Risk Factors for Recurrent Exacerbations in the General-Practitioner-Based Swiss Chronic Obstructive Pulmonary Disease (COPD) Cohort

Overview

Journal J Clin Med

Specialty General Medicine

Date 2023 Oct 28

PMID 37892832

Authors

Nebal S Abu Hussein

Stephanie Giezendanner

Pascal Urwyler

Pierre-Olivier Bridevaux

Prashant N Chhajed

Thomas Geiser

Ladina Joos Zellweger

Malcolm Kohler

David Miedinger

Zahra Pasha

Robert Thurnheer

Christophe von Garnier

Joerg D Leuppi

Affiliations

Soon will be listed here.

Abstract

Background: Patients with chronic obstructive pulmonary disease (COPD) often suffer from acute exacerbations. Our objective was to describe recurrent exacerbations in a GP-based Swiss COPD cohort and develop a statistical model for predicting exacerbation.

Methods: COPD cohort demographic and medical data were recorded for 24 months, by means of a questionnaire-based COPD cohort. The data were split into training (75%) and validation (25%) datasets. A negative binomial regression model was developed using the training dataset to predict the exacerbation rate within 1 year. An exacerbation prediction model was developed, and its overall performance was validated. A nomogram was created to facilitate the clinical use of the model.

Results: Of the 229 COPD patients analyzed, 77% of the patients did not experience exacerbation during the follow-up. The best subset in the training dataset revealed that lower forced expiratory volume, high scores on the MRC dyspnea scale, exacerbation history, and being on a combination therapy of LABA + ICS (long-acting beta-agonists + Inhaled Corticosteroids) or LAMA + LABA (Long-acting muscarinic receptor antagonists + long-acting beta-agonists) at baseline were associated with a higher rate of exacerbation. When validated, the area-under-curve (AUC) value was 0.75 for one or more exacerbations. The calibration was accurate (0.34 predicted exacerbations vs 0.28 observed exacerbations).

Conclusion: Nomograms built from these models can assist clinicians in the decision-making process of COPD care.

References

Jochmann A, Neubauer F, Miedinger D, Schafroth S, Tamm M, Leuppi J . General practitioner's adherence to the COPD GOLD guidelines: baseline data of the Swiss COPD Cohort Study. Swiss Med Wkly. 2010; 140. DOI: 10.4414/smw.2010.13053. View

Jones P, Harding G, Berry P, Wiklund I, Chen W, Leidy N . Development and first validation of the COPD Assessment Test. Eur Respir J. 2009; 34(3):648-54. DOI: 10.1183/09031936.00102509. View

Chaudhary M, Hoffman E, Guo J, Comellas A, Newell Jr J, Nagpal P . Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study. Lancet Digit Health. 2023; 5(2):e83-e92. PMC: 9896720. DOI: 10.1016/S2589-7500(22)00232-1. View

Muller D, Johansson M, Brennan P . Lung Cancer Risk Prediction Model Incorporating Lung Function: Development and Validation in the UK Biobank Prospective Cohort Study. J Clin Oncol. 2017; 35(8):861-869. DOI: 10.1200/JCO.2016.69.2467. View

Fletcher C . The clinical diagnosis of pulmonary emphysema; an experimental study. Proc R Soc Med. 1952; 45(9):577-84. View

Yii A, Loh C, Tiew P, Xu H, Taha A, Koh J . A clinical prediction model for hospitalized COPD exacerbations based on "treatable traits". Int J Chron Obstruct Pulmon Dis. 2019; 14:719-728. PMC: 6443227. DOI: 10.2147/COPD.S194922. View

Donaldson G, Goldring J, Wedzicha J . Influence of season on exacerbation characteristics in patients with COPD. Chest. 2011; 141(1):94-100. DOI: 10.1378/chest.11-0281. View

Vestbo J, Hurd S, Agusti A, Jones P, Vogelmeier C, Anzueto A . Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2012; 187(4):347-65. DOI: 10.1164/rccm.201204-0596PP. View

Marshall D, Al Omari O, Goodall R, Shalhoub J, Adcock I, Chung K . Trends in prevalence, mortality, and disability-adjusted life-years relating to chronic obstructive pulmonary disease in Europe: an observational study of the global burden of disease database, 2001-2019. BMC Pulm Med. 2022; 22(1):289. PMC: 9336030. DOI: 10.1186/s12890-022-02074-z. View

10.

Siro C, Bastos P, Knaus W, Wagner D . APACHE II scores in the prediction of multiple organ failure syndrome. Arch Surg. 1991; 126(4):528-9. DOI: 10.1001/archsurg.1991.01410280132022. View

11.

Bertens L, Reitsma J, Moons K, van Mourik Y, Lammers J, Broekhuizen B . Development and validation of a model to predict the risk of exacerbations in chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2013; 8:493-9. PMC: 3797610. DOI: 10.2147/COPD.S49609. View

12.

Wells P, Anderson D, Rodger M, Ginsberg J, Kearon C, Gent M . Derivation of a simple clinical model to categorize patients probability of pulmonary embolism: increasing the models utility with the SimpliRED D-dimer. Thromb Haemost. 2000; 83(3):416-20. View

13.

Donaldson G, Hurst J, Smith C, Hubbard R, Wedzicha J . Increased risk of myocardial infarction and stroke following exacerbation of COPD. Chest. 2009; 137(5):1091-7. DOI: 10.1378/chest.09-2029. View

14.

Kate R, Pearce N, Mazumdar D, Nilakantan V . A continual prediction model for inpatient acute kidney injury. Comput Biol Med. 2020; 116:103580. DOI: 10.1016/j.compbiomed.2019.103580. View

15.

Sundh J, Efraimsson E, Janson C, Montgomery S, Stallberg B, Lisspers K . Management of COPD exacerbations in primary care: a clinical cohort study. Prim Care Respir J. 2013; 22(4):393-9. PMC: 6442855. DOI: 10.4104/pcrj.2013.00087. View

16.

Mullerova H, Maselli D, Locantore N, Vestbo J, Hurst J, Wedzicha J . Hospitalized exacerbations of COPD: risk factors and outcomes in the ECLIPSE cohort. Chest. 2014; 147(4):999-1007. DOI: 10.1378/chest.14-0655. View

17.

Rabe K, Hurd S, Anzueto A, Barnes P, Buist S, Calverley P . Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med. 2007; 176(6):532-55. DOI: 10.1164/rccm.200703-456SO. View

18.

Hoogendoorn M, Feenstra T, Boland M, Briggs A, Borg S, Jansson S . Prediction models for exacerbations in different COPD patient populations: comparing results of five large data sources. Int J Chron Obstruct Pulmon Dis. 2017; 12:3183-3194. PMC: 5677310. DOI: 10.2147/COPD.S142378. View

19.

Glaab T, Vogelmeier C, Hellmann A, Buhl R . Guideline-based survey of outpatient COPD management by pulmonary specialists in Germany. Int J Chron Obstruct Pulmon Dis. 2012; 7:101-8. PMC: 3282602. DOI: 10.2147/COPD.S27887. View

20.

Perez X, Wisnivesky J, Lurslurchachai L, Kleinman L, Kronish I . Barriers to adherence to COPD guidelines among primary care providers. Respir Med. 2011; 106(3):374-81. PMC: 3377746. DOI: 10.1016/j.rmed.2011.09.010. View