Pulmonary biomarkers in chronic obstructive pulmonary disease

被引:200
作者
Barnes, Peter J.
Chowdhury, Badrul
Kharitonov, Sergei A.
Magnussen, Helgo
Page, Clive P.
Postma, Dirkje
Saetta, Marina
机构
[1] Kings Coll London, Natl Heart & Lung Inst, Imperial Coll London, Guys Kings & St Thomas Sch Biomed Sci, London SW3 6LY, England
[2] US FDA, Rockville, MD 20857 USA
[3] Ctr Pneumol & Thorac Surg, Grosshansdorf, Germany
[4] Univ Groningen Hosp, Groningen, Netherlands
[5] Univ Padua, Dept Cardiothorac & Vasc Sci, Padua, Italy
关键词
bronchial biopsy; bronchoalveolar lavage; exhaled breath; condensate; exhaled nitric oxide; induced sputum;
D O I
10.1164/rccm.200510-1659PP
中图分类号
R4 [临床医学];
学科分类号
1002 ; 100602 ;
摘要
There has been increasing interest in using pulmonary biomarkers to understand and monitor the inflammation in the respiratory tract of patients with chronic obstructive pulmonary disease (COPD). In this Pulmonary Perspective we discuss the merits of the various approaches by reviewing the current literature on pulmonary biomarkers in COPD and underscore the need for more systematic studies in the future. Bronchial biopsies and bronchoalveolar lavage provide valuable information about inflammatory cells and mediators, but are invasive, so that repeated measurements have to be very limited in assessing any interventions. Induced sputum has provided considerable information about the inflammatory process, including mediators and proteinases in COPD, but selectively samples proximal airways and may not closely reflect distal inflammatory processes. Exhaled gases and breath condensate are noninvasive procedures, so repeated measurements are possible, but for some assays the variability is relatively high. There is relatively little information about how any of these biomarkers relate to other clinical outcomes, such as progression of the disease, severity of disease, clinical subtypes, or response to therapy. More information is also needed about the variability in these measurements. In the future, pulmonary biomarkers may be useful in predicting disease progression, indicating disease instability, and in predicting response to current therapies and novel therapies, many of which are now in development.
引用
收藏
页码:6 / 14
页数:9
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