A score to predict short-term risk of COPD exacerbations (SCOPEX)

Tracking COPD exacerbation patterns and forecasting readmission risks utilizing electronic medical records

INTRODUCTION

Accurate evaluation of exacerbation frequency is an essential part of COPD assessment. But relying on just the prior-year exacerbation history may not capture the full picture of risk given the inherent year-to-year fluctuations in exacerbation rates. This study aimed to evaluate the predictive performance of models incorporating the 3-year exacerbation history based on electronic medical record.

MATERIALS AND METHODS

This retrospective cohort study included 86,501 COPD hospitalized patients in Beijing from 2008 to 2014. The annual frequency of COPD exacerbation hospitalizations over a 3-year period after the index hospitalization was calculated, with patients segmented into seven distinct exacerbation trajectory groups. Logistic regression was used to evaluate the predictive capability of the 3-year exacerbation history for exacerbation readmission in the fourth year. Predictors included age, sex, comorbidities, and exacerbation hospitalization in previous 1-3 years. Model performance was evaluated using area under the receiver operating characteristic curve (AUC).

RESULTS

Of the studied patients, 56.5% were men, and the mean age (SD) was 73.8 (10.3) years. The overall readmission rate for COPD exacerbation was 0.31 per person-year, with only 3.8% of patients persistently readmitted over three consecutive years. The 3-year trajectory of exacerbation frequency was associated with exacerbation risk in the fourth year. Compared to just the prior year, the inclusion of a 3-year exacerbation hospitalization history notably improved prediction accuracy, with AUC elevating from 0.731 (0.724-0.739) to 0.786 (0.779-0.792).

CONCLUSION

These results unveil the fluctuating nature of COPD exacerbation hospitalization frequency across years and demonstrate that integrating a more comprehensive 3-year exacerbation history significantly refines the prediction model for future risk, thus providing a more nuanced and actionable insight for clinical care.

Prognostic risk factors for moderate-to-severe exacerbations in patients with chronic obstructive pulmonary disease: a systematic literature review

Background

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. COPD exacerbations are associated with a worsening of lung function, increased disease burden, and mortality, and, therefore, preventing their occurrence is an important goal of COPD management. This review was conducted to identify the evidence base regarding risk factors and predictors of moderate-to-severe exacerbations in patients with COPD.

Methods

A literature review was performed in Embase, MEDLINE, MEDLINE In-Process, and the Cochrane Central Register of Controlled Trials (CENTRAL). Searches were conducted from January 2015 to July 2019. Eligible publications were peer-reviewed journal articles, published in English, that reported risk factors or predictors for the occurrence of moderate-to-severe exacerbations in adults age ≥ 40 years with a diagnosis of COPD.

Results

The literature review identified 5112 references, of which 113 publications (reporting results for 76 studies) met the eligibility criteria and were included in the review. Among the 76 studies included, 61 were observational and 15 were randomized controlled clinical trials. Exacerbation history was the strongest predictor of future exacerbations, with 34 studies reporting a significant association between history of exacerbations and risk of future moderate or severe exacerbations. Other significant risk factors identified in multiple studies included disease severity or bronchodilator reversibility (39 studies), comorbidities (34 studies), higher symptom burden (17 studies), and higher blood eosinophil count (16 studies).

Conclusions

This systematic literature review identified several demographic and clinical characteristics that predict the future risk of COPD exacerbations. Prior exacerbation history was confirmed as the most important predictor of future exacerbations. These prognostic factors may help clinicians identify patients at high risk of exacerbations, which are a major driver of the global burden of COPD, including morbidity and mortality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02123-5.

Automatically Explaining Machine Learning Predictions on Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study

Background

Chronic obstructive pulmonary disease (COPD) is a major cause of death and places a heavy burden on health care. To optimize the allocation of precious preventive care management resources and improve the outcomes for high-risk patients with COPD, we recently built the most accurate model to date to predict severe COPD exacerbations, which need inpatient stays or emergency department visits, in the following 12 months. Our model is a machine learning model. As is the case with most machine learning models, our model does not explain its predictions, forming a barrier for clinical use. Previously, we designed a method to automatically provide rule-type explanations for machine learning predictions and suggest tailored interventions with no loss of model performance. This method has been tested before for asthma outcome prediction but not for COPD outcome prediction.

Objective

This study aims to assess the generalizability of our automatic explanation method for predicting severe COPD exacerbations.

Methods

The patient cohort included all patients with COPD who visited the University of Washington Medicine facilities between 2011 and 2019. In a secondary analysis of 43,576 data instances, we used our formerly developed automatic explanation method to automatically explain our model’s predictions and suggest tailored interventions.

Results

Our method explained the predictions for 97.1% (100/103) of the patients with COPD whom our model correctly predicted to have severe COPD exacerbations in the following 12 months and the predictions for 73.6% (134/182) of the patients with COPD who had ≥1 severe COPD exacerbation in the following 12 months.

Conclusions

Our automatic explanation method worked well for predicting severe COPD exacerbations. After further improving our method, we hope to use it to facilitate future clinical use of our model.

International Registered Report Identifier (IRRID)

RR2-10.2196/13783

Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study

Background

Chronic obstructive pulmonary disease (COPD) poses a large burden on health care. Severe COPD exacerbations require emergency department visits or inpatient stays, often cause an irreversible decline in lung function and health status, and account for 90.3% of the total medical cost related to COPD. Many severe COPD exacerbations are deemed preventable with appropriate outpatient care. Current models for predicting severe COPD exacerbations lack accuracy, making it difficult to effectively target patients at high risk for preventive care management to reduce severe COPD exacerbations and improve outcomes.

Objective

The aim of this study is to develop a more accurate model to predict severe COPD exacerbations.

Methods

We examined all patients with COPD who visited the University of Washington Medicine facilities between 2011 and 2019 and identified 278 candidate features. By performing secondary analysis on 43,576 University of Washington Medicine data instances from 2011 to 2019, we created a machine learning model to predict severe COPD exacerbations in the next year for patients with COPD.

Results

The final model had an area under the receiver operating characteristic curve of 0.866. When using the top 9.99% (752/7529) of the patients with the largest predicted risk to set the cutoff threshold for binary classification, the model gained an accuracy of 90.33% (6801/7529), a sensitivity of 56.6% (103/182), and a specificity of 91.17% (6698/7347).

Conclusions

Our model provided a more accurate prediction of severe COPD exacerbations in the next year compared with prior published models. After further improvement of its performance measures (eg, by adding features extracted from clinical notes), our model could be used in a decision support tool to guide the identification of patients with COPD and at high risk for care management to improve outcomes.

International Registered Report Identifier (IRRID)

RR2-10.2196/13783

Change in individual chronic obstructive pulmonary disease assessment test item scores after short-term bronchodilator therapy and its impact on exacerbation in treatment-naïve patients with chronic obstructive pulmonary disease

Background:

The chronic obstructive pulmonary disease (COPD) assessment test (CAT) measures the health status of patients with COPD. We aimed to investigate the change in individual CAT scores after short-term bronchodilator therapy among treatment-naïve patients with COPD.

