Current Respiratory Care Reports

, Volume 3, Issue 3, pp 133–139

Personalized medicine in COPD treatment

COPD (C Bai and Y Song, Section Editors)

Abstract

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease, and not all patients respond to all currently available drugs. The importance of personalized treatment of COPD is increasingly recognized. The new GOLD guidelines have moved the principles of treatment of stable COPD forward by including concepts of symptoms and risks into the decision for therapy. COPD phenotypes are the basis of personalized treatment in clinical practice. Consensus has been reached concerning several phenotypes: phenotypes according to the evaluation of image; the frequent exacerbator and infrequent exacerbator; asthma and COPD overlap syndrome; and the persistent systemic inflammation phenotype. These phenotypes can help clinicians identify patients that respond to specific pharmacological interventions. Comorbidities and other factors, such as social and economic status, must also be considered. Future research needs to validate potential phenotypes in longitudinal studies, and examine the responses of different phenotypes to existing and future therapies.

Keywords

Chronic obstructive pulmonary disease Personalized medicine Phenotype Guideline 

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. 1.•
    Global Initiative for Chronic Obstructive Lung Disease (GOLD). Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: revised 2014. Available from: http://www.goldcopd.org. GOLD is the most important document of COPD, and the new version of GOLD is a tentative move towards personalized treatment for patients with COPD.
  2. 2.•
    Han MK et al. Chronic obstructive pulmonary disease phenotypes: the future of COPD. Am J Respir Crit Care Med. 2010;182:598–604. This clinical commentary gave a clear definition of COPD phenotype, and proposed that COPD phenotypes should be associated with clinically meaningful outcomes. This more focused definition allows for classification of patients into distinct prognostic and therapeutic subgroups for both clinical and research purposes.PubMedCrossRefGoogle Scholar
  3. 3.
    Burrows B et al. The emphysematours and bronchial types of chronic airways obstruction. Lancet. 1966;1:830.PubMedCrossRefGoogle Scholar
  4. 4.
    Weiss ST, Speizer FE. Increased levels of airways responsiveness as a risk factor for development of chronic obstructive lung disease: what are the issues? Chest. 1984;86:3.PubMedCrossRefGoogle Scholar
  5. 5.
    Kim V et al. COPDGene Investigators. The chronic bronchitic phenotype of COPD: an analysis of the COPD gene study. Chest. 2011;140:626–33.PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Vestbo J et al. ECLIPSE investigators. Evaluation of COPD longitudinally to identify predictive surrogate end-points (ECLIPSE). Eur Respir J. 2008;31:869–73.PubMedCrossRefGoogle Scholar
  7. 7.
    Agustí A et al. For the evaluation of COPD longitudinally to identify predictive surrogate endpoints (ECLIPSE) investigators. Characterization of COPD heterogeneity in the ECLIPSE cohort. Respir Res. 2010;11:122.PubMedCentralPubMedGoogle Scholar
  8. 8.
    Couper D, SPIROMICS Research Group, et al. Design of the subpopulations and intermediate outcomes in COPD study (SPIROMICS). Thorax. 2014;69:492–5.CrossRefGoogle Scholar
  9. 9.
    Rennard SI et al. Reduction of exacerbations by the PDE4 inhibitor roflumilast – the importance of defining different subsets of patients with COPD. Respir Res. 2011;12:18.PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.•
    Hurst JR et al. Susceptibility to exacerbation in chronic obstructive pulmonary disease. N Engl J Med. 2010;363:1128–38. This analysis was based on data collected as part of the ECLIPSE observational study and analyzed the frequency and associations of exacerbation in 2,138 patients. This finding supports the hypothesis that patients who are more subject to frequent exacerbations have a distinct susceptibility phenotype.PubMedCrossRefGoogle Scholar
  11. 11.
    Soler-Cataluna JJ, Rodriguez-Roisin R. Frequent chronic obstructive pulmonary disease exacerbators: how much real, how much fictitious? COPD. 2010;7:276–84.PubMedCrossRefGoogle Scholar
  12. 12.
    Uzun S, et al. Azithromycin maintenance treatment in patients with frequent exacerbations of chronic obstructive pulmonary disease (COLUMBUS): a randomised, double-blind, placebo-controlled trial.Lancet Respir Med. 2014 Apr 15. [Epub ahead of print].Google Scholar
  13. 13.
