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      Predicting frequent COPD exacerbations using primary care data

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          Abstract

          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.

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          Most cited references 27

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          Chronic obstructive pulmonary disease

          Summary Chronic obstructive pulmonary disease (COPD) is characterised by progressive airflow obstruction that is only partly reversible, inflammation in the airways, and systemic effects or comorbities. The main cause is smoking tobacco, but other factors have been identified. Several pathobiological processes interact on a complex background of genetic determinants, lung growth, and environmental stimuli. The disease is further aggravated by exacerbations, particularly in patients with severe disease, up to 78% of which are due to bacterial infections, viral infections, or both. Comorbidities include ischaemic heart disease, diabetes, and lung cancer. Bronchodilators constitute the mainstay of treatment: β2 agonists and long-acting anticholinergic agents are frequently used (the former often with inhaled corticosteroids). Besides improving symptoms, these treatments are also thought to lead to some degree of disease modification. Future research should be directed towards the development of agents that notably affect the course of disease.
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            The clinical features of the overlap between COPD and asthma

            Background The coexistence of COPD and asthma is widely recognized but has not been well described. This study characterizes clinical features, spirometry, and chest CT scans of smoking subjects with both COPD and asthma. Methods We performed a cross-sectional study comparing subjects with COPD and asthma to subjects with COPD alone in the COPDGene Study. Results 119 (13%) of 915 subjects with COPD reported a history of physician-diagnosed asthma. These subjects were younger (61.3 vs 64.7 years old, p = 0.0001) with lower lifetime smoking intensity (43.7 vs 55.1 pack years, p = 0.0001). More African-Americans reported a history of asthma (33.6% vs 15.6%, p < 0.0001). Subjects with COPD and asthma demonstrated worse disease-related quality of life, were more likely to have had a severe COPD exacerbation in the past year, and were more likely to experience frequent exacerbations (OR 3.55 [2.19, 5.75], p < 0.0001). Subjects with COPD and asthma demonstrated greater gas-trapping on chest CT. There were no differences in spirometry or CT measurements of emphysema or airway wall thickness. Conclusion Subjects with COPD and asthma represent a relevant clinical population, with worse health-related quality of life. They experience more frequent and severe respiratory exacerbations despite younger age and reduced lifetime smoking history. Trial registration ClinicalTrials.gov: NCT00608764
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              GOLD 2011 disease severity classification in COPDGene: a prospective cohort study.

              The 2011 GOLD (Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease [COPD]) consensus report uses symptoms, exacerbation history, and forced expiratory volume (FEV1)% to categorise patients according to disease severity and guide treatment. We aimed to assess both the influence of symptom instrument choice on patient category assignment and prospective exacerbation risk by category. Patients were recruited from 21 centres in the USA, as part of the COPDGene study. Eligible patients were aged 45-80 years, had smoked for 10 pack-years or more, and had an FEV1/forced vital capacity (FVC) <0·7. Categories were defined with the modified Medical Research Council (mMRC) dyspnoea scale (score 0-1 vs ≥2) and the St George's Respiratory Questionnaire (SGRQ; ≥25 vs <25 as a surrogate for the COPD Assessment Test [CAT] ≥10 vs <10) in addition to COPD exacerbations in the previous year (<2 vs ≥ 2), and lung function (FEV1% predicted ≥50 vs <50). Statistical comparisons were done with k-sample permutation tests. This study cohort is registered with ClinicalTrials.gov, number NCT00608764. 4484 patients with COPD were included in this analysis. Category assignment using the mMRC scale versus SGRQ were similar but not identical. On the basis of the mMRC scale, 1507 (33·6%) patients were assigned to category A, 919 (20·5%) to category B, 355 (7·9%) to category C, and 1703 (38·0%) to category D; on the basis of the SGRQ, 1317 (29·4%) patients were assigned to category A, 1109 (24·7%) to category B, 221 (4·9%) to category C, and 1837 (41·0%) to category D (κ coefficient for agreement, 0·77). Significant heterogeneity in prospective exacerbation rates (exacerbations/person-years) were seen, especially in the D subcategories, depending on the risk factor that determined category assignment (lung function only [0·89, 95% CI 0·78-1·00]), previous exacerbation history only [1·34, 1·0-1·6], or both [1·86, 1·6-2·1; p<0·0001]). The GOLD classification emphasises the importance of symptoms and exacerbation risk when assessing COPD severity. The choice of symptom measure influences category assignment. The relative number of patients with low symptoms and high risk for exacerbations (category C) is low. Differences in exacerbation rates for patients in the highest risk category D were seen depending on whether risk was based on lung function, exacerbation history, or both. National Heart, Lung, and Blood Institute, and the COPD Foundation through contributions from AstraZeneca, Boehringer Ingelheim, Novartis, and Sepracor. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Int J Chron Obstruct Pulmon Dis
                Int J Chron Obstruct Pulmon Dis
                International Journal of COPD
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove Medical Press
                1176-9106
                1178-2005
                2015
                09 November 2015
                : 10
                : 2439-2450
                Affiliations
                [1 ]Research in Real-Life, Cambridge, UK
                [2 ]Mundesley Medical Centre, Norfolk, UK
                [3 ]Plymouth University Peninsula School of Medicine and Dentistry, Plymouth, UK
                [4 ]Respiratory Effectiveness Group, Cambridge, UK
                [5 ]Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Aberdeen, UK
                Author notes
                Correspondence: David B Price, Academic Primary Care, Division of Applied Health Sciences, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK, Tel +44 12 2455 4588, Fax +44 12 2455 0683, Email dprice@ 123456rirl.org
                Article
                copd-10-2439
                10.2147/COPD.S94259
                4644169
                © 2015 Kerkhof et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License

                The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Respiratory medicine

                fev1, prediction, risk factor, model, validation

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