Methods:

Data from 148 patients newly diagnosed with COPD between January 2016 and April 2020 were retrospectively analyzed. We compared the CAT score, modified Medical Research Council (mMRC) dyspnea grade, and forced expiratory volume in 1 s (FEV1) before and after short-term (6 ± 2 months) bronchodilator therapy. We analyzed the change trends using generalized estimating equations.

Results:

The mean patient age was 70.9 years, and 92.6% were male. The total CAT score did not significantly improve. However, among the CAT items, phlegm [adjusted difference: –0.22 (–0.48, –0.002)], chest tightness [–0.30 (–0.56, –0.05)], and breathlessness [–0.45 (–0.66, –0.23)] scores significantly improved after bronchodilator therapy. The patients were divided into two groups: CAT score improved ( n = 69) and not improved group ( n = 79). The development of moderate-to-severe exacerbations during follow-up was significantly lower (2.9% versus 17.7%, p = 0.004) in the CAT score improved group.

Conclusion:

The improvement in CAT items indicating respiratory symptoms was more evident than the CAT total score after short-term bronchodilator therapy. Despite the significant increase in FEV1 after bronchodilator therapy, fewer than half of the patients achieved meaningful improvement in CAT, and this group showed significantly lower development of exacerbation during follow-up.

Prediction of Acute COPD Exacerbation in the Swiss Multicenter COPD Cohort Study (TOPDOCS) by Clinical Parameters, Medication Use, and Immunological Biomarkers

BACKGROUND AND OBJECTIVE

Whether immunological biomarkers combined with clinical characteristics measured during an exacerbation-free period are predictive of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) frequency and severity is unknown.

METHOD

We measured immunological biomarkers and clinical characteristics in 271 stable chronic obstructive pulmonary disease (COPD) patients (67% male, mean age 63 years) from "The Obstructive Pulmonary Disease Outcomes Cohort of Switzerland" cohort on a single occasion. One-year follow-up data were available for 178 patients. Variables independently associated with AECOPD frequency and severity were identified by multivariable regression analyses. Receiver operating characteristic analysis was used to obtain optimal cutoff levels and measure the area under the curve (AUC) in order to assess if baseline data can be used to predict future AECOPD.

RESULTS

Higher number of COPD medications (adjusted incident rate ratio [aIRR] 1.17) and platelet count (aIRR 1.03), and lower FEV1% predicted (aIRR 0.84) and IgG2 (aIRR 0.84) were independently associated with AECOPD frequency in the year before baseline. Optimal cutoff levels for experiencing frequent (>1) AECOPD were ≥3 COPD medications (AUC = 0.72), FEV1 ≤40% predicted (AUC = 0.72), and IgG2 ≤2.6 g/L (AUC = 0.64). The performance of a model using clinical and biomarker parameters to predict future, frequent AECOPD events in the same patients was fair (AUC = 0.78) but not superior to a model using only clinical parameters (AUC = 0.79). The IFN-lambda rs8099917GG-genotype was more prevalent in patients who had severe AECOPD.

CONCLUSIONS

Clinical and biomarker parameters assessed at a single point in time correlated with the frequency of AECOPD events during the year before and the year after assessment. However, only clinical parameters had fair discriminatory power in identifying patients likely to experience frequent AECOPD.

Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis

Background

Asthma and chronic obstructive pulmonary disease (COPD) impose a heavy burden on health care. Approximately one-fourth of patients with asthma and patients with COPD are prone to exacerbations, which can be greatly reduced by preventive care via integrated disease management that has a limited service capacity. To do this well, a predictive model for proneness to exacerbation is required, but no such model exists. It would be suboptimal to build such models using the current model building approach for asthma and COPD, which has 2 gaps due to rarely factoring in temporal features showing early health changes and general directions. First, existing models for other asthma and COPD outcomes rarely use more advanced temporal features, such as the slope of the number of days to albuterol refill, and are inaccurate. Second, existing models seldom show the reason a patient is deemed high risk and the potential interventions to reduce the risk, making already occupied clinicians expend more time on chart review and overlook suitable interventions. Regular automatic explanation methods cannot deal with temporal data and address this issue well.

Objective

To enable more patients with asthma and patients with COPD to obtain suitable and timely care to avoid exacerbations, we aim to implement comprehensible computational methods to accurately predict proneness to exacerbation and recommend customized interventions.

Methods

We will use temporal features to accurately predict proneness to exacerbation, automatically find modifiable temporal risk factors for every high-risk patient, and assess the impact of actionable warnings on clinicians’ decisions to use integrated disease management to prevent proneness to exacerbation.

Results

We have obtained most of the clinical and administrative data of patients with asthma from 3 prominent American health care systems. We are retrieving other clinical and administrative data, mostly of patients with COPD, needed for the study. We intend to complete the study in 6 years.

Conclusions

Our results will help make asthma and COPD care more proactive, effective, and efficient, improving outcomes and saving resources.

International Registered Report Identifier (IRRID)

PRR1-10.2196/27065

Predicting Re-Exacerbation Timing and Understanding Prolonged Exacerbations: An Analysis of Patients with COPD in the ECLIPSE Cohort

PURPOSE

Understanding risk factors for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is important for optimizing patient care. We re-analyzed data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study (NCT00292552) to identify factors predictive of re-exacerbations and associated with prolonged AECOPDs.

METHODS

Patients with COPD from ECLIPSE with moderate/severe AECOPDs were included. The end of the first exacerbation was the index date. Timing of re-exacerbation risk was assessed in patients with 180 days' post-index-date follow-up data. Factors predictive of early (1-90 days) vs late (91-180 days) vs no re-exacerbation were identified using a multivariable partial-proportional-odds-predictive model. Explanatory logistic-regression modeling identified factors associated with prolonged AECOPDs.

RESULTS

Of the 1,554 eligible patients from ECLIPSE, 1,420 had 180 days' follow-up data: more patients experienced early (30.9%) than late (18.7%) re-exacerbations; 50.4% had no re-exacerbation within 180 days. Lower post-bronchodilator FEV1 (P=0.0019), a higher number of moderate/severe exacerbations on/before index date (P<0.0001), higher St. George's Respiratory Questionnaire total score (P=0.0036), and season of index exacerbation (autumn vs winter, P=0.00164) were identified as predictors of early (vs late/none) re-exacerbation risk within 180 days. Similarly, these were all predictors of any (vs none) re-exacerbation risk within 180 days. Median moderate/severe AECOPD duration was 12 days; 22.7% of patients experienced a prolonged AECOPD. The odds of experiencing a prolonged AECOPD were greater for severe vs moderate AECOPDs (adjusted odds ratio=1.917, P=0.002) and lower for spring vs winter AECOPDs (adjusted odds ratio=0.578, P=0.017).

CONCLUSION

Prior exacerbation history, reduced lung function, poorer respiratory-related quality-of-life (greater disease burden), and season may help identify patients who will re-exacerbate within 90 days of an AECOPD. Severe AECOPDs and winter AECOPDs are likely to be prolonged and may require close monitoring.

Validation of the Summit Lab Score in Predicting Exacerbations of Chronic Obstructive Pulmonary Disease Among Individuals with High Arterial Stiffness

INTRODUCTION

The presence of cardiovascular (CV) risk factors and CV disease in patients with chronic obstructive pulmonary disease (COPD) leads to worse outcomes. A number of tools are currently available to stratify the risk of adverse outcomes in these patients with COPD. This post hoc analysis evaluated the Summit Lab Score for validation as a predictor of the first episode of moderate-to-severe acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and other outcomes, in patients with COPD and high arterial pulse wave velocity (aPWV).

