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中华肺部疾病杂志(电子版) ›› 2021, Vol. 14 ›› Issue (01) : 24 -30. doi: 10.3877/cma.j.issn.1674-6902.2021.01.005

论著

呼出气一氧化氮和血嗜酸性粒细胞对哮喘患者气道高反应性程度的预测价值
李江华1, 李力1, 王玉波1, 陈恒屹1, 何勇1,()   
  1. 1. 400032 重庆,陆军(第三)军医大学第三附属医院呼吸与危重症医学科
  • 收稿日期:2020-10-05 出版日期:2021-02-25
  • 通信作者: 何勇
  • 基金资助:
    陆军医科大学临床医学科研人才培养计划(2019XLC2019)

Predictive value of exhaled nitric oxide and blood eosinophils on the degree of airway hyperresponsiveness in asthma patients

Jianghua Li1, Li Li1, Yubo Wang1, Hengyi Chen1, Yong He1,()   

  1. 1. Department of Respiratory and Critical Care Medicine, The Third Affiliated Hospital of Army Military Medical University, Chongqing 400032, China
  • Received:2020-10-05 Published:2021-02-25
  • Corresponding author: Yong He
引用本文:

李江华, 李力, 王玉波, 陈恒屹, 何勇. 呼出气一氧化氮和血嗜酸性粒细胞对哮喘患者气道高反应性程度的预测价值[J]. 中华肺部疾病杂志(电子版), 2021, 14(01): 24-30.

Jianghua Li, Li Li, Yubo Wang, Hengyi Chen, Yong He. Predictive value of exhaled nitric oxide and blood eosinophils on the degree of airway hyperresponsiveness in asthma patients[J]. Chinese Journal of Lung Diseases(Electronic Edition), 2021, 14(01): 24-30.

目的

分析呼出气一氧化氮(fraction of exhaled nitric oxide, FeNO)水平和血嗜酸性粒细胞(blood eosinophil, B-Eos)计数对哮喘患者气道高反应性(airway hyperresponsiveness, AHR)程度的预测价值,并探索AHR严重程度的预测模型。

方法

选择2014年1月至2019年12月于我院首诊为哮喘的患者1 347例,将其中520例具有FeNO和B-Eos的纳入主要研究人群。依据乙酰甲胆碱激发试验(methacholine challenge test, MCT)结果,分为重度AHR组(MCT为中度或重度阳性183例和轻度AHR组(MCT为极轻度或轻度阳性337例。然后分析两组差异,用Logistic回归构建预测模型,最后绘制重度AHR风险的列线图和森林图。

结果

重度AHR组的FeNO和B-Eos均高于轻度AHR组(73 vs. 36 ppb、394 vs. 243个/μl,P<0.001)。Logistic回归示年龄、性别、FEV1/FVC、B-Eos、FeNO为重度AHR的独立危险因素,将它们纳入回归模型,其灵敏度为49.7%,特异度为87.8%。受试者工作特征曲线示模型的曲线下面积明显高于单独的FeNO或B-Eos(0.797 vs. 0.715或0.644,P<0.001)。重度AHR风险的亚组分析示:随着FeNO或B-Eos的增高风险逐步增高(趋势检验P<0.001);女性的风险为男性的1.57倍(P=0.041),而低FEV1/FVC组(<70%)为正常组的3.38倍(P<0.001)。

结论

在哮喘患者中单独的FeNO或B-Eos对重度AHR具有中等程度的预测效能,通过多因素回归模型构建的列线图可以用于预测重度AHR的概率。

Objective

To analyze the predictive value of the fractional of exhaled nitric oxide (FeNO) and blood eosinophil (B-Eos) counts on the severity of airway hyperresponsiveness in asthma patients, then explore a prediction model for the severity of AHR.

Methods

This study retrospectively collected 1347 patients diagnosed with asthma in our hospital from January 2014 to December 2019, and identified a cohort of 520 patients who had simultaneous completed datasets of FeNO and B-Eos. According to the methacholine challenge test (MCT) results, the population was divided into severe AHR group (MCT is moderate or severely positive, n=183) and mild AHR group (MCT is very mild or slightly positive, n=337). The differences in demographics, lung function, FeNO and B-Eos are analyzed between these two groups. Logistic regression is used to construct a multi-factor regression model, then the risk of severe AHR is displayed by nomogram and forest chart.

