1.88) and 1.80 (95%CI 1.68-1.92)). Patients had increased probability of receiving ICS treatment if they were female, were co-habiting, or had completed only primary education.

CONCLUSION

Patients with a hospital-registered COPD diagnosis in non-capital municipalities receive more ICS, and in higher doses, compared to patients in capital municipalities. This is the first study to confirm that such urban-rural differences exist in Europe, and further research on this area is warranted.

Acute exacerbation prediction of COPD based on Auto-metric graph neural network with inspiratory and expiratory chest CT images

Chronic obstructive pulmonary disease (COPD) is a widely prevalent disease with significant mortality and disability rates and has become the third leading cause of death globally. Patients with acute exacerbation of COPD (AECOPD) often substantially suffer deterioration and death. Therefore, COPD patients deserve special consideration regarding treatment in this fragile population for pre-clinical health management. Based on the above, this paper proposes an AECOPD prediction model based on the Auto-Metric Graph Neural Network (AMGNN) using inspiratory and expiratory chest low-dose CT images. This study was approved by the ethics committee in the First Affiliated Hospital of Guangzhou Medical University. Subsequently, 202 COPD patients with inspiratory and expiratory chest CT Images and their annual number of AECOPD were collected after the exclusion. First, the inspiratory and expiratory lung parenchyma images of the 202 COPD patients are extracted using a trained ResU-Net. Then, inspiratory and expiratory lung Radiomics and CNN features are extracted from the 202 inspiratory and expiratory lung parenchyma images by Pyradiomics and pre-trained Med3D (a heterogeneous 3D network), respectively. Last, Radiomics and CNN features are combined and then further selected by the Lasso algorithm and generalized linear model for determining node features and risk factors of AMGNN, and then the AECOPD prediction model is established. Compared to related models, the proposed model performs best, achieving an accuracy of 0.944, precision of 0.950, F1-score of 0.944, ad area under the curve of 0.965. Therefore, it is concluded that our model may become an effective tool for AECOPD prediction.

Real-World Effectiveness of Fluticasone Furoate/Umeclidinium/Vilanterol Once-Daily Single-Inhaler Triple Therapy for Symptomatic COPD: The ELLITHE Non-Interventional Trial

Purpose

Real-life effectiveness data on once-daily single-inhaler triple therapy (odSITT) with the inhaled corticosteroid fluticasone furoate (FF), the long-acting muscarinic antagonist umeclidinium (UMEC), and the long-acting β2-agonist vilanterol (VI) in patients with chronic obstructive pulmonary disease (COPD) are important to complement evidence from well-controlled randomized clinical trials. Effectiveness of odSITT was quantified by assessing health status and symptoms in usual care.

Patients and Methods

ELLITHE was a single-country (Germany), multicenter, open-label, non-interventional effectiveness study between 2020 and 2022, evaluating the effect of treatment initiation with FF/UMEC/VI 100/62.5/25 µg once-daily via the ELLIPTA inhaler on improvements in clinical outcomes versus baseline in COPD patients. The primary endpoint was the change in the total COPD Assessment Test (CAT) score between baseline and month 12. Key secondary endpoints included change in CAT score over time, occurrence of exacerbations until month 12, changes in forced expiratory volume in one second (FEV1), inhaler adherence, and safety.

Results

Nine hundred and six patients were included (age 66.6 years, 55.6% male, mean FEV1 52.6% of predicted, mean CAT 21.5 units, 1.4 exacerbations/year pre-study). About 63.9% of patients were escalated from dual therapies, and 18% were switched from multiple-inhaler triple therapies. Reductions in CAT score at month 12 were statistically significant and above the threshold of clinical importance (-2.6 units; p < 0.0001). CAT score also improved at interim visits. CAT improvements were more pronounced in patients with high baseline scores and better inhaler adherence. Exacerbations during follow-up were rare (0.2 events/year) compared to pre-study (1.4 events/year). FEV1 was improved by 93 mL (p < 0.0001). No new safety effects were observed.

Conclusion

In usual care, treatment with odSITT resulted in significant and clinically relevant improvements of CAT score and FEV1 in COPD patients, regardless of the occurrence of exacerbations. These findings challenge the current guideline recommendations for SITT only in patients experiencing exacerbations.

Investigation of the Methodology of Specific Airway Resistance Measurements in COPD

Introduction

Specific resistance (SRaw) measurements in Chronic Obstructive Pulmonary Disease (COPD) patients may be performed by panting or tidal breathing. The aim of this study was to compare how breathing frequency affected SRaw in COPD and compare different tangent plotting methods.