METHODS

Data from a multicenter, randomized, placebo-controlled, double-blind study were retrospectively analyzed to evaluate treatment effects of once-daily fluticasone furoate/vilanterol 100/25 μg in patients with COPD and an elevated CV risk (aPWV≥11m/s) over 24 weeks. The previously derived Summit Lab Score and, secondarily, the Intermountain Risk Score (IMRS) were computed for each patient, with patients then stratified into tertiles for each score. Risk of moderate-to-severe AECOPD was analyzed across tertiles using Kaplan-Meier survival curve and Cox regression analyses.

RESULTS

In 430 patients with COPD, Kaplan-Meier probabilities of no moderate-to-severe AECOPD for Summit Lab Score tertiles 1, 2, and 3 were 92.3%, 95.5%, and 85.1%, respectively (P trend = 0.015), over 24 weeks. Grouped by IMRS tertiles, the respective probabilities were 92.9%, 91.2%, and 88.3%, respectively (P trend = 0.141). Length of stay in the hospital (P = 0.034) and the hospital ward (P = 0.042) were also significantly different between Summit Lab Score tertiles but not for intensive care (P = 0.191).

CONCLUSION

The Summit Lab Score was associated with the 24-week risk of moderate-to-severe AECOPD in COPD patients with elevated CV risk. Secondarily, IMRS showed a trend towards differences in the risk of AECOPD, which was not statistically significant.

Early Clinically Important Improvement (ECII) and Exacerbation Outcomes in COPD Patients

Background

Chronic obstructive pulmonary disease (COPD) exacerbations are difficult outcomes to measure in clinical trials. It would be valuable to be able to predict which patients are likely to benefit in terms of exacerbation prevention based on their early response in lung function and symptoms.

Methods

This was a post-hoc analysis from the 52-week, randomized, double-blind, double-dummy, non-inferiority FLAME trial. Early clinically important improvement (ECII) was defined as achievement of minimal clinically important difference in trough forced expiratory volume in 1 second (FEV1; ≥100 mL increase) and one patient-reported outcome (PRO): either St. George's Respiratory Questionnaire for COPD (≥4-unit reduction; D1), or COPD assessment test (≥2-point reduction; D2) at Week 4 or 12.

Results

Approximately 18-20% of patients achieved ECII at Week 4 or 12 post-randomization according to any of the two definitions. The rate of subsequent exacerbations was lower in patients who achieved ECII at Week 4 (D1: ratio of rates [95% CI], 0.85 [0.74 to 0.98]; D2, 0.88 [0.77 to 1.00]) or at Week 12 (D1, 0.85 [0.74 to 0.98]; D2, 0.86 [0.75 to 1.00]) versus patients not achieving ECII. Patients who achieved ECII experienced longer time-to-first exacerbation between Week 4 or 12 to end of study. More patients achieved ECII with indacaterol/glycopyrronium versus salmeterol/fluticasone according to both definitions at Week 4 (D1, odds ratio [95% CI], 1.69 [1.40 to 2.04]; D2, 1.61 [1.34 to 1.93]), and 12 (D1, 2.01 [1.66 to 2.44]; D2, 1.80 [1.48 to 2.18]).

Conclusion

ECII is a novel composite endpoint, based on clinically relevant improvement in lung function and PROs in the early phase of treatment intervention that may predict subsequent exacerbation risk and may be used in clinical trials.

Improving the evaluation of COPD exacerbation treatment effects by accounting for early treatment discontinuations: a post-hoc analysis of randomized clinical trials

Background

Chronic obstructive pulmonary disease (COPD) clinical trials aimed at evaluating treatment effects on exacerbations often suffer from early discontinuations of randomized treatment. Treatment discontinuations imply a loss of information and should ideally be considered in the statistical analysis of trial results, particularly if the discontinuations are related to the disease or treatment itself. Here, we explore this issue by investigating (1) whether there exists an association between the risks of exacerbation and treatment discontinuation in COPD clinical trials and (2) whether disregarding this association can cause bias in exacerbation treatment effect estimates. We focus on the hypothetical estimand, i.e. the treatment effect that would have been observed had all subjects completed the trial as planned.

Methods

The association between exacerbation and discontinuation risks was analysed by applying a joint frailty (random effect) model – allowing for the simultaneous analysis of multiple types of correlated events – to data from five Phase III-IV COPD clinical trials. Specifically, the impact of the association on exacerbation treatment effect estimates was assessed by comparing the treatment hazard ratios of the joint frailty model to the rate/hazard ratios of two related statistical models (the negative binomial and shared frailty models), which both assume discontinuations to be unrelated to the trial outcome. The models were also compared using simulated data.

Results

A statistically significant (p < 0.0001), positive association between exacerbation and discontinuation risks was found in all trials. Importantly, simulations confirmed that – with such an association – models disregarding the association risk producing biased results (> 5 percentage point difference in hazard/rate ratio). For some treatment comparisons in the clinical trials, the difference in treatment effect estimates between the joint frailty and the other models was as high as 10–15 percentage points. The difference was affected by the strength of the exacerbation-discontinuation association, the population heterogeneity in exacerbation risk, and the difference in discontinuation rates between treatment arms.

Conclusions

We have identified an association between the risks of exacerbation and treatment discontinuation in five COPD clinical trials. We recommend using the joint frailty model to account for this association when estimating exacerbation treatment effects, particularly when targeting the hypothetical estimand.

Higher short-acting beta-agonist use is associated with greater COPD burden

INTRODUCTION

The COPD Assessment Test (CAT) is a self-administered questionnaire that measures symptomatic burden. CAT is used as part of the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines refined ABCD tool and is usually performed during office visit assessment. Electronic medication monitors (EMMs) capture utilization of short-acting beta-agonists (SABA) that may indicate disease worsening in real-time. The primary objective was to assess the relationship of CAT with SABA utilization.

METHODS

From 8/2017-1/2019, COPD patients ≥40 years of age were enrolled in a digital health platform consisting of EMMs and a mobile application to track time and date of SABA use. Patients with a completed CAT and ≥81 days of continuous EMM data were included in analyses. Using one-way ANOVA, SABA use and maintenance medication adherence were compared by CAT score categories: <10 (low burden), 10-20 (medium), 21-30 (high), and 31-40 (very high). Associations were additionally estimated in patients who used ≥1 puff/week of their rescue and maintenance medication.

RESULTS

The population included 2196 COPD patients (mean age: 60 years). CAT scores from low to high burden were associated with greater SABA use, from 0.8 to 1.9 puffs/day (+1.1 [95% CI: 0.6, 1.6 puffs/day], P < 0.001), and lower adherence, from 69% to 59%, (-10% [95% CI: -1, -19%], P = 0.04). Sensitivity analyses yielded similar results.

CONCLUSIONS

This study found a significant association between greater SABA use and lower adherence with higher burden CAT scores. This finding may suggest that passive collection of inhaled medications could serve as a surrogate for CAT.

