稳定期COPD患者呼出气一氧化氮与外周血嗜酸性粒细胞水平的相关性分析

张彩云; 韩志海; 孟激光; 赖莉芬; 刘方; 李泳群

doi:10.3969/j.issn.2095-5227.2022.04.002

稳定期COPD患者呼出气一氧化氮与外周血嗜酸性粒细胞水平的相关性分析

Correlation analysis of fractional exhaled nitric oxide and peripheral blood eosinophil count in patients with stable chronic obstructive pulmonary disease

摘要

摘要:
背景血嗜酸性粒细胞(eosinophils，EOS)计数已成为慢性阻塞性肺疾病(chronic obstructive pulmonary disease，COPD)患者应用吸入糖皮质激素(inhaled corticosteroids，ICS)治疗的指征，但呼出气一氧化氮(fractional exhaled nitric oxide，FeNO)在稳定期COPD患者诊断治疗中的应用价值仍不清楚。
目的观察不同特征的稳定期COPD患者外周血EOS与FeNO的相关性，探讨FeNO在稳定期COPD患者中的应用价值及局限性。
方法回顾性纳入2017年3月- 2020年3月在我中心接受FeNO和外周血嗜酸性粒细胞计数检测的稳定期COPD患者和哮喘患者，分别对两组患者FeNO与血EOS计数的相关性进行统计分析。对FeNO值升高的危险因素进行二元logistic回归分析。根据气道阻塞程度(FEV1pred%)、过度充气程度(RVpred%：150%及RVpred%：200%)进一步将COPD患者分为FEV1pred%＞50%组及FEV1pred%≤50%组、RVpred%＞150组及RVpred%≤150组、RVpred%＞200组及RVpred%≤200组分别进行FeNO和血嗜酸性粒细胞相关性分析。分别对哮喘组及COPD组血嗜酸性粒细胞预测FeNO值升高的鉴别效能进行ROC分析。
结果共纳入COPD患者113例，其中男性90例，女性23例，平均年龄(69.04±9.59)岁；支气管哮喘患者43例，其中男性31例，女性12例，平均年龄(68.37±9.45)岁。哮喘组FeNO与血EOS计数呈中度相关(r=0.439，P＜0.001)；而COPD组FeNO水平与血EOS无相关性(r=0.104，P=0.272)。二元logistic回归分析发现吸烟史为COPD组FeNO升高的危险因素，RVpred%为FeNO升高的保护性因素。对COPD患者进行亚组分析，发现FEV1pred%≤50%组外周血EOS与FeNO呈正相关(r=0.370，P=0.020)。其余亚组血EOS与FeNO均无相关性(P＞0.05)。ROC分析发现COPD组中血嗜酸性粒细胞对FeNO值几乎无鉴别效能；FEV1pred%＜50% COPD组血嗜酸性粒细胞对FeNO值有一定的鉴别效能，AUC为0.688(95% CI：0.444 ~ 0.931)，敏感度为0.56，特异性为0.90。哮喘组血嗜酸性粒细胞对FeNO值有较好的鉴别效能，AUC为0.869(95% CI：0.721 ~ 1.018)，敏感度为0.83，特异性为0.90。
结论稳定期COPD患者FeNO与血EOS的相关性与哮喘患者不同，其FeNO水平与血EOS无相关性，但FEV1pred%≤50%的患者FeNO与血EOS存在一定的正相关。稳定期COPD患者FeNO不能代替血EOS用于评估ICS使用，FEV1pred%＜50% COPD组FeNO值在一定程度上可代替血EOS用于评估是否使用ICS治疗，而哮喘患者FeNO值可代替血EOS用于评估气道嗜酸性炎症。

Abstract:
Background Blood eosinophil count has become an indication for the application of inhaled corticosteroids in patients with chronic obstructive pulmonary disease (COPD), but the value of fractional exhaled nitric oxide (FeNO) in the diagnosis and treatment of patients with stable COPD is still unclear.
Objective To observe the correlation between blood eosinophil count and FeNO in patients with stable COPD with different characteristics, and explore the value and limitations of FeNO in stable COPD.
Methods Patients with stable COPD or asthma who had FeNO and peripheral blood eosinophil count results in our hospital from March 2017 to March 2020 were retrospectively included. The correlation between FeNO and blood eosinophil count was analyzed for both groups. A binary logistic regression analysis was performed to identify risk factors for an elevation in FeNO. According to the degree of airway obstruction (FEV1pred%) and the degree of hyperinflation (RVpred%), the patients with COPD were divided into FEV1pred%≤50% and FEV1pred%>50% subgroups, RVpred%>150 and RVpred%≤150 subgroups, and RVpred%>200 and RVpred%≤200 subgroups to perform the correlation analysis of peripheral blood eosinophil count and FeNO. A receiver operating characteristic (ROC) curve analysis was conducted to determine the efficacy of blood eosinophil count in predicting an elevated FeNO level in the asthma and COPD groups.
Results A total of 113 patients with COPD (90 males and 23 females with a mean age of 69.04±9.59 years) and 43 patients with asthma (31 males and 12 females with a mean age of 68.37±9.45 years) were included. FeNO was moderately correlated with blood eosinophil count in the asthma group (r=0.439, P<0.001), but without significant correlation in the COPD group (r=0.104, P=0.272). The binary logistic regression analysis found that smoking history was a risk factor and RVpred% was a protective factor for an elevated FeNO level in the COPD group. Further subgroup analysis of the patients with COPD showed that blood eosinophil count was positively correlated with FeNO in the FEV1pred%≤50% subgroup (r=0.370, P=0.020), but without significant correlation in the other subgroups (P >0.05). The ROC analysis found that blood eosinophil count had almost no differential value for FeNO in the COPD group, but with certain differential efficacy in the FEV1pred%<50% subgroup (the area under the curve AUC=0.688, 95% CI: 0.444-0.931, sensitivity=0.56, and specificity=0.90). Blood eosinophil count showed good differential efficacy for FeNO in the asthma group (AUC=0.869, 95% CI: 0.721-1.018, sensitivity=0.83, and specificity=0.90).
Conclusion There is no correlation between FeNO and blood eosinophil count in patients with stable COPD, which is different from that of patients with asthma, but the two indicators are positively correlated in patients with stable COPD with FEV1pred%≤50%. FeNO can not replace blood eosinophil count to determine whether to use inhaled corticosteroids in patients with stable COPD, but it can be an alternative choice to a certain extent in the FEV1pred%≤50% subgroup. However, FeNO can replace blood eosinophil count to evaluate eosinophilic airway inflammation in patients with asthma.

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