背景與目的：慢性阻塞性肺疾病（COPD）是世界上第四大死因，是一種漸進的慢性呼吸道發炎性疾病，其特徵是「持續氣流受限」。目前COPD被認為是一種複雜且異質性高的綜合病症，其在生理特徵、臨床表現、急性惡化風險及對治療的反應各方面都存在顯著的異質性。然而，目前醫界對於COPD的表現型分類並無共識，臨床上也無有效的生物標記可供應用。血清IgE和血液嗜酸性白血球（簡稱嗜酸性球）為氣喘常用的生物標記，且檢測容易。本研究之目的在評估這兩者作為COPD生物標記的臨床應用。
研究方法：我們於高雄醫學大學附設醫院進行了一項前瞻性觀察型研究。於2016年1月1日至2017年12月31日，我們納入了208位COPD病人，追蹤至2018年3月31日，平均追蹤時間長達18.8個月，並分析了其中190位具完整資料的病人。我們依血清IgE值高低（< 100 KU/L vs. ≥ 100 KU/L）及血液嗜酸性球數高低（< 300/µL vs. ≥ 300/µL及< 4% vs. ≥ 4%）來比較COPD病人的基本臨床特徵和急性惡化頻率是否不同。
研究結果：本研究所分析的190位病人中，有56（29.5%）位病人於追蹤期間發生中度或重度的急性惡化；有55（28.9%）位病人之血液嗜酸性球數≥ 300/µL：有65（34.2%）位病人之血液嗜酸性球比率≥ 4%；有83（45.1%）位病人的血清IgE值≥ 100 KU/L。近一步分析發現血液嗜酸性球數≥ 300/µL或比率≥ 4%的COPD病人有較高的風險會發生急性惡化（OR = 2.80、95% CI = 1.44-5.44，P = 0.011；OR = 2.35、95% CI = 1.23-4.48，P = 0.093）。血清IgE值> 100 IU / mL的COPD病人則未見有較高風險會發生急性惡化（OR = 0.81、95% CI = 0.43-1.55，P = 0.533）。在多變異數分析中，支氣管擴張試驗呈陽性反應、一氧化碳瀰散能力和血液嗜酸性球比率均與病人急性惡化的風險有顯著相關，血液嗜酸性球比率每增加1%，未來急性惡化的風險會增加25%（OR = 1.25、95% CI = 1.09-1.43，P = 0.001）。
結論：血液嗜酸性球數及比率均與COPD病人急性惡化風險有顯著相關，血液嗜酸性球比率每增加1%，未來急性惡化的風險會增加25%。血清IgE則與COPD病人急性惡化風險無關。由於血液嗜酸性球檢測容易，我們建議對COPD病人常規檢測血液嗜酸性球數或比率，做為評估未來急性惡化風險之生物標誌物。

Background: Chronic obstructive pulmonary disease (COPD), the fourth leading cause of death in the world, is a chronic inflammatory disease of the airway characterized by “persistent airflow limitation that is usually progressive”. COPD is recognized as a complex and heterogeneous syndrome. Significant heterogeneity exists within COPD with respect to clinical presentation, physiology, imaging, response to therapy, decline in lung function, and survival. Currently, there are neither consensus phenotypes classification nor useful biomarkers in COPD. Serum IgE and blood eosinophil, which are easy to measure, have been used as biomarkers in asthma. This study aimed to evaluate the clinical utility of serum IgE levels and blood eosinophil counts in COPD patients.
Methods: We conducted a prospective observational study in Kaohsiung Medical University Hospital. From Jan 1, 2016 to Dec 31, 2017, we enrolled 208 patients with COPD into this study. These patients were followed till Mar 31, 2018, with a mean follow-up period of 18.8 months. Of the 208 enrolled patients, 190 with complete data were analyzed. We compared clinical features and exacerbation frequency between COPD patients with serum IgE < 100 KU/L vs. ≥ 100 KU/L, blood eosinophil counts < 300/µL vs. ≥ 300/µL and blood eosinophil < 4% vs. ≥ 4%
Results: Of the 190 COPD patients analyzed in this study, 56 (29.5%) patients had moderate or severe acute exacerbation events, 55 (28.9%) had blood eosinophil ≥ 300/µL, 65 (34.2%) had blood eosinophil ≥ 4%, and 83 (45.1%) had serum IgE ≥ 100 KU/L. COPD patients with blood eosinophil ≥ 300/µL or > 4% had significantly higher risk of acute exacerbation (OR = 2.80, 95% CI = 1.44-5.44, P = 0.011; OR = 2.35, 95% CI = 1.23-4.48, P = 0.093). Serum IgE ≥ 100 KU/L were not associated with higher risk of acute exacerbation (OR = 0.81, 95% CI = 0.43-1.55, P = 0.533). In multivariate analysis, positive bronchodilator response, diffusion capacity of the lung for carbon monoxide (DLCO) and blood eosinophil percentage were significantly associated with acute exacerbation risk. For every 1% increment in blood eosinophil, the risk of exacerbation increased by 25% (OR = 1.25, 95% CI = 1.09-1.43, P = 0.001).