Development of a Nomogram to Predict the Risk of 30-Day Re-Exacerbation for Patients Hospitalized for Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Acute exacerbation (AE) is the main cause of increased disability and mortality for patients with Chronic Obstructive Pulmonary Disease (COPD). Short-term re-exacerbation after discharge is common for in-hospital patients with AECOPD. Thus, we aimed to design a scoring system to effectively predict the 30-day re-exacerbation using simple and easily accessible variables. We retrospectively enrolled 686 cases hospitalized for AECOPD in two Chinese hospitals from 2005 to 2017. A variety of parameters were collected like demographics, clinical manifestations and treatments in stable and AE period. The optimal subset of covariates in the multivariate logistic analysis was identified by the smallest Akaike Information Criterion (AIC) and was further used to develop a practical and reliable nomogram to predict the 30-day re-exacerbation. The efficacy of the nomogram was internally validated by concordance index (C-index) and a calibration plot. The incidence of 30-day re-exacerbation was 15.8%. Based on the smallest AIC, eight easily-accessible parameters were included in the nomogram, including sex, COPD assessment test (CAT) scores, AE with respiratory failure in the previous year, new purulent sputum, new cardiovascular events, combined antibiotic therapy, theophylline therapy for AE and ICU admission. Our nomogram revealed good discriminative ability with the C-index of 0.702. The calibration curve showed good agreement between nomogram-predicted probability and actual observation. Incorporating eight common variables, a nomogram for 30-day re-exacerbation after discharge with high predictive performance was constructed for patients with AECOPD, which was helpful in predicting individualized risk of re-exacerbation and offering individualized post-discharge support.

Factors associated with chronic obstructive pulmonary disease exacerbation, based on big data analysis

Preventing exacerbation in chronic obstructive pulmonary disease (COPD) patients is crucial, but requires identification of the exacerbating factors. To date, no integrated analysis of patient-derived and external factors has been reported. To identify factors associated with COPD exacerbation, we collected data, including smoking status, lung function, and COPD assessment test scores, from 594 COPD patients in the Korean COPD subgroup study (KOCOSS), and merged these data with patients' Korean Health Insurance Review and Assessment Service data for 2007-2012. We also collected primary weather variables, including levels of particulate matter <10 microns in diameter, daily minimum ambient temperature, as well as respiratory virus activities, and the logs of web queries on COPD-related issues. We then assessed the associations between these patient-derived and external factors and COPD exacerbations. Univariate analysis showed that patient factors, air pollution, various types of viruses, temperature, and the number of COPD-related web queries were associated with COPD exacerbation. Multivariate analysis revealed that the number of exacerbations in the preceding year, female sex, COPD grade, and influenza virus detection rate, and lowest temperature showed significant association with exacerbation. Our findings may help COPD patients predict when exacerbations are likely, and provide intervention as early as possible.

A clinical prediction model for hospitalized COPD exacerbations based on "treatable traits"

Background

Assessing risk of future exacerbations is an important component in COPD management. History of exacerbation is a strong and independent predictor of future exacerbations, and the criterion of ≥2 nonhospitalized or ≥1 hospitalized exacerbation is often used to identify high-risk patients in whom therapy should be intensified. However, other factors or "treatable traits" also contribute to risk of exacerbation.

Objective

The objective of the study was to develop and externally validate a novel clinical prediction model for risk of hospitalized COPD exacerbations based on both exacerbation history and treatable traits.

Patients and methods

A total of 237 patients from the COPD Registry of Changi General Hospital, Singapore, aged 75±9 years and with mean post-bronchodilator FEV1 60%±20% predicted, formed the derivation cohort. Hospitalized exacerbation rate was modeled using zero-inflated negative binomial regression. Calibration was assessed by graphically comparing the agreement between predicted and observed annual hospitalized exacerbation rates. Predictive (discriminative) accuracy of the model for identifying high-risk patients (defined as experiencing ≥1 hospitalized exacerbations) was assessed with area under the curve (AUC) and receiver operating characteristics analyses, and compared to other existing risk indices. We externally validated the prediction model using a multicenter dataset comprising 419 COPD patients.

Results

The final model included hospitalized exacerbation rate in the previous year, history of acute invasive/noninvasive ventilation, coronary artery disease, bronchiectasis, and sputum nontuberculous mycobacteria isolation. There was excellent agreement between predicted and observed annual hospitalized exacerbation rates. AUC was 0.789 indicating good discriminative accuracy, and was significantly higher than the AUC of the Global Initiative for Chronic Obstructive Lung Disease (GOLD) risk assessment criterion (history of ≥1 hospitalized exacerbation in the previous year) and the age, dyspnea, and obstruction index. When applied to the independent multicenter validation cohort, the model was well-calibrated and discrimination was good.

Conclusion

We have derived and externally validated a novel risk prediction model for COPD hospitalizations which outperforms several other risk indices. Our model incorporates several treatable traits which can be targeted for intervention to reduce risk of future hospitalized exacerbations.

Predictive factors for exacerbation and re-exacerbation in chronic obstructive pulmonary disease: an extension of the Cox model to analyze data from the Swiss COPD cohort

Background

The Swiss COPD cohort was established in 2006 to collect data in a primary care setting. The objective of this study was to evaluate possible predictive factors for exacerbation and re-exacerbation.

Methods

In order to predict exacerbation until the next visit based on the knowledge of exacerbation since the last visit, a multistate model described by Therneau and Grambsch was performed.

Results

Data of 1,247 patients (60.4% males, 46.6% current smokers) were analyzed, 268 (21.5%) did not fulfill spirometric diagnostic criteria for COPD. Data of 748 patients (63% males, 44.1% current smokers) were available for model analysis. In order to predict exacerbation an extended Cox Model was performed. Mean FEV₁/FVC-ratio was 53.1% (±11.5), with a majority of patients in COPD GOLD classes 2 or 3. Hospitalization for any reason (HR1.7; P = 0.04) and pronounced dyspnea (HR for mMRC grade four 3.0; P < 0.001) at most recent visit as well as prescription of short-acting bronchodilators (HR1.7; P < 0.001), inhaled (HR1.2; P = 0.005) or systemic corticosteroids (HR1.8; P = 0.015) were significantly associated with exacerbation when having had no exacerbation at most recent visit. Higher FEV₁/FVC (HR0.9; P = 0.008) and higher FEV₁ values (HR0.9; P = 0.001) were protective. When already having had an exacerbation at the most recent visit, pronounced dyspnea (HR for mMRC grade 4 1.9; P = 0.026) and cerebrovascular insult (HR2.1; P = 0.003) were significantly associated with re-exacerbation. Physical activity (HR0.6; P = 0.031) and treatment with long-acting anticholinergics (HR0.7; P = 0.044) seemed to play a significant protective role. In a best subset model for exacerbation, higher FEV₁ significantly reduced and occurrence of sputum increased the probability of exacerbation. In the same model for re-exacerbation, coronary heart disease increased and hospitalization at most recent visit seemed to reduce the risk for re-exacerbation.

Conclusion

Our data confirmed well-established risk factors for exacerbations whilst analyzing their predictive association with exacerbation and re-exacerbation. This study confirmed the importance of spirometry in primary care, not only for diagnosis but also as a risk evaluation for possible future exacerbations.

