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. 2022 Jul 29:17:1703-1713.
doi: 10.2147/COPD.S364812. eCollection 2022.

Disease Progression and Age as Factors Underlying Multimorbidity in Patients with COPD: Results from COSYCONET

Peter Alter  1 , Kathrin Kahnert  2 , Franziska C Trudzinski  3 , Robert Bals  4 , Henrik Watz  5 , Tim Speicher  1 , Sandra Söhler  1 , Stefan Andreas  6 , Tobias Welte  7 , Klaus F Rabe  8 , Emiel F M Wouters  9 , Antonia Sassmann-Schweda  10 , Hubert Wirtz  11 , Joachim H Ficker  12   13 , Claus F Vogelmeier  1 , Rudolf A Jörres  14
Affiliations

Disease Progression and Age as Factors Underlying Multimorbidity in Patients with COPD: Results from COSYCONET

Peter Alter et al. Int J Chron Obstruct Pulmon Dis. .

Abstract

Background: Multimorbidity plays an important role in chronic obstructive pulmonary disease (COPD) but is also a feature of ageing. We estimated to what extent increases in the prevalence of multimorbidity over time are attributable to COPD progression compared to increasing patient age.

Methods: Patients with COPD from the long-term COSYCONET (COPD and Systemic Consequences - Comorbidities Network) cohort with four follow-up visits were included in this analysis. At each visit, symptoms, exacerbation history, quality of life and lung function were assessed, along with the comorbidities heart failure (HF), coronary artery disease (CAD), peripheral arterial disease (PAD), hypertension, sleep apnea, diabetes mellitus, hyperlipidemia, hyperuricemia and osteoporosis. Using longitudinal logistic regression analysis, we determined what proportion of the increase in the prevalence of comorbidities could be attributed to patients' age or to the progression of COPD over visits.

Results: Of 2030 patients at baseline, 878 completed four follow-up visits (up to 4.5 years). CAD prevalence increased over time, with similar effects attributable to the 4.5-year follow-up, used as indicator of COPD progression, and to a 5-year increase in patients' age. The prevalence of HF, diabetes, hyperlipidemia, hyperuricemia, osteoporosis and sleep apnea showed stronger contributions of COPD progression than of age; in contrast, age dominated for hypertension and PAD. There were different relationships to patients' characteristics including BMI and sex. The results were not critically dependent on the duration of COPD prior to enrolment, or the inclusion of patients with all four follow-up visits vs those attending only at least one of them.

Conclusion: Analyzing the increasing prevalence of multimorbidity in COPD over time, we separated age-independent contributions, probably reflecting intrinsic COPD-related disease progression, from age-dependent contributions. This distinction might be useful for the individual assessment of disease progression in COPD.

Keywords: chronic obstructive pulmonary disease; comorbidities; disease progression; multimorbidity; prognosis.

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Conflict of interest statement

Dr Franziska C Trudzinski reports personal fees from Novartis AG, non-financial support from CSL Behring, personal fees from Boehringer Ingelheim, personal fees from GlaxoSmithKline, personal fees from Chiesi, outside the submitted work. Professor Dr Robert Bals reports grants from BMBF, grants from Marburg University, during the conduct of the study; grants, personal fees from Various, outside the submitted work. Prof Dr Stefan Andreas reports grants from Boehringer, personal fees from Altana, Boehringer, AZ, GSK, Chiesi, GSK, Novartis, Menerini, outside the submitted work. Professor Dr Tobias Welte reports grants from German Ministry of Research and Education, during the conduct of the study. Dr Antonia Sassmann-Schweda reports Contractual payments for conduction of study visits; payments were made to Research Center Borstel, Center for Clinical Studies from Philipps University of Marburg, during the conduct of the study. Professor Dr Joachim H Ficker reports personal fees, non-financial support from CSL Behring, personal fees from Novartis, personal fees from AstraZeneca, personal fees from Boehringer, personal fees from Pfizer, outside the submitted work; Prof Dr Claus F Vogelmeier reports personal fees from Aerogen, grants, personal fees from AstraZeneca, grants, personal fees from Boehringer Ingelheim, grants, personal fees from CSL Behring, grants, personal fees from Chiesi, grants, personal fees from GlaxoSmithKline, grants, personal fees from Grifols, personal fees from Menarini, grants, personal fees from Novartis, personal fees from Nuvaira, personal fees from MedUpdate, outside the submitted work. The authors report no other conflicts of interest in this work.

Figures

Figure 1
Figure 1
Prevalence of comorbidities over the study visits 1 to 5, scheduled at enrolment and follow-up after 6, 18, 36 and 54 months, respectively. Data refer to patients with all four follow-up visits.
Figure 2
Figure 2
Results from generalized logistic regression models for the prevalence of comorbidities. Dependent variables are given in the headline and estimated regression coefficients in the columns. The effects of age are given per 5 years, of BMI per 5 units, of VAS per 20 units, and of FEV1 per 10% predicted. Scales are different among comorbidities. Significance levels are denoted as follows: +p<0.05, ++p<0.01 and +++p<0.001. Data refer to patients with all four follow-up visits, and numerical values are given in Table 3 (further details are given in Supplemental Table S1).
See this image and copyright information in PMC

References

    1. Vanfleteren LE, Spruit MA, Groenen M, et al. Clusters of comorbidities based on validated objective measurements and systemic inflammation in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2013;187(7):728–735. doi: 10.1164/rccm.201209-1665OC - DOI - PubMed
    1. Alter P, Mayerhofer BA, Kahnert K, et al. Prevalence of cardiac comorbidities, and their underdetection and contribution to exertional symptoms in COPD: results from the COSYCONET cohort. Int J Chron Obstruct Pulmon Dis. 2019;14:2163–2172. doi: 10.2147/COPD.S209343 - DOI - PMC - PubMed
    1. Karch A, Vogelmeier C, Welte T, et al. The German COPD cohort COSYCONET: aims, methods and descriptive analysis of the study population at baseline. Respir Med. 2016;114:27–37. doi: 10.1016/j.rmed.2016.03.008 - DOI - PubMed
    1. Alter P, Lucke T, Watz H, et al. Predictors of mortality and exacerbations in patients with stable COPD. Submitted. 2021;4:54.
    1. Alter P, Baker JR, Dauletbaev N, et al. Update in chronic obstructive pulmonary disease 2019. Am J Respir Crit Care Med. 2020;202(3):348–355. doi: 10.1164/rccm.202002-0370UP - DOI - PMC - PubMed

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