Methods

Fifteen COPD patients participated. Three protocols were performed: tidal 1 - spontaneous tidal breathing; tidal 2 - tidal breathing with a flow of ±1 L/sec; panting - 60 breaths per min. Effective (SReff), total (SRtot), ±0.5 L/s (SR0.5), and mid (SRmid) specific resistance were assessed.

Results

The tidal breathing protocols provided similar results. Panting resulted in higher SReff (p = 0.0002) and SRtot (p < 0.0001) versus tidal breathing, but not SR0.5 or SRmid. Breathing frequency did not affect intra-test variance. SReff and SRtot measurements were similar, and were higher than SR0.5, during tidal breathing (p = 0.0014 and p < 0.0001 respectively) and panting (p = 0.0179 and p < 0.0001 respectively). SRtot was higher than SRmid during tidal breathing (p < 0.0001) and panting (p < 0.0001). Intra-test variance of SReff and SRtot were similar and showed the lowest percent coefficient of variation during both tidal breathing and panting.

Conclusion

Panting and tidal breathing manoeuvres are not interchangeable in COPD patients. Panting widens the clubbing in the SRaw loop. SR0.5 and SRmid may underestimate abnormal physiology in COPD.

DElaying Disease Progression In COPD with Early Initiation of Dual Bronchodilator or Triple Inhaled PharmacoTherapy (DEPICT): A Predictive Modelling Approach

INTRODUCTION

Clinical studies demonstrate an accelerated decline in lung function in patients with moderate chronic obstructive pulmonary disease (COPD) (Global Initiative for Chronic Obstructive Lung Disease [GOLD] grade 2) versus severe and very severe COPD (GOLD grades 3 and 4). This predictive modelling study assessed the impact of initiating pharmacotherapy earlier versus later on long-term disease progression in COPD.

METHODS

The modelling approach used data on decline in forced expiratory volume in 1 s (FEV1) extracted from published studies to develop a longitudinal non-parametric superposition model of lung function decline with progressive impact of exacerbations from 0 per year to 3 per year and no ongoing pharmacotherapy. The model simulated decline in FEV1 and annual exacerbation rates from age 40 to 75 years in COPD with initiation of long-acting anti-muscarinic antagonist (LAMA)/long-acting beta2-agonist (LABA) (umeclidinium (UMEC)/vilanterol (VI)) or triple (inhaled corticosteroid (ICS)/LAMA/LABA; fluticasone furoate (FF)/UMEC/VI) therapy at 40, 55 or 65 years of age.

RESULTS

Model-predicted decline in FEV1 showed that, compared with 'no ongoing' therapy, initiation of triple or LAMA/LABA therapy at age 40, 55 or 65 years preserved an additional 469.7 mL or 236.0 mL, 327.5 mL or 203.3 mL, or 213.5 mL or 137.5 mL of lung function, respectively, by the age of 75. The corresponding average annual exacerbation rates were reduced from 1.57 to 0.91, 1.06 or 1.23 with triple therapy or to 1.2, 1.26 and 1.4 with LAMA/LABA therapy when initiated at 40, 55 or 65 years of age, respectively.

CONCLUSIONS

This modelling study suggests that earlier initiation of LAMA/LABA or triple therapy may have positive benefits in slowing disease progression in patients with COPD. Greater benefits were demonstrated with early initiation therapy with triple versus LAMA/LABA.

Putative Bidirectionality of Chronic Obstructive Pulmonary Disease and Periodontal Disease: A Review of the Literature

The prevalence of chronic obstructive pulmonary disease (COPD) is increasing worldwide and is currently the third leading cause of death globally. The long-term inhalation of toxic substances, mainly cigarette smoke, deteriorates pulmonary function over time, resulting in the development of COPD in adulthood. Periodontal disease is an inflammatory condition that affects most adults and is caused by the bacteria within dental plaque. These bacteria dissolve the gums around the teeth and the bone that supports them, ultimately leading to tooth loss. Periodontal disease and COPD share common risk factors, such as aging and smoking. Other similarities include local chronic inflammation and links with the onset and progression of systemic diseases such as ischemic heart disease and diabetes mellitus. Understanding whether interventions for periodontal disease improve the disease trajectory of COPD (and vice versa) is important, given our rapidly aging society. This review focuses on the putative relationship between COPD and periodontal disease while exploring current evidence and future research directions.

