Predictors of change in asthma-related quality of life: a longitudinal real-life study in adult asthmatics.

peer reviewed("[en] PURPOSE: Asthma negatively impacts health-related quality of life (HRQL). The objective is to investigate the longitudinal relationship between HRQL in asthma and disease control, demographic and clinical objective parameters in an adult population in real-life settings. METHODS: We conducted a longitudinal study on adult asthmatics recruited from Liege University Hospital Asthma Clinic (Belgium) between 2011 and 2019. We selected those who had two visits and completed two patient-reported outcome measures (PROMs), the asthma control test (ACT) and the mini asthma quality of life questionnaire (AQLQ) (n = 290). AQLQ was the dependent variable. Demographic, functional and inflammatory characteristics, asthma control, and exacerbations were the independent variables. We applied generalized linear mixed models to identify the factors associated with change in AQLQ and its dimensions. RESULTS: Median (IQR) time interval between the two visits was 7 (5-19) months. Overall, median (IQR) global AQLQ increased from 4.1 (3-5.1) to 4.6 (3.4-5.9) (p < 0.0001). All AQLQ dimensions significantly improved, apart the environmental one. AQLQ improved in patients who had both step-up and step-down pharmacological treatment as well as in patients reporting no change between the two visits. The fitted models indicated that change in ACT was the main predictor of change in AQLQ (p < 0.0001). A rise in 3 units in ACT predicted an improvement of 0.5 AQLQ (AUC-ROC = 0.85; p < 0.0001). Change in BMI inversely impacted global AQLQ (p < 0.01) and its activity dimension (p < 0.0001). CONCLUSION: Asthma control and BMI are key predictors of asthma quality of life acting in an opposite direction. AQLQ may improve without step-up in the pharmacological treatment.","[en] ",""

Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis

Introduction Although asthma is a common disease, its diagnosis remains a challenge in clinical practice with both over- and underdiagnosis. Here, we performed a prospective observational study investigating the value of symptom intensity scales alone or combined with spirometry and exhaled nitric oxide fraction (FENO) to aid in asthma diagnosis. Methods Over a 38-month period we recruited 303 untreated patients complaining of symptoms suggestive of asthma (wheezing, dyspnoea, cough, sputum production and chest tightness). The whole cohort was split into a training cohort (n=166) for patients recruited during odd months and a validation cohort (n=137) for patients recruited during even months. Asthma was diagnosed either by a positive reversibility test (≥12% and ≥200 mL in forced expiratory volume in 1 s (FEV1)) and/or a positive bronchial challenge test (provocative concentration of methacholine causing a 20% fall in FEV1 ≤8 mg·mL−1). In order to assess the diagnostic performance of symptoms, spirometric indices and FENO, we performed receiver operating characteristic curve analysis and multivariable logistic regression to identify the independent factors associated with asthma in the training cohort. Then, the derived predictive models were applied to the validation cohort. Results 63% of patients in the derivation cohort and 58% of patients in the validation cohort were diagnosed as being asthmatic. After logistic regression, wheezing was the only symptom to be significantly associated with asthma. Similarly, FEV1 (% pred), FEV1/forced vital capacity (%) and FENO were significantly associated with asthma. A predictive model combining these four parameters yielded an area under the curve of 0.76 (95% CI 0.66–0.84) in the training cohort and 0.73 (95% CI 0.65–0.82) when applied to the validation cohort. Conclusion Combining a wheezing intensity scale with spirometry and FENO may help in improving asthma diagnosis accuracy in clinical practice