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大样本哮喘队列中痰液细胞表型分布:预测嗜酸性粒细胞与中性粒细胞炎症的相关因素。

Distribution of sputum cellular phenotype in a large asthma cohort: predicting factors for eosinophilic vs neutrophilic inflammation.

机构信息

Department of Respiratory Medicine, CHU Sart-Tilman B35, Liege 4000, Belgium.

出版信息

BMC Pulm Med. 2013 Feb 26;13:11. doi: 10.1186/1471-2466-13-11.

Abstract

BACKGROUND

Phenotyping asthma according to airway inflammation allows identification of responders to targeted therapy. Induced sputum is technically demanding. We aimed to identify predictors of sputum inflammatory phenotypes according to easily available clinical characteristics.

METHODS

This retrospective study was conducted in 508 asthmatics with successful sputum induction recruited from the University Asthma Clinic of Liege. Receiver-operating characteristic (ROC) curve and multiple logistic regression analysis were used to assess the relationship between sputum eosinophil or neutrophil count and a set of covariates. Equations predicting sputum eosinophils and neutrophils were then validated in an independent group of asthmatics.

RESULTS

Eosinophilic (≥3%) and neutrophilic (≥76%) airway inflammation were observed in 46% and 18% of patients respectively. Predictors of sputum eosinophilia ≥3% were high blood eosinophils, FENO and IgE level and low FEV1/FVC. The derived equation was validated with a Cohen's kappa coefficient of 0.59 (p < 0.0001). ROC curves showed a cut-off value of 220/mm3 (AUC = 0.79, p < 0.0001) or 3% (AUC = 0.81, p < 0.0001) for blood eosinophils to identify sputum eosinophilia ≥3%. Independent predictors of sputum neutrophilia were advanced age and high FRC but not blood neutrophil count.

CONCLUSION

Eosinophilic and paucigranulocytic asthma are the dominant inflammatory phenotypes. Blood eosinophils provide a practical alternative to predict sputum eosinophilia but sputum neutrophil count is poorly related to blood neutrophils.

摘要

背景

根据气道炎症对哮喘进行表型分析可以鉴定出靶向治疗的应答者。诱导痰技术要求较高。本研究旨在根据易于获得的临床特征,确定痰液炎症表型的预测因子。

方法

这项回顾性研究在利埃格大学哮喘诊所招募的 508 例成功诱导痰液的哮喘患者中进行。使用受试者工作特征(ROC)曲线和多变量逻辑回归分析来评估痰液嗜酸性粒细胞或中性粒细胞计数与一组协变量之间的关系。然后在一组独立的哮喘患者中验证预测痰液嗜酸性粒细胞和中性粒细胞的方程。

结果

分别有 46%和 18%的患者存在气道嗜酸性粒细胞(≥3%)和中性粒细胞(≥76%)炎症。痰液嗜酸性粒细胞≥3%的预测因子是高血嗜酸性粒细胞、FeNO 和 IgE 水平以及低 FEV1/FVC。该方程的验证得到了 Cohen's kappa 系数为 0.59(p<0.0001)。ROC 曲线显示,血嗜酸性粒细胞的截断值为 220/mm3(AUC=0.79,p<0.0001)或 3%(AUC=0.81,p<0.0001),可用于识别痰液嗜酸性粒细胞≥3%。痰液中性粒细胞增多的独立预测因子是年龄较大和 FRC 较高,但不是血中性粒细胞计数。

结论

嗜酸性粒细胞和少粒细胞性哮喘是主要的炎症表型。血嗜酸性粒细胞可作为预测痰液嗜酸性粒细胞的实用替代指标,但痰液中性粒细胞计数与血中性粒细胞计数相关性较差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbb6/3657295/7086f967f16b/1471-2466-13-11-1.jpg

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