Unleashing the Power of Very Small Data to Predict Acute Exacerbations of Chronic Obstructive Pulmonary Disease

Introduction

In this article, we explore to what extent it is possible to leverage on very small data to build machine learning (ML) models that predict acute exacerbations of chronic obstructive pulmonary disease (AECOPD).

Methods

We build ML models using the small data collected during the eHealth Diary telemonitoring study between 2013 and 2017 in Sweden. This data refers to a group of multimorbid patients, namely 18 patients with chronic obstructive pulmonary disease (COPD) as the major reason behind previous hospitalisations. The telemonitoring was supervised by a specialised hospital-based home care (HBHC) unit, which also was responsible for the medical actions needed.

Results

We implement two different ML approaches, one based on time-dependent covariates and the other one based on time-independent covariates. We compare the first approach with standard COX Proportional Hazards (CPH). For the second one, we use different proportions of synthetic data to build models and then evaluate the best model against authentic data.

Discussion

To the best of our knowledge, the present ML study shows for the first time that the most important variable for an increased risk of future AECOPDs is "maintenance medication changes by HBHC". This finding is clinically relevant since a sub-optimal maintenance treatment, requiring medication changes, puts the patient in risk for future AECOPDs.

Conclusion

The experiments return useful insights about the use of small data for ML.

In 'real world' patients with COPD, exacerbation history, and not blood eosinophils, is the most reliable predictor of future exacerbations

INTRODUCTION

There is an interest in the role of blood eosinophils for predicting inhaled corticosteroid (ICS) response in chronic obstructive pulmonary disease (COPD). Most data are from interventional clinical studies; data from unselected real-world populations may help better inform treatment decisions. DACCORD is a non-interventional real-world study. Cohort 3 recruited patients with COPD who had received triple therapy for ≥ 6 months; prior to entry patients either continued triple therapy, or switched to a long-acting muscarinic antagonist/long-acting beta₂-agonist (LABA/LAMA), and were followed for 12 months.

METHODS

For these post-hoc analyses, patients were divided into four groups based on exacerbation history and baseline blood eosinophil count (< 100 vs. > 300 cells/µL). Exacerbation rates were calculated overall and for the two treatments.

RESULTS

Among the 430 patients in the current analyses, the largest groups had low exacerbation history with high (44.2%) or low eosinophils (36.7%). Most patients did not exacerbate during follow-up (68.8% overall; 83.2% and 63.7% with LABA/LAMA and triple therapy). The highest exacerbation rates were in groups with high exacerbation history, differing significantly in the overall analyses from those with low exacerbation history (matched by eosinophil count); rates did not differ when grouped by eosinophil count (matched by exacerbation history).

CONCLUSIONS

Although most patients in these analyses did not exacerbate during follow-up, whereas exacerbation history is a predictor of future exacerbations, blood eosinophil count is not. This suggests that although eosinophil count may help to guide ICS initiation, this is less of a consideration when 'stepping-down' from triple therapy to a LABA/LAMA.

Evaluation of the Effect of COVID-19 Vaccination on Exacerbations of Chronic Obstructive Pulmonary Disease: A Single-Center Study

BACKGROUND AND AIM

 Vaccinations have been one of the main approaches to reducing mortality and exacerbations caused by infectious agents in chronic obstructive pulmonary disease (COPD). Among viral pathogens, coronaviruses have been described to play a role. This study aims to investigate the role of coronavirus disease 2019 (COVID-19) vaccination on exacerbation reduction in patients with COPD.

METHODS

Patients diagnosed with COPD prior to the study date were considered the study population. Exacerbations of COPD before and after the COVID-19 vaccination were recorded. Patients with influenza and/or pneumococcal vaccination were excluded from the study due to their known role in reducing exacerbations of COPD.

RESULTS

The study included 152 patients with a mean age of 67.5 ± 9.7 years. Most patients were classified under Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2 and 3. In fully vaccinated patients, COPD exacerbation was observed to be higher than in those without full vaccination (70.5% vs. 55.3%, respectively). Total risk status and vaccination status, however, were seen to be in a positive correlation, with higher risk and complete vaccination status presenting with a higher count of COPD exacerbation.

CONCLUSION

Although it is known that the administration of COVID-19 vaccines in patients in risk groups reduces the risk of disease, there is no study showing a positive effect on COPD exacerbations alone. In our study, it was observed that only the COVID-19 vaccine was ineffective in attacks without influenza and pneumococcal vaccines.