Conclusion: Blood eosinophil count and percentage were significantly associated with acute exacerbation in COPD. For every 1% increment in blood eosinophil, the risk of exacerbation increased by 25%. Serum IgE levels were not associated with risk of COPD acute exacerbation. Blood eosinophil are easily available and can serve as useful biomarkers in COPD. We suggest measuring blood eosinophil counts or percentage routinely in COPD to evaluate the risk of future acute exacerbation.

論文審定書…………………………………………………………………………..……..………..……………… i
論文公開授權書…………………………………………………………………..……..………..……………… ii
誌謝………………………………………………………………………………………….……………….…………… iii
中文摘要……………………………………………………………………….….…………………………...……… iv
英文摘要………………………………………………………………..……………………………………………… vi
目錄……………………………………..………………………………………………………………………………… viii
圖次……………………………………..………………………………………………………………………………… x
表次……………………………………..………………………………………………………………………………… xi
第一章 緒論………………………………………………………………………………………………..………… 01
1.1 慢性阻塞性肺病簡介…………………………………….………………………………………… 01
1.2 慢性阻塞性肺病之流行病學……………………..…………………………….……………… 02
1.3 慢性阻塞性肺病為一異質性高之複雜性疾病………………………………………… 03
1.4 慢性阻塞性肺病之生物標記………….……………………………………………….……… 04
1.5 研究目的………………………………………………………………………………………….……… 05
第二章 研究方法……………………………………………………………………………….………….……… 06
2.1 研究設計………………………………………………………………………………………….……… 06
2.2 納入及排除條件…………………………………………………………………….……….……… 06
2.3 資料收集..……………………………………………………………………………………….……… 07
2.4 統計分析……………………………………………..………………………………………….……… 07
第三章 研究結果……………………………………………….…………………………………………………. 09
3.1研究族群基本特性………………………………………………………………….……….……… 09
3.2血液嗜酸性球數、血液嗜酸性球比率及血清IgE值………………….….……… 11
3.3生物標記預測COPD急性惡化之敏感度分析.……………………………….……… 13
3.4不同血液嗜酸性球數、血液嗜酸性球比率及血清IgE值之COPD病人
臨床特性比較….……………………………………………………………….……………...……… 15
3.5不同血液嗜酸性球數、血液嗜酸性球比率及血清IgE值之COPD病人
急性惡化風險比較….……………………………………………………….……………...……… 21
3.6 COPD病人急性惡化相關危險因子分析………………………………………….……… 24
第四章 討論與結論……………………………………………………………………………………………… 27
參考文獻……………………………………………………………………………….…………….……………….. 30

1. From the Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease (GOLD) 2018 Report. Available from: https://goldcopd.org
2. Barnes PJ: Immunology of asthma and chronic obstructive pulmonary disease. Nat Rev Immunol 2008, 8(3):183-192.
3. Cosio MG, Saetta M, Agusti A: Immunologic aspects of chronic obstructive pulmonary disease. The New England journal of medicine 2009, 360(23):2445-2454.
4. From the Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease (GOLD) 2011 Report. Available from: https://goldcopd.org
5. WHO: 10 facts on noncommunicable diseases. 2013.
6. WHO: 10 facts on ageing and health. 2017.
7. 衛生福利部: 105 年死因統計結果分析. 2016.
8. Collaborators GBDCRD: Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet Respir Med 2017, 5(9):691-706.
9. 台灣行政院經濟建設委員會人力規劃處: 2010 年至 2060 年 臺灣人口推計. 2010.
10. 衛生福利部公開資料: https://www.mohw.gov.tw/cp-3218-22790-1.html. 2013.
11. Mathers CD, Loncar D: Projections of global mortality and burden of disease from 2002 to 2030. PLoS medicine 2006, 3(11):e442.
12. Hogg JC, Chu F, Utokaparch S, Woods R, Elliott WM, Buzatu L, Cherniack RM, Rogers RM, Sciurba FC, Coxson HO et al: The nature of small-airway obstruction in chronic obstructive pulmonary disease. The New England journal of medicine 2004, 350(26):2645-2653.
13. Lopez-Campos JL, Centanni S: Current Approaches for Phenotyping as a Target for Precision Medicine in COPD Management. Copd 2018:1-10.
