Clinical and laboratory parameters in assessing the risk of exacerbations in chronic obstructive pulmonary disease

Cite item

Full Text


Aim. To estimate the significance of measuring the concentrations of cytokines and immunoglobulins and the relative counts of lymphocyte subpopulations in peripheral blood, as well as clinical parameters in patients with chronic obstructive pulmonary disease (COPD) in order to assess the risk of exacerbations. Subjects and methods. Thirty-seven patients with COPD were examined. A study group consisted of 31 patients. Patients with rare exacerbations were assigned to those who had no or one case; patients with frequent exacerbations were those who had two or more cases a year after examination. A prognostic model was created using the binary logistic regression analysis. Results. A significant statistical model was developed as a regression equation involving 4 indicators (vascular endothelial growth factor, C-reactive protein, CAT scores, and number of exacerbations in the previous year). This mathematical model can predict frequent exacerbations in next year with a sensitivity of 94.1% and a specificity of 80%. Conclusion. The mathematical model created to estimate the risk of frequent exacerbations may be used to elaborate adequate individual treatment regimens for both smoking and non-smoking patients with COPD.


  1. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease. Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2011.
  2. Sin D.D., Vestbo J. Biomarkers in chronic obstructive pulmonary disease. Proc Am Thorac Soc 2009; 6: 543—545.
  3. Salvi S.S., Barnes P.J. Chronic obstructive pulmonary disease in non-smokers. Lancet 2009; 374 (9691): 733—743.
  4. Кадушкин А.Г., Таганович А.Д., Лаптева И.М. Эпидемиологические особенности хронической обструктивной болезни легких у городских жителей Республики Беларусь. Здравоохранение 2013; 7: 21—25.
  5. Suissa S., Dellʹaniello S., Ernst P. Long-term natural history of chronic obstructive pulmonary disease: severe exacerbations and mortality. Thorax 2012; 67: 957—963.
  6. Simoens S., Laekeman G., Decramer M. Preventing COPD exacerbations with macrolides: a review and budget impact analysis. Respir Med 2013; 107 (5): 637—648.
  7. Anzueto A. Impact of exacerbations on COPD. Eur Respir Rev 2010; 19 (116): 113—118.
  8. Hurst J.R., Vestbo J., Anzueto A. et al. Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) Investigators. Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med 2010; 363 (12): 1128—1138.
  9. Thomsen M., Ingebrigtsen T.S., Marott J.L. et al. Inflammatory biomarkers and exacerbations in chronic obstructive pulmonary disease. JAMA 2013; 309 (22): 2353—2361.
  10. Bertens L.C., Reitsma J.B., Moons K.G. et al. 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—499.
  11. Кадушкин А.Г., Таганович А.Д. Молекулярно-клеточные механизмы развития хронической обструктивной болезни легких. Военная медицина 2012; 1: 132—138.
  12. Barnes P.J. The cytokine network in chronic obstructive pulmonary disease. Am J Respir Cell Mol Biol 2009; 41 (6): 631—638.
  13. Gan W.Q., Man S.F., Sin D.D. Association between chronic obstructive pulmonary disease and systemic inflammation: a systematic review and a meta-analysis. Thorax 2004; 59: 574—580.
  14. Shopland D.R., Hartman A.M., Gibson J.T. et al. Cigarette smoking among U.S. adults by state and region: estimates from the current population survey. J Natl Cancer Inst 1996; 88: 1748—1758.
  15. Wanger J., Clausen J.L., Coates A. et al. Standartisation of the measurement of lung volumes. Eur Respir J 2005; 26 (3): 511—522.
  16. Zweig M.H., Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 1993; 39 (4): 561—577.
  17. Celli B.R., Locantore N., Yates J. et al. Inflammatory biomarkers improve clinical prediction of mortality in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2012; 185 (10): 1065—1072.
  18. Кадушкин А.Г., Шман Т.В., Новиков В.П. и др. Особенности количественного изменения регуляторных T-лимфоцитов у пациентов с хронической обструктивной болезнью легких. Пульмонология 2013; 3: 26—30.
  19. Serapinas D., Narbekovas A., Juskevicius J. et al. Systemic inflammation in COPD in relation to smoking status. Multidiscip Respir Med 2011; 6 (4): 214—219.
  20. Кадушкин А.Г., Таганович А.Д., Шман Т.В. и др. Популяции лимфоцитов, содержащих Fas- и ССR5-рецепторы, в периферической крови пациентов с хронической обструктивной болезнью легких. Туб и бол легких 2013; 10: 35—41.
  21. Кадушкин А.Г., Таганович А.Д., Картун Л.В. и др. Уровень цитокинов в плазме крови некурящих и курящих пациентов с хронической обструктивной болезнью легких. Пульмонология 2013; 6: 27—32.

Copyright (c) 2015 Consilium Medicum

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Address of the Editorial Office:

  • Novij Zykovskij proezd, 3, 40, Moscow, 125167

Correspondence address:

  • Alabyan Street, 13/1, Moscow, 127055, Russian Federation

Managing Editor:

  • Tel.: +7 (926) 905-41-26
  • E-mail:


© 2018-2021 "Consilium Medicum" Publishing house

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies