Blog
About

7
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Peripheral blood eosinophils: a surrogate marker for airway eosinophilia in stable COPD

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Introduction

          Sputum eosinophilia occurs in approximately one-third of stable chronic obstructive pulmonary disease (COPD) patients and can predict exacerbation risk and response to corticosteroid treatments. Sputum induction, however, requires expertise, may not always be successful, and does not provide point-of-care results. Easily applicable diagnostic markers that can predict sputum eosinophilia in stable COPD patients have the potential to progress COPD management. This study investigated the correlation and predictive relationship between peripheral blood and sputum eosinophils. It also examined the repeatability of blood eosinophil counts.

          Methods

          Stable COPD patients (n=141) were classified as eosinophilic or noneosinophilic based on their sputum cell counts (≥3%), and a cross-sectional analysis was conducted comparing their demographics, clinical characteristics, and blood cell counts. Receiver operating characteristic curve analysis was used to assess the predictive ability of blood eosinophils for sputum eosinophilia. Intraclass correlation coefficient was used to examine the repeatability of blood eosinophil counts.

          Results

          Blood eosinophil counts were significantly higher in patients with sputum eosinophilia (n=45) compared to those without (0.3×10 9/L vs 0.15×10 9/L; P<0.0001). Blood eosinophils correlated with both the percentage (ρ=0.535; P<0.0001) and number of sputum eosinophils (ρ=0.473; P<0.0001). Absolute blood eosinophil count was predictive of sputum eosinophilia (area under the curve =0.76, 95% confidence interval [CI] =0.67–0.84; P<0.0001). At a threshold of ≥0.3×10 9/L (specificity =76%, sensitivity =60%, and positive likelihood ratio =2.5), peripheral blood eosinophil counts enabled identification of the presence or absence of sputum eosinophilia in 71% of the cases. A threshold of ≥0.4×10 9/L had similar classifying ability but better specificity (91.7%) and higher positive likelihood ratio (3.7). In contrast, ≥0.2×10 9/L offered a better sensitivity (91.1%) for ruling out sputum eosinophilia. There was a good agreement between two measurements of blood eosinophil count over a median of 28 days (intraclass correlation coefficient =0.8; 95% CI =0.66–0.88; P<0.0001).

          Conclusion

          Peripheral blood eosinophil counts can help identify the presence or absence of sputum eosinophilia in stable COPD patients with a reasonable degree of accuracy.

          Related collections

          Most cited references 28

          • Record: found
          • Abstract: not found
          • Article: not found

          Non-eosinophilic corticosteroid unresponsive asthma.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Severe exacerbations and BODE index: two independent risk factors for death in male COPD patients.

            1) To determine whether severe exacerbation of COPD is a BODE index independent risk factor for death; 2) whether the combined application of exacerbations and BODE (e-BODE index), offers greater predictive capacity than BODE alone or can simplify the model, by replacing the exercise capacity (BODEx index). A prospective study was made of a cohort of COPD patients. In addition to calculation of the BODE index we register frequency of exacerbations. An analysis was made of all-cause mortality, evaluating the predictive capacity of the exacerbations after adjusting for the BODE. These variables were also used to construct two new indexes: e-BODE and BODEx. The study included 185 patients with a mean age of 71+/-9 years, and FEV(1)% 47+/-17%. Severe exacerbation appeared as an independent adverse prognostic variable of BODE index. For each new exacerbation the adjusted mortality risk increased 1.14-fold (95% CI: 1.04-1.25). However, the e-BODE index (C statistic: 0.77, 95% CI: 0.67-0.86) didn't improve prognostic capacity of BODE index (C statistic: 0.75, 95% CI: 0.66-0.84) (p=NS). An interesting finding was that BODEx index (C statistic: 0.74, 95% CI: 0.65-0.83) had similar prognostic capacity than BODE index. Severe exacerbations of COPD imply an increased mortality risk that is independent of baseline severity of the disease as measured by the BODE index. The combined application of both parameters (e-BODE index) didn't improve the predictive capacity, but on replacing exacerbation with exercise capacity the multidimensional grading system is simplified without loss of predictive capacity.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Current concepts in targeting chronic obstructive pulmonary disease pharmacotherapy: making progress towards personalised management.

              Chronic obstructive pulmonary disease (COPD) is a common, complex, and heterogeneous disorder that is responsible for substantial and growing morbidity, mortality, and health-care expense worldwide. Of imperative importance to decipher the complexity of COPD is to identify groups of patients with similar clinical characteristics, prognosis, or therapeutic needs, the so-called clinical phenotypes. This strategy is logical for research but might be of little clinical value because clinical phenotypes can overlap in the same patient and the same clinical phenotype could result from different biological mechanisms. With the goal to match assessment with treatment choices, the latest iteration of guidelines from the Global Initiative for Chronic Obstructive Lung Disease reorganised treatment objectives into two categories: to improve symptoms (ie, dyspnoea and health status) and to decrease future risk (as predicted by forced expiratory volume in 1 s level and exacerbations history). This change thus moves treatment closer to individualised medicine with available bronchodilators and anti-inflammatory drugs. Yet, future treatment options are likely to include targeting endotypes that represent subtypes of patients defined by a distinct pathophysiological mechanism. Specific biomarkers of these endotypes would be particularly useful in clinical practice, especially in patients in which clinical phenotype alone is insufficient to identify the underlying endotype. A few series of potential COPD endotypes and biomarkers have been suggested. Empirical knowledge will be gained from proof-of-concept trials in COPD with emerging drugs that target specific inflammatory pathways. In every instance, specific endotype and biomarker efforts will probably be needed for the success of these trials, because the pathways are likely to be operative in only a subset of patients. Network analysis of human diseases offers the possibility to improve understanding of disease pathobiological complexity and to help with the development of new treatment alternatives and, importantly, a reclassification of complex diseases. All these developments should pave the way towards personalised treatment of patients with COPD in the clinic.
                Bookmark

                Author and article information

                Journal
                Int J Chron Obstruct Pulmon Dis
                Int J Chron Obstruct Pulmon Dis
                International Journal of COPD
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove Medical Press
                1176-9106
                1178-2005
                2016
                01 July 2016
                : 11
                : 1495-1504
                Affiliations
                [1 ]Priority Research Centre for Healthy Lungs, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW, Australia
                [2 ]Hunter Medical Research Institute, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW, Australia
                [3 ]Department of Respiratory and Sleep Medicine, John Hunter Hospital, Newcastle, NSW, Australia
                [4 ]School of Nursing and Midwifery, Faculty of Health and Medicine, The University of Newcastle, Callaghan, NSW, Australia
                [5 ]Institute for Infection and Immunity, St George’s, University of London, London, UK
                Author notes
                Correspondence: Netsanet A Negewo, Hunter Medical Research Institute, Level 2 West Wing, Locked Bag 1000, New Lambton, NSW 2305, Australia, Tel +61 2 4042 0762, Fax +61 2 4042 0046, Email netsanet.negewo@ 123456uon.edu.au
                Article
                copd-11-1495
                10.2147/COPD.S100338
                4936821
                27445469
                © 2016 Negewo et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Comments

                Comment on this article