14. Kang J, Kim KT, Lee JH, Kim EK, Kim TH, Yoo KH, Lee JS, Kim WJ, Kim JH, Oh YM: Predicting treatable traits for long-acting bronchodilators in patients with stable COPD. International journal of chronic obstructive pulmonary disease 2017, 12:3557-3565.
15. Cazzola M, Calzetta L, Rogliani P, Matera MG: The Challenges of Precision Medicine in COPD. Mol Diagn Ther 2017, 21(4):345-355.
16. Balkissoon R: New Treatment Options for COPD: How Do We Decide Phenotypes, Endotypes or Treatable Traits? Chronic Obstr Pulm Dis 2018, 5(1):72-80.
17. de Jong PA, Mohamed Hoesein F: Precision medicine in COPD: Are we making it too difficult? Respirology 2017, 22(2):211-212.
18. Pauwels RA, Buist AS, Calverley PM, Jenkins CR, Hurd SS: Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease. NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) Workshop summary. American journal of respiratory and critical care medicine 2001, 163(5):1256-1276.
19. Rabe KF, Hurd S, Anzueto A, Barnes PJ, Buist SA, Calverley P, Fukuchi Y, Jenkins C, Rodriguez-Roisin R, van Weel C et al: Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. American journal of respiratory and critical care medicine 2007, 176(6):532-555.
20. From the Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease (GOLD) 2017 Report. Available from: https://goldcopd.org
21. Tashkin DP, Celli B, Senn S, Burkhart D, Kesten S, Menjoge S, Decramer M: A 4-year trial of tiotropium in chronic obstructive pulmonary disease. The New England journal of medicine 2008, 359(15):1543-1554.
22. Calverley PM, Anderson JA, Celli B, Ferguson GT, Jenkins C, Jones PW, Yates JC, Vestbo J: Salmeterol and fluticasone propionate and survival in chronic obstructive pulmonary disease. The New England journal of medicine 2007, 356(8):775-789.
23. Bourbeau J, Christodoulopoulos P, Maltais F, Yamauchi Y, Olivenstein R, Hamid Q: Effect of salmeterol/fluticasone propionate on airway inflammation in COPD: a randomised controlled trial. Thorax 2007, 62(11):938-943.
24. Culpitt SV, Rogers DF, Shah P, De Matos C, Russell RE, Donnelly LE, Barnes PJ: Impaired inhibition by dexamethasone of cytokine release by alveolar macrophages from patients with chronic obstructive pulmonary disease. American journal of respiratory and critical care medicine 2003, 167(1):24-31.
25. Barnes PJ, Adcock IM: Glucocorticoid resistance in inflammatory diseases. Lancet (London, England) 2009, 373(9678):1905-1917.
26. Brightling CE, McKenna S, Hargadon B, Birring S, Green R, Siva R, Berry M, Parker D, Monteiro W, Pavord ID et al: Sputum eosinophilia and the short term response to inhaled mometasone in chronic obstructive pulmonary disease. Thorax 2005, 60(3):193-198.
27. Marshall JC, Reinhart K, International Sepsis F: Biomarkers of sepsis. Crit Care Med 2009, 37(7):2290-2298.
28. Jameson JL, Longo DL: Precision medicine--personalized, problematic, and promising. The New England journal of medicine 2015, 372(23):2229-2234.
29. Agusti A, Sin DD: Biomarkers in COPD. Clin Chest Med 2014, 35(1):131-141.
30. Rosenberg SR, Kalhan R: Biomarkers in chronic obstructive pulmonary disease. Transl Res 2012, 159(4):228-237.
31. Bafadhel M, Pavord ID, Russell REK: Eosinophils in COPD: just another biomarker? Lancet Respir Med 2017, 5(9):747-759.
32. Bafadhel M, McKenna S, Terry S, Mistry V, Reid C, Haldar P, McCormick M, Haldar K, Kebadze T, Duvoix A et al: Acute exacerbations of chronic obstructive pulmonary disease: identification of biologic clusters and their biomarkers. American journal of respiratory and critical care medicine 2011, 184(6):662-671.
33. Couillard S, Larivee P, Courteau J, Vanasse A: Eosinophils in COPD Exacerbations Are Associated With Increased Readmissions. Chest 2017, 151(2):366-373.
34. Kerkhof M, Sonnappa S, Postma DS, Brusselle G, Agusti A, Anzueto A, Jones R, Papi A, Pavord I, Pizzichini E et al: Blood eosinophil count and exacerbation risk in patients with COPD. The European respiratory journal 2017, 50(1). doi: 10.1183/13993003.00761-2017