The Application Value Of FeNO And Blood Eosinophils In Suspected Asthma And The Degree Of Airway Hyperresponsiveness

Part I:The distribution of FeNO and blood eosinophils in patients with suspected asthma and their predictive value for variable expiratory flow limitationBackground:Asthma is characterized by recurrent respiratory symptoms and a variable expiratory-airflow limitation,affecting approximately 334 million people worldwide.Meanwhile,many asthma patients are still underdiagnosed,which leads to a decrease in work productivity and poor vitality and mental health.The main reason is that the common symptoms of asthma are relatively non-specific,and the objective tests recommended by the Global Initiative for Asthma(GINA),including the bronchial-provocation test(BPT)and the bronchodilation test(BDT),require full cooperation from patients,over long durations of examination time,and might pose risk of airway spasm.Therefore,finding a simple and effective method for diagnosing asthma is an urgent clinical need.In most cases,asthma is an inflammatory disease driven by T-helper 2(Th2)cells,even moderate to severe persistent corticosteroid-refractory(defined as Th2-low)asthma has Th2-high features.Fractional exhaled nitric oxide(FeNO)and the blood eosinophil(B-Eos)count have been suggested as biomarkers of Th2 inflammation.As promising and easy-to-measure biomarkers,FeNO and B-Eos count are attractive to help diagnose asthma,even though their exact characteristics and roles in the diagnosis of asthma are still controversial.Objectives:We aimed to evaluate whether the combination of FeNO and B-Eos can be used to distinguish certain asthma patients for whom the objective tests could be avoided.Methods:We screened 7,463 suspected asthma cases between January 2014 and December 2019 in Chongqing,China,and identified a cohort of 2,349 patients with complete FeNO,B-Eos count,and spirometry data.Among them,807 cases were diagnosed with asthma by clinicians by the criteria of recurrent respiratory symptoms and a positive bronchial-provocation or bronchodilation test.Based on the recommended diagnostic cutoff value of the two biomarkers,which was obtained by receiver operating characteristic(ROC)curve analysis and in-series test,the cohort was divided into four groups: group A(high FeNO and high B-Eos count,n = 395),group B(high FeNO and low B-Eos count,n = 354),group C(low FeNO and high B-Eos count,n = 273),group D(low FeNO and low B-Eos count,n = 1327).The risks of having asthma and reduced lung function were compared between different groups.The conclusions were verified in the incomplete data group.Results:The ROC curve showed that the optimal cutoff values to predict the objective test results of asthma were 38 ppb for FeNO and 203 cells/μl for B-Eos.The area under the ROC curve(AUC)showed no difference between FeNO and B-Eos count(0.745 vs.0.728,P = 0.212),and the AUC increased slightly when two biomarkers were used in combination by logistic regression(0.768 vs 0.745 or 0.728,both P < 0.001).The odds ratio of a positive objective test increased progressively with a gradual increase in FeNO or B-Eos count(both P < 0.001).Further analysis of the in-series combinations of different threshold values for the two biomarkers indicated that moderately elevated biomarker levels(FeNO > 40 ppb and B-Eos > 300 cells/μl)support that the objective test for asthma is positive because the positive likelihood ratio(PLR)was > 10.This conclusion was verified when selecting the2017–2019 data as the internal validation dataset.Conclusion:Detecting FeNO or B-Eos count alone is not enough to accurately predict the objective test results.When the biomarkers of suspected asthmatic subjects are moderately elevated(FeNO> 40 ppb and B-Eos> 300/μl),it could predict that the objective test for asthma is positive,thereby enabling these patients to avoid complicated asthma diagnostic tests,especially such tests are not feasible.Part II: Predictive value of exhaled nitric oxide and blood eosinophil count for the degree of airway hyperresponsiveness in asthmatic patients Background: Asthma is a chronic airway inflammatory disease,usually associated with variable expiratory airflow limitation and airway hyperresponsiveness(AHR).It is characterized by the history of respiratory symptoms such as cough,chest tightness,shortness of breath and wheeze that vary over time and in intensity.In order to avoid underdiagnosis,overdiagnosis,or misdiagnosis,objective tests are demonded to support the diagnosis of asthma.Methacholine challenge test(MCT)is a commonly used method for the diagnosis of asthma with high sensitivity and good effectiveness.Poor control of asthma is usually accompanied by a higher level of AHR,which will decrease when the condition improves.However,it is difficult to determine the degree of AHR.However,MCT is time-consuming,has a risk of triggering asthma attack,and is usually not available in primary care.Therefore,a simple and effective method is needed to determine the degree of AHR,monitor the changes of the disease and guide the adjustment of treatment.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 were analyzed between these two groups.Logistic regression model was used to construct a multi-factor regression model,then the risk of severe AHR was displayed by nomogram and forest chart.Results:FeNO and B-Eos in the severe AHR group were obviously 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 ROC curve analysis indicates 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(a OR)of having severe AHR elevated progressively with the gradual increase in FeNO or B-Eos(P<0.001).Meanwhile,the multivariable a OR 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.