Trial registration

Our study got approval by local ethical committee in 2006 (EK Nr. 170/06) and was registered retrospectively on ClinicalTrials.gov (NCT02065921, 19^th of February 2014).

External Validation of a COPD Risk Measure in a Commercial and Medicare Population: The COPD Treatment Ratio

BACKGROUND

Chronic obstructive pulmonary disease (COPD) exacerbations can accelerate disease progression and lead to higher health care costs. To improve patient survival and reduce cost, risk assessment measures should be developed to identify patients at risk for exacerbations and prevent future exacerbations.

OBJECTIVES

To (a) externally validate the COPD treatment ratio (CTR) as a measure of COPD exacerbation risk based on predictive models previously tested and (b) assess the measure's capability to assess risk using only pharmacy claims for use in Medicare Part D programs.

METHODS

This was a retrospective observational study conducted using the Humana research datasets. Separate assessments were performed using pharmacy-only models that excluded risk factors derived from medical claims. Patients were aged ≥ 40 years, with ≥ 1 inpatient hospitalization or ≥ 2 physician's office, emergency department, or urgent care visits with a COPD diagnosis. Using logistic regression models, risk factors (age, exacerbation history, COPD and concomitant medication use, and comorbidities) were assessed during the baseline period (year 1) and were used to predict the risk of exacerbation during year 2. Continuous and dichotomized CTRs were analyzed. A cut-point of 0.3 was initially used for dichotomizing CTR, and subsequently receiver operating characteristics (ROC) analysis was used to determine the optimal cut-point for CTR.

RESULTS

A total of 92,496 patients were identified, the majority of which (96.2%) were Medicare members with a mean age of 69 years. During the baseline period, 14.0% and 11.2% of patients had ≥ 1 moderate or severe exacerbation, respectively. Overall, the CTR performed well in predicting future COPD exacerbations, especially severe exacerbations. ROC analysis suggested that 0.7 was the optimal cut-point for dichotomizing CTR. Patients with a CTR ≥ 0.7 had a 7.9% (OR = 0.921; 95% CI = 0.852-0.995) lower risk of a severe exacerbation, compared with those with a CTR < 0.7. Stronger effects were seen in pharmacy-only models, with patients 17% less likely to experience a severe exacerbation with a CTR ≥ 0.7 compared with patients with a CTR < 0.7.

CONCLUSIONS

This study validated the use of CTR as a modifiable measure of risk of COPD exacerbation in a large commercial and Medicare population and remained a robust predictor when pharmacy-only claims data were available. A CTR of ≥ 0.7 may be a useful target to help reduce the risk of severe exacerbations, and its use by payer or quality organizations has the potential to improve COPD management.

DISCLOSURES

This study was funded by GlaxoSmithKline (GSK; study number HO-15-16651). GSK had a role in the study design, collection, analysis, and interpretation of data and in the writing of the study report but did not place any restrictions on access to the data or on the statements made in the manuscript. The authors were in full editorial control of publication target journal and content and conclusions, accepted full responsibility for final approval of a manuscript describing this GSK-sponsored research, and had final responsibility for the decision to submit for publication. Stanford and Lau are employees of GSK and hold GSK stocks/shares. Li and Stemkowski are employees of Comprehensive Health Insights, which was contracted to conduct the study but did not receive funding for manuscript development. This manuscript was presented in part at the American Thoracic Society 2017 International Conference; May 19-24, 2017; Washington, DC.

Spirometric Values of Greek People and Comparison with ECSC and GLI Values in COPD People

Background:

During the past few years, the use of criteria introduced by Global Initiative for Chronic Obstructive Lung Disease (GOLD) is recommended for the diagnosis and classification of Chronic Obstructive Pulmonary Disease(COPD),taking into account the values of a Forced Expiratory Volume In 1 second (FEV1) and a Forced Expiratory Volume In 1 second (FEV1) to Forced Vital Capacity (FVC) ratio. In Europe, the reference values of the European Coal and Steel Community (ECSC), that were originally developed in 1993 are still used.

Aim of the Study:

The study aimed to carry out measurement of spirometric values in a healthy, non smoking Greek population, development of local equations and comparison with ECSC and Global Lung Initiative(GLI) equations, in order to see if there is a need for separate ones in everyday use.

Methods:

Normal predicted values for FEV1 and FEV1/FVC% were obtained from a group of 500 healthy subjects, aged 18-89 years. In addition, a group of 124 COPD patients, with no other comorbidities was studied. Patients were classified according to GOLD criteria in four groups with ECSC, GLI predicted values or with our own predicted values.

Results:

The statistical analysis has revealed that there is no significant difference among the three sets of predicted values and no statistical difference was detected among the classification of COPD patients.

Conclusion:

It is shown that the 3 sets of predicted values are almost identical, despite the fact that they have been collected from different study populations.Αccording to the study, there is no need in recalculating values for Greek population.

The role of argyrophilic nucleolar organizing region-associated proteins in clinical exacerbation of chronic obstructive pulmonary disease

Objective

To investigate whether argyrophilic nucleolar organizing region-associated protein (AgNOR) parameters can be used as a biomarker that could potentially help with the management and clinical prognosis of chronic obstructive pulmonary disease (COPD) exacerbation.

Methods

This case–control study enrolled patients with COPD who were admitted to the Emergency Department and healthy sex- and age-matched control subjects. Peripheral blood samples were collected at hospital admission and the peripheral lymphocytes were silver-stained to investigate the quantity and distribution of AgNOR proteins. Fifty nuclei per patient were viewed and the total AgNOR area/total nuclear area (TAA/TNA) ratio and the mean AgNOR number for each patient were calculated.

Results

A total of 20 patients with COPD exacerbation and 17 healthy control subjects were recruited to the study. The TAA/TNA ratio and the mean AgNOR number were significantly higher in the patients with COPD exacerbation compared with the healthy control subjects. The mean AgNOR number showed a positive correlation with the pCO₂ levels on admission.

Conclusion

AgNOR protein levels were elevated during a COPD exacerbation compared with healthy control subjects and there was a positive correlation between pCO₂ levels and mean AgNOR number.

