The German COPD cohort COSYCONET: Aims, methods and descriptive analysis of the study population at baseline

被引:112
|
作者
Karch, Annika [1 ]
Vogelmeier, Claus [2 ]
Welte, Tobias [3 ]
Bals, Robert [4 ]
Kauczor, Hans-Ulrich [5 ]
Biederer, Juergen [5 ]
Heinrich, Joachim [6 ]
Schulz, Holger [6 ]
Glaeser, Sven [7 ]
Holle, Rolf [8 ]
Watz, Henrik [9 ]
Korn, Stephanie [10 ]
Adaskina, Nina [1 ]
Biertz, Frank [1 ]
Vogel, Charlotte [1 ]
Vestbo, Jorgen [11 ]
Wouters, Emiel F. M. [12 ,13 ]
Rabe, Klaus Friedrich
Soehler, Sandra [14 ]
Koch, Armin [1 ]
Joerres, Rudolf A. [14 ]
机构
[1] Hannover Med Sch, Inst Biostat, Carl Neuberg Str 1, D-30625 Hannover, Germany
[2] Univ Marburg, UGMLC, German Ctr Lung Res, Dept Resp Med, Baldingerstr, D-35043 Marburg, Germany
[3] Hannover Med Sch, German Ctr Lung Res, Clin Pneumol, Carl Neuberg Str 1, D-30625 Hannover, Germany
[4] Saarland Univ Hosp, Dept Internal Med 5, Pulmonol Allergol Resp Intens Care Med, Kirrberger Str 1, D-66424 Homburg, Germany
[5] Heidelberg Univ, TLRC, German Ctr Lung Res, Dept Diagnost & Intervent Radiol, Neuenheimer Feld 110, D-69120 Heidelberg, Germany
[6] Helmholtz Zentrum Munchen, German Ctr Lung Res, CPC M, German Res Ctr Environm Hlth,Inst Epidemiol, Ingolstaedter Landstr 1, D-85764 Neuherberg, Germany
[7] Univ Med Greifswald, Dept Internal Med B, Cardiol Intens Care Pulm Med & Infect Dis, Div Pneumol & Pneumol Epidemiol, Ferdinand Sauerbruch Str, D-17475 Greifswald, Germany
[8] Helmholtz Zentrum Munchen GmbH, German Res Ctr Environm Hlth, German Ctr Lung Res, Comprehens Pneumol Ctr Munich CPC M,Inst Hlth Eco, D-85764 Neuherberg, Germany
[9] Airway Res Ctr North, German Ctr Lung Res, Pulm Res Inst, LungenClin Grosshansdorf, Woehrendamm 80, D-22927 Grosshansdorf, Germany
[10] Mainz Univ Hosp, Dept Pulm, Langenbeckstr 1, D-55131 Mainz, Germany
[11] Univ Manchester, Inst Inflammat & Repair, Ctr Resp Med & Allergy, Southmoor Rd, Manchester M23 9LT, Lancs, England
[12] Maastricht Univ Med Ctr, Dept Resp Med, P Debyelaan 25, NL-6202 AZ Maastricht, Netherlands
[13] Univ Marburg, ASCONET Study Coordinat Off, Baldingerstr, D-35043 Marburg, Germany
[14] Univ Munich, Inst & Outpatient Clin Occupat Social & Environm, Ziemssenstr 1, D-80336 Munich, Germany
关键词
COPD; Comorbidity; Systemic inflammation; Cohort; Study design; OBSTRUCTIVE PULMONARY-DISEASE; AIR-FLOW LIMITATION; SYSTEMIC INFLAMMATION; GOLD CLASSIFICATION; REFERENCE VALUES; LUNG-FUNCTION; COMORBIDITIES; HEALTH; IMPACT; STANDARDIZATION;
D O I
10.1016/j.rmed.2016.03.008
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: The German COPD cohort study COSYCONET ("COPD and SYstemic consequences-COmorbidities NETwork") investigates the interaction of lung disease, comorbidities and systemic inflammation. Recruitment took place from 2010 to 2013 in 31 study centers. In addition to the baseline visit, follow-up visits are scheduled at 6, 18, 36 and 54 months after baseline. The study also comprises a biobank, image bank, and includes health economic data. Here we describe the study design of COSYCONET and present baseline data of our COPD cohort. Methods: Inclusion criteria were broad in order to cover a wide range of patterns of the disease. In each visit, patients undergo a large panel of assessments including e.g. clinical history, spirometry, body plethysmography, diffusing capacity, blood samples, 6-min walk-distance, electrocardiogram and echocardiography. Chest CTs are collected if available and CTs and MRIs are performed in a subcohort. Data are entered into eCRFs and subjected to several stages of quality control. Results: Overall, 2741 subjects with a clinical diagnosis of COPD were included (59% male; mean age 65 +/- 8.6 years (range 40-90)). Of these, 8/35/32/9% presented with GOLD stages I-IV; 16% were uncategorized, including the former GOLD-0 category. 24% were active smokers, 68% ex-smokers and 8% never-smokers. Data completeness was 96% for the baseline items. Conclusion: The German COPD cohort comprises patients with advanced and less advanced COPD. This is particularly useful for studying the time course of COPD in relation to comorbidities. Baseline data indicate that COSYCONET offers the opportunity to investigate our research questions in a large-scale, high-quality dataset. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:27 / 37
页数:11
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