    Donath E et al. A meta-analysis on the prophylactic use of macrolide antibiotics for the prevention of disease exacerbations in patients with chronic obstructive pulmonary disease. Respir Med. 2013;107:1385–92.PubMedCrossRefGoogle Scholar
  14. 14.
    Sethi S, PULSE Study group, et al. Pulsed moxifloxacin for the prevention of exacerbations of chronic obstructive pulmonary disease: a randomized controlled trial. Respir Res. 2010;11:10.PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Agustí A et al. Evaluation of COPD longitudinally to identify predictive surrogate endpoints (ECLIPSE) investigators. Persistent systemic inflammation is associated with poor clinical outcomes in COPD: a novel phenotype. PLoS One. 2012;7:e37483.PubMedCentralPubMedCrossRefGoogle Scholar
  16. 16.
    Lomas DA et al. On behalf of the evaluation of COPD longitudinally to identify predictive surrogate endpoints study investigators. Serum surfactant protein D is steroid sensitive and associated with exacerbations of COPD. Eur Respir J. 2009;34:95–102.PubMedCrossRefGoogle Scholar
  17. 17.
    Lomas DA et al. On behalf of the evaluation of COPD longitudinally to identify predictive surrogate endpoints (ECLIPSE) investigators. Evaluation of serum CC-16 as a biomarker for COPD in theECLIPSE cohort. Thorax. 2008;63:1058–63.PubMedCrossRefGoogle Scholar
  18. 18.
    Thomsen M et al. Inflammatory biomarkers and comorbidities in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2012;186:982–8.PubMedCrossRefGoogle Scholar
  19. 19.
    Thomsen M et al. Inflammatory biomarkers and exacerbations of chronic obstructive pulmonary disease. JAMA. 2013;309:2353–61.PubMedCrossRefGoogle Scholar
  20. 20.
    Calverley PMA et al. On behalf of the TORCH investigators. Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease. N Engl J Med. 2007;356:775–89.PubMedCrossRefGoogle Scholar
  21. 21.
    Tashkin DP, and UPLIFT study investigators, et al. A 4-year trial of tiotropium in chronic obstructive pulmonary disease. N Engl J Med. 2008;359:1543–54.PubMedCrossRefGoogle Scholar
  22. 22.
    Goldstein S. Benefits of β-blocker therapy for heart failure: weighing the evidence. Arch Intern Med. 2002;162:641–8.PubMedCrossRefGoogle Scholar
  23. 23.
    Rutten FH et al. β-Blockers may reduce mortality and risk of exacerbations in patients with chronic obstructive pulmonary disease. Arch Intern Med. 2010;170:880–7.PubMedCrossRefGoogle Scholar
  24. 24.
    Short PM et al. Effect of beta blockers in treatment of chronic obstructive pulmonary disease: a retrospective cohort study. BMJ. 2011;342:d2549.PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Guo Y et al. Effects of one month treatment with propranolol and metoprolol on the relaxant and contractile function of isolated trachea from rats exposed to cigarette smoke for four months. Inhal Toxicol. 2014;26:271–7.PubMedCrossRefGoogle Scholar
  26. 26.
    Janda S et al. Statins in COPD: a systematic review. Chest. 2009;136:734–43.PubMedCrossRefGoogle Scholar
  27. 27.
    Wang MT et al. Statin use and risk of COPD exacerbation requiring hospitalization. Am J Med. 2013;126:598–606.PubMedCrossRefGoogle Scholar
  28. 28.
    Van de Bool C, Steiner MC, Schols AM. Nutritional targets to enhance exercise performance in chronic obstructive pulmonary disease. Curr Opin Clin Nutr Metab Care. 2012;15:553–60.PubMedCrossRefGoogle Scholar
  29. 29.
    van den Borst B, Health, Aging, and Body Composition (Health ABC) Study, et al. The influence of abdominal visceral fat on inflammatory pathways and mortality risk in obstructive lung disease. Am J Clin Nutr. 2012;96:516–26.PubMedCentralPubMedCrossRefGoogle Scholar
  30. 30.
    Miravitlles M et al. Spanish COPD guidelines (GesEPOC). Pharmacological treatment of stable COPD. Arch Bronconeumol. 2012;48:247–57.PubMedGoogle Scholar
  31. 31.
    Zhong NS et al. Prevalence of chronic obstructive pulmonary disease in China. Am J Respir Crit Care Med. 2007;176:753–60.PubMedCrossRefGoogle Scholar
  32. 32.
    National Health and Family Planning Commission. China Health Statistical Yearbook, 2011. http://www.moh.gov.cn/htmlfiles/zwgkzt/ptjnj/year2011/index2011.html (accessed Feb 1, 2014).
  33. 33.
    Shen N, Yao WZ, Zhu H. Patient’s perspective of chronic obstructive pulmonary disease in Yanqing county of Beijing. Zhonghua Jie He He Hu Xi Za Zhi. 2008;31:206–8.PubMedGoogle Scholar
  34. 34.
    Shen N, He B. Is the new GOLD classification applicable in China? Lancet Global Health. 2013;1:e247–8.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Respiratory MedicinePeking University Third HospitalBeijingChina

Personalised recommendations