Rural Residence and Chronic Obstructive Pulmonary Disease Exacerbations. Analysis of the SPIROMICS Cohort

Rationale: Rural residence is associated with poor outcomes in several chronic diseases. The association between rural residence and chronic obstructive pulmonary disease (COPD) exacerbations remains unclear.Objectives: In this work, we sought to determine the independent association between rural residence and COPD-related outcomes, including COPD exacerbations, airflow obstruction, and symptom burden.Methods: A total of 1,684 SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) participants with forced expiratory volume in 1 second/forced vital capacity < 0.70 had geocoding-defined rural-urban residence status determined (N = 204 rural and N = 1,480 urban). Univariate and multivariate logistic and negative binomial regressions were performed to assess the independent association between rurality and COPD outcomes, including exacerbations, lung function, and symptom burden. The primary exposure of interest was rural residence, determined by geocoding of the home address to the block level at the time of study enrollment. Additional covariates of interest included demographic and clinical characteristics, occupation, and occupational exposures. The primary outcome measures were exacerbations determined over a 1-year course after enrollment by quarterly telephone calls and at an annual research clinic visit. The odds ratio (OR) and incidence rate ratio (IRR) of exacerbations that required treatment with medications, including steroids or antibiotics (total exacerbations), and exacerbations leading to hospitalization (severe exacerbations) were determined after adjusting for relevant covariates.Results: Rural residence was independently associated with a 70% increase in the odds of total exacerbations (OR, 1.70 [95% confidence interval (CI), 1.13-2.56]; P = 0.012) and a 46% higher incidence rate of total exacerbations (IRR 1.46 [95% CI, 1.02-2.10]; P = 0.039). There was no association between rural residence and severe exacerbations. Agricultural occupation was independently associated with increased odds and incidence of total and severe exacerbations. Inclusion of agricultural occupation in the analysis attenuated the association between rural residence and the odds and incidence rate of total exacerbations (OR, 1.52 [95% CI, 1.00-2.32]; P = 0.05 and IRR 1.39 [95% CI, 0.97-1.99]; P = 0.07). There was no difference in symptoms or airflow obstruction between rural and urban participants.Conclusions: Rural residence is independently associated with increased odds and incidence of total, but not severe, COPD exacerbations. These associations are not fully explained by agriculture-related exposures, highlighting the need for future research into potential mechanisms of the increased risk of COPD exacerbations in the rural population.

Acute exacerbation of COPD during pulmonary rehabilitation: outcomes and risk prediction

Purpose

This study was performed to examine acute exacerbation of COPD (AECOPD) during pulmonary rehabilitation (PR) and the usefulness of multidimensional indices (MIs) to predict AECOPD at enrolment in PR.

Patients and methods

A 4-week PR program (PRP) was implemented for 125 consecutive patients with COPD. At baseline and PRP completion, we recorded the FEV₁, 6-minute walk test, peak work rate at cardiopulmonary testing, modified Medical Research Council score, and COPD Assessment Test (CAT) score. The risk of AECOPDs at baseline was assessed using the body mass index, airway obstruction, dyspnea, Exercise capacity (BODE), dyspnea, obstruction, smoking, exacerbation (DOSE), and score to predict short-term risk of COPD exacerbations (SCOPEX) MIs.

Results

Thirty-two episodes of AECOPD occurred. The COPD status was worse in patients with than without AECOPD at baseline (lower FEV₁, 6-minute walk test, and peak work rate; higher modified Medical Research Council and CAT scores). The sensitivities of the BODE, DOSE, and SCOPEX MIs to predict the occurrence of AECOPD during PRP were 78.1%, 21.9%, and 84.4%, and the specificities were 73.6%, 87.1%, and 51.6%, respectively.

Conclusion

The BODE and SCOPEX MIs help to predict the exacerbation risk during PR.

Predictors of exacerbation risk and response to budesonide in patients with chronic obstructive pulmonary disease: a post-hoc analysis of three randomised trials

BACKGROUND

The peripheral blood eosinophil count might help identify those patients with chronic obstructive pulmonary disease (COPD) who will experience fewer exacerbations when taking inhaled corticosteroids (ICS). Previous post-hoc analyses have proposed eosinophil cutoffs that are both arbitrary and limited in evaluating complex interactions of treatment response. We modelled eosinophil count as a continuous variable to determine the characteristics that determine both exacerbation risk and clinical response to ICS in patients with COPD.

METHODS

We analysed data from three AstraZeneca randomised controlled trials of budesonide-formoterol in patients with COPD with a history of exacerbations and available blood eosinophil counts. Patients with any history of asthma were excluded. Negative binomial regression analysis was done using splines for modelling of continuous variables to study the primary outcome of annual exacerbation rate adjusted for exposure time and study design. The trials are registered with ClinicalTrials.gov, NCT00206167, NCT00206154, and NCT00419744.

FINDINGS

4528 patients were studied. A non-linear increase in exacerbations occurred with increasing eosinophil count in patients who received formoterol alone. At eosinophil counts of 0·10 × 10⁹ cells per L or more, a significant treatment effect was recorded for exacerbation reduction with budesonide-formoterol compared with formoterol alone (rate ratio 0·75, 95% CI 0·57-0·99; p_interaction=0·015). Interactions were observed between eosinophil count and the treatment effects of budesonide-formoterol over formoterol on St George's Respiratory Questionnaire (p_interaction=0·0043) and pre-bronchodilator FEV₁ (linear effect p<0·0001, p_interaction=0·067). Only eosinophil count and smoking history were independent predictors of response to budesonide-formoterol in reducing exacerbations (eosinophil count, p_interaction=0·013; smoking history, p_interaction=0·015).

INTERPRETATION

In patients with COPD treated with formoterol, blood eosinophil count predicts exacerbation risk and the clinical response to ICS.

FUNDING

AstraZeneca.

Determinants of exacerbation risk in patients with COPD in the TIOSPIR study

BACKGROUND

Exacerbation history is used to grade the risk of COPD exacerbation, but its reliability and relationship to other risk factors and prior therapy is unclear. To examine these interrelationships, we conducted a post hoc analysis of patients in the TIOSPIR trial with ≥2 years' follow-up or who died on treatment.

PATIENTS AND METHODS

Patients were grouped by their annual exacerbation rate on treatment into nonexacerbators, infrequent, and frequent exacerbators (annual exacerbation rates 0, ≤1, and >1, respectively), and baseline characteristics discriminating among the groups were determined. We used univariate and multivariate analyses to explore the effect of baseline characteristics on risk of exacerbation, hospitalization (severe exacerbation), and death (all causes).

RESULTS

Of 13,591 patients, 6,559 (48.3%) were nonexacerbators, 4,568 (33.6%) were infrequent exacerbators, and 2,464 (18.1%) were frequent exacerbators; 45% of patients without exacerbations in the previous year exacerbated on treatment. Multivariate analysis identified baseline pulmonary maintenance medication as a predictive factor of increased exacerbation risk, with inhaled corticosteroid treatment associated with increased exacerbation risk irrespective of exacerbation history.

CONCLUSION

Our data confirm established risk factors for exacerbation, but highlight the limitations of exacerbation history when categorizing patients and the importance of prior treatment when identifying exacerbation risk.

Reducing COPD readmissions through predictive modeling and incentive-based interventions

This paper introduces a case study at a community hospital to develop a predictive model to quantify readmission risks for patients with chronic obstructive pulmonary disease (COPD), and use it to support decision making for appropriate incentive-based interventions. Data collected from the community hospital's database are analyzed to identify risk factors and a logistic regression model is developed to predict the readmission risk within 30 days post-discharge of an individual COPD patient. By targeting on the high-risk patients, we investigate the implementability of the incentive policy which encourages patients to take interventions and helps them to overcome the compliance barrier. Specifically, the conditions and scenarios are identified for either achieving the desired readmission rate while minimizing the total cost, or reaching the lowest readmission rate under incentive budget constraint. Currently, such models are under consideration for a pilot study at the community hospital.

Prediction models for exacerbations in different COPD patient populations: comparing results of five large data sources

BACKGROUND AND OBJECTIVES

Exacerbations are important outcomes in COPD both from a clinical and an economic perspective. Most studies investigating predictors of exacerbations were performed in COPD patients participating in pharmacological clinical trials who usually have moderate to severe airflow obstruction. This study was aimed to investigate whether predictors of COPD exacerbations depend on the COPD population studied.