Results

FeNO and B-Eos in the severe AHR group were significantly higher than those in the mild AHR group (73 vs. 36 ppb, 394 vs. 243 cells/μl, P<0.001). Logistic regression showed that age, gender, FEV1/FVC ratio, B-Eos, and FeNO were independent risk factors for severe AHR. The model incorporating these risk factors has a sensitivity of 49.7% and a specificity of 87.8%. The receiver operating characteristic (ROC) curve analysis shows that the AUC of the regression model is significantly higher than that of FeNO or B-Eos alone (0.797 vs. 0.715 or 0.644, P<0.001). When comparing the risk of having severe AHR in different subgroups, the adjusted odds ratio (aOR) of having severe AHR elevated progressively with the gradual increase in FeNO or B-Eos (P<0.001). While, the multivariable aOR of having severe AHR was 1.57 for females (P=0.041), 3.38 for patients with lower FEV1/FVC ratio (<70%, P<0.001).

Conclusion

FeNO or B-Eos alone has moderate diagnostic accuracy for predicting severe AHR. The nomogram constructed by the multi-factor regression model can be used to predict the probability of severe AHR.

图1 MCT等级分组后FeNO及B-Eos分布的散点图;注:(A)MCT等级分组后FeNO分布的散点图;(B)MCT等级分组后B-Eos分布的散点图;备注:各指标的组间散点分布以不同颜色区分,短线标注为每组的中位数和四分位数范围;组间统计学差异采用Kruskal-Wallis H检验比较
表1 研究人群人口学资料及基线特征
临床资料 气道高反应性程度 P 数据是否齐全d P
轻度(MCT+或+/-)(n=337) 重度(MCT++或+++)(n=183) 数据齐全组(n=520) 数据不齐组(n=827)
年龄(岁) 45(32~52) 41(32~49) 0.040a 43.5(32~51) 44(31.75~52) 0.591a
身高(cm) 158(153~165) 160(153~165) 0.483a 159(153~165) 159(153~166) 0.218a
体重(kg) 58(52~66) 57(52~65) 0.346a 58(52~66) 58(52~66) 0.722a
体重指数(kg/m2) 23.37(21.09~25.59) 22.86(21.19~25) 0.156a 23.21(21.12~25.47) 22.95(20.58~25.49) 0.428a
白细胞(×109/L) 6.87(5.86~8.53) 7.23(6.1~8.85) 0.212a 7.06(5.9~8.7) 7.58(6.25~8.67)(n=84) 0.065a
中性粒细胞(%) 59.38±9.80 57.10±10.05 0.012b 58.58±9.94 60.01±9.05(n=84) 0.214b
嗜酸性粒细胞计数(/μl) 243(111.5~462.5) 394(216~617) <0.001a 289.5(134.25~500) 249(150~481.25)(n=84) 0.824a
嗜酸性粒细胞(%) 3.5(1.6~6.3) 5.6(3.3~8.6) <0.001a 4.2(2~7.38) 4.05(1.9~5.88)(n=84) 0.382a
FeNO (ppb) 36(20~67) 73(40~132) <0.001a 50(24~87) 48.5(24~88)(n=576) 0.975a
用力肺活量(占预计值%) 99.4(90.6~108.4) 98.9(93.5~109.5) 0.394a 99.2(91.75~108.78) 97.95(90.78~106.9) 0.049a
FEV1(占预计值%) 89.7(81.4~99.9) 84(76.4~92.7) <0.001a 87.65(79.7~97.1) 86.9(80.4~95.3) 0.547a
FEV1/FVC (%) 77(69.53~82.04) 69.98(66.33~76.8) <0.001a 74.88(68.25~80.08) 75.5(69.03~80.9) 0.169a
性别     0.552c     0.206c
  111(32.9) 65(35.5)   176(33.8) 308(37.2)  
  226(67.1) 118(64.5)   344(66.2) 519(62.8)  
图2 预测AHR程度的ROC曲线;注:(A)所有患者中FeNO、B-Eos及回归模型的ROC曲线比较;(B)女性患者中FeNO、B-Eos及回归模型的ROC曲线比较。b:采用Hanley&McNeil非参数方法
表2 FeNO及B-Eos不同界值预测重度AHR的准确性
图3 预测重度AHR模型的列线图;注:Logistic回归模型的列线图
表3 多因素Logistic回归模型的统计量
图4 不同分组重度AHR占比及乙酰甲胆碱PD20-FEV1剂量分布;注:(A)FeNO及B-Eos高低分组后AHR程度的直方图;(B)FeNO及B-Eos高低分组后乙酰甲胆碱PD20-FEV1的散点图;备注:以FeNO、B-Eos预测重度AHR的最佳截止值(52 ppb或170个/微升)区分各自高或低
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