METHODS

A network of COPD health economic modelers used data from five COPD data sources - two population-based studies (COPDGene® and The Obstructive Lung Disease in Norrbotten), one primary care study (RECODE), and two studies in secondary care (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoint and UPLIFT) - to estimate and validate several prediction models for total and severe exacerbations (= hospitalization). The models differed in terms of predictors (depending on availability) and type of model.

RESULTS

FEV1% predicted and previous exacerbations were significant predictors of total exacerbations in all five data sources. Disease-specific quality of life and gender were predictors in four out of four and three out of five data sources, respectively. Age was significant only in the two studies including secondary care patients. Other significant predictors of total exacerbations available in one database were: presence of cough and wheeze, pack-years, 6-min walking distance, inhaled corticosteroid use, and oxygen saturation. Predictors of severe exacerbations were in general the same as for total exacerbations, but in addition low body mass index, cardiovascular disease, and emphysema were significant predictors of hospitalization for an exacerbation in secondary care patients.

CONCLUSIONS

FEV1% predicted, previous exacerbations, and disease-specific quality of life were predictors of exacerbations in patients regardless of their COPD severity, while age, low body mass index, cardiovascular disease, and emphysema seem to be predictors in secondary care patients only.

Clinic continuity of care, clinical outcomes and direct costs for COPD in Sweden: a population based cohort study

Introduction: In this study we investigate whether clinic level continuity of care (COC) for individuals with chronic obstructive pulmonary disease (COPD) is associated with better health care outcomes and lower costs in a Swedish setting. Methods: Individuals with COPD (N = 20,187) were identified through ICD-10 codes in all Stockholm County health care registries in 2007-2011 (59% female, 40% in the age group 65-74 years). We followed the individuals prospectively for 365 days after their first outpatient visit in 2012. Individual associations between COC and incidence of any hospitalization or emergency department visit and total costs for health care and pharmaceuticals were quantified by regression analysis, controlling for age, sex, comorbidity and number of visits. Clinic level COC was measured through the Bice-Boxerman COC index, grouped into quintiles. Results: At baseline, 26% of the individuals had been hospitalized at least once and 73% had dispensed at least seven prescription drugs (23% at least 16) in the last year. Patients in the lowest COC quintile (Q1) had higher probabilities of any hospitalization and any emergency department visit compared to those in Q5 (odds ratio 2.17 [95% CI 1.95-2.43] and 2.06 [1.86-2.28], respectively). Patients in Q1 also on average had 58% [95% CI: 52-64] higher costs. Conclusion: The findings show robust associations between clinic level COC and outcomes. These results verify the importance of COC, and suggest that clinic level COC is of relevance to both better outcomes for COPD patients and more efficient use of resources.

Patient Heterogeneity in Health Economic Decision Models for Chronic Obstructive Pulmonary Disease: Are Current Models Suitable to Evaluate Personalized Medicine?

OBJECTIVES

To assess how suitable current chronic obstructive pulmonary disease (COPD) cost-effectiveness models are to evaluate personalized treatment options for COPD by exploring the type of heterogeneity included in current models and by validating outcomes for subgroups of patients.

METHODS

A consortium of COPD modeling groups completed three tasks. First, they reported all patient characteristics included in the model and provided the level of detail in which the input parameters were specified. Second, groups simulated disease progression, mortality, quality-adjusted life-years (QALYs), and costs for hypothetical subgroups of patients that differed in terms of sex, age, smoking status, and lung function (forced expiratory volume in 1 second [FEV₁] % predicted). Finally, model outcomes for exacerbations and mortality for subgroups of patients were validated against published subgroup results of two large COPD trials.

RESULTS

Nine COPD modeling groups participated. Most models included sex (seven), age (nine), smoking status (six), and FEV₁% predicted (nine), mainly to specify disease progression and mortality. Trial results showed higher exacerbation rates for women (found in one model), higher mortality rates for men (two models), lower mortality for younger patients (four models), and higher exacerbation and mortality rates in patients with severe COPD (four models).

CONCLUSIONS

Most currently available COPD cost-effectiveness models are able to evaluate the cost-effectiveness of personalized treatment on the basis of sex, age, smoking, and FEV₁% predicted. Treatment in COPD is, however, more likely to be personalized on the basis of clinical parameters. Two models include several clinical patient characteristics and are therefore most suitable to evaluate personalized treatment, although some important clinical parameters are still missing.

Multi-component assessment of chronic obstructive pulmonary disease: an evaluation of the ADO and DOSE indices and the global obstructive lung disease categories in international primary care data sets

Suitable tools for assessing the severity of chronic obstructive pulmonary disease (COPD) include multi-component indices and the global initiative for chronic obstructive lung disease (GOLD) categories. The aim of this study was to evaluate the dyspnoea, obstruction, smoking, exacerbation (DOSE) and the age, dyspnoea, obstruction (ADO) indices and GOLD categories as measures of current health status and future outcomes in COPD patients. This was an observational cohort study comprising 5,114 primary care COPD patients across three databases from UK, Sweden and Holland. The associations of DOSE and ADO indices with (i) health status using the Clinical COPD Questionnaire (CCQ) and St George's Respiratory Questionnaire (SGRQ) and COPD Assessment test (CAT) and with (ii) current and future exacerbations, admissions and mortality were assessed in GOLD categories and DOSE and ADO indices. DOSE and ADO indices were significant predictors of future exacerbations: incident rate ratio was 1.52 (95% confidence intervals 1.46-1.57) for DOSE, 1.16 (1.12-1.20) for ADO index and 1.50 (1.33-1.68) and 1.23 (1.10-1.39), respectively, for hospitalisations. Negative binomial regression showed that the DOSE index was a better predictor of future admissions than were its component items. The hazard ratios for mortality were generally higher for ADO index groups than for DOSE index groups. The GOLD categories produced widely differing assessments for future exacerbation risk or for hospitalisation depending on the methods used to calculate them. None of the assessment systems were excellent at predicting future risk in COPD; the DOSE index appears better than the ADO index for predicting many outcomes, but not mortality. The GOLD categories predict future risk inconsistently. The DOSE index and the GOLD categories using exacerbation frequency may be used to identify those at high risk for exacerbations and admissions.

Early response to inhaled bronchodilators and corticosteroids as a predictor of 12-month treatment responder status and COPD exacerbations

Background

Early treatment response markers, for example, improvement in forced expiratory volume in 1 second (FEV₁) and St George’s Respiratory Questionnaire (SGRQ) total score, may help clinicians to better manage patients with chronic obstructive pulmonary disease (COPD). We investigated the prevalence of clinically important improvements in FEV₁ and SGRQ scores after 2-month budesonide/formoterol or formoterol treatment and whether such improvements predict subsequent improvements and exacerbation rates.

Methods

This post hoc analysis is based on data from three double-blind, randomized studies in patients with moderate-to-very-severe COPD receiving twice-daily budesonide/formoterol or formoterol alone for 6 or 12 months. Prebronchodilator FEV₁ and SGRQ total score were measured before treatment and at 2 and 12 months; COPD exacerbation rates were measured during months 2–12. Responders were defined by ≥100 mL improvement in prebronchodilator FEV₁ and ≥4-point decrease in SGRQ total score.

Results

Overall, 2,331 and 1,799 patients were included in the 0–2- and 0–12-month responder analyses, respectively, and 2,360 patients in the 2–12-month exacerbation rate analysis. At 2 months, 35.1% of patients were FEV₁ responders and 44.3% were SGRQ responders. The probability of response was significantly greater with budesonide/formoterol than with formoterol or placebo for both parameters. Two-month responders had a greater chance of 12-month response than 2-month nonresponders for both FEV₁ (odds ratio, 5.57; 95% confidence interval, 4.14–7.50) and SGRQ (odds ratio, 3.87; 95% confidence interval, 2.83–5.31). Two-month response in FEV₁ (P<0.001), but not SGRQ (P=0.11), was associated with greater reductions in exacerbation risk.

Conclusion

Early FEV₁ and SGRQ treatment responses relate to their changes at 12 months. FEV₁ response, but not SGRQ response, at 2 months predicts the risk of a future COPD exacerbation in some, but not all patients. This is potentially useful in clinical practice, although more sensitive and specific markers of favorable treatment response are required.

Patient reported outcome measures in chronic obstructive pulmonary disease: Which to use?

Patient-reported outcomes (PROs), such as symptoms and perceived health status, are essential in chronic obstructive pulmonary disease (COPD) for determining disease severity, impact on daily life, effect of treatment and recovery from exacerbations. This field has evolved rapidly and there are a plethora of instruments assessing different PROs. The aim of this review is to provide an understanding of the concept of PROs in COPD. The PROs reflect important aspects of COPD which have a direct impact on daily life. Common symptoms such as dyspnea, cough, phlegm, anxiety, fatigue, and pain and as well as physical function and the risk for and occurrence of acute exacerbations should be assessed both in the clinic and in research. Besides impact on daily life, some of the PROs are related to disease progress and mortality. Construction of composite variables including different disease specific and generic PROs provide a general estimation of health status.

Risk of exacerbation in chronic obstructive pulmonary disease: a primary care retrospective cohort study

Background

The risk of exacerbation in chronic obstructive pulmonary disease (COPD) depends on the severity of disease and other less well known factors. Predictive models of exacerbation are more accurate than the forced expiratory volume in one second (FEV1). The objective was to design a model that predicts the risk of exacerbation in COPD.

Methods

Retrospective cohort study with data from the electronic medical records of patients diagnosed with COPD in the province of Lleida (Spain). A total of 2501 patients were followed during 3 years. The dependent variable was acute exacerbation; independent variables were: clinical parameters, spirometry results, severity of disease, influenza and 23-valent pneumococcal immunisation, comorbidities, smoking and history of exacerbation. The association of these variables with disease exacerbation was measured by the adjusted odds ratio using a logistic regression model.

Results

Mean age at the start of the study was 68.38 years (SD = 11.60) and 74.97 % patients were men; severity of disease was considered mild in 50.82 % of patients, moderate in 35.31 %, severe in 9.44 % and very severe in 4.44 %. During the three year study period up to 83.17 % of patients experienced at least one exacerbation. Predictive factors in the model were age, gender, previous exacerbations, influenza and 23-valent pneumococcal immunisations, number of previous visits to the General Practice and severity (GOLD), with an area under the ROC curve (AUROC) of 0.70.

Conclusions

This model can identify patients at high risk of acute exacerbation. Preventive measures and modification of treatment in these high-risk patients would improve survival.

Predicting frequent COPD exacerbations using primary care data

PURPOSE

Acute COPD exacerbations account for much of the rising disability and costs associated with COPD, but data on predictive risk factors are limited. The goal of the current study was to develop a robust, clinically based model to predict frequent exacerbation risk.

PATIENTS AND METHODS

Patients identified from the Optimum Patient Care Research Database (OPCRD) with a diagnostic code for COPD and a forced expiratory volume in 1 second/forced vital capacity ratio <0.7 were included in this historical follow-up study if they were ≥40 years old and had data encompassing the year before (predictor year) and year after (outcome year) study index date. The data set contained potential risk factors including demographic, clinical, and comorbid variables. Following univariable analysis, predictors of two or more exacerbations were fed into a stepwise multivariable logistic regression. Sensitivity analyses were conducted for subpopulations of patients without any asthma diagnosis ever and those with questionnaire data on symptoms and smoking pack-years. The full predictive model was validated against 1 year of prospective OPCRD data.

RESULTS

The full data set contained 16,565 patients (53% male, median age 70 years), including 9,393 patients without any recorded asthma and 3,713 patients with questionnaire data. The full model retained eleven variables that significantly predicted two or more exacerbations, of which the number of exacerbations in the preceding year had the strongest association; others included height, age, forced expiratory volume in 1 second, and several comorbid conditions. Significant predictors not previously identified included eosinophilia and COPD Assessment Test score. The predictive ability of the full model (C statistic 0.751) changed little when applied to the validation data set (n=2,713; C statistic 0.735). Results of the sensitivity analyses supported the main findings.

CONCLUSION

Patients at risk of exacerbation can be identified from routinely available, computerized primary care data. Further study is needed to validate the model in other patient populations.

Reliever salbutamol use as a measure of exacerbation risk in chronic obstructive pulmonary disease

BACKGROUND

Debate exists regarding which endpoints most sensitively reflect day-to-day variation in chronic obstructive pulmonary disease (COPD) symptoms and are most useful in clinical practice to predict COPD exacerbations. We hypothesized that short-acting β2-agonist (SABA) reliever use would predict short- and long-term exacerbation risk in COPD patients.

METHODS

We performed a retrospective analysis of data from a study (ClinicalTrials.gov registration: NCT00419744) comparing budesonide/formoterol 320/9 μg with formoterol 9 μg (both twice daily) in patients with moderate-to-very-severe COPD; reliever salbutamol 90 μg was provided. First occurrence of reliever use >4 (low), >10 (medium), and >20 (high) inhalations/day was assessed as a predictor of short-term (3-week) exacerbation risk. Mean daily reliever use in the week preceding the 2-month visit was investigated as a predictor of the long-term (10-month) exacerbation risk, using intervals of 2-5, 6-9, and ≥10 inhalations/day.

RESULTS

Overall, 810 patients were included (61 % male; mean age 63.2 years; post-bronchodilator forced expiratory volume in 1 s 37.7 % of predicted). First occurrence of low, medium, or high reliever use was predictive of an exacerbation within the following 3 weeks; exacerbation risk increased significantly with increasing reliever use. Mean reliever use over 1 week was predictive of long-term exacerbation risk. Patients with mean use of 2-5, 6-9, and ≥10 inhalations/day exhibited 21 %, 67 %, and 135 % higher exacerbation rates, respectively, in the following 10 months, compared with <2 inhalations/day. Budesonide/formoterol was associated with lower short- and long-term exacerbation risk than formoterol in all reliever-use groups.

CONCLUSIONS

SABA reliever use is a predictor of short- and long-term exacerbation risk in moderate-to-very-severe COPD patients with a history of exacerbations receiving budesonide/formoterol or formoterol.