Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
Pulmonary and Respiratory Medicine; Asthma; PROMs; Symptoms intensity scales; Diagnosis
Abstract :
INTRODUCTIONAlthough asthma is a common disease, its diagnosis remains a challenge in clinical practice with both over/under-diagnosis. Here, we performed a prospective observational study investigating the value of symptom intensity scales alone or combined with spirometry and FeNO to aid in asthma diagnosis.METHODSWe recruited, over a 38-month period, 303 untreated patients complaining with symptoms suggestive of asthma (cough, chest tightness, dyspnea, airway secretion and wheezing). The whole cohort was split in a training cohort (n=166) for patients recruited in odd months and a validation cohort (n=137) for the patients recruited in even months. Asthma was diagnosed either by a positive reversibility test (≥12% and 200 ml) and/or a positive bronchial challenge test (PC20M≤8 mg·ml−1). In order to assess the diagnostic performance of symptoms, spirometric indices and FeNO, we performed ROC 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.RESULTS63% of patients in the derivation cohort and 58% in the validation cohort were diagnosed as being asthmatics. After logistic regression wheezing was the only symptom to be significantly associated with asthma. Similarly, FEV1% predicted, FEV1/FVC% and FeNO were significantly associated with asthma. A predictive model combining these four parameters yielded an AUC 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.CONCLUSIONCombining wheezing intensity scale with spirometry and FeNO may help in improving asthma diagnosis accuracy in clinical practice.
Disciplines :
Public health, health care sciences & services
Author, co-author :
Louis, Gilles ; Université de Liège - ULiège > Santé publique : de la Biostatistique à la Promotion de la Santé
Schleich, FLorence ; Centre Hospitalier Universitaire de Liège - CHU > > Service de pneumologie - allergologie
Guillaume, Michèle ; Université de Liège - ULiège > Département des sciences de la santé publique > Santé publique : aspects spécifiques
Kirkove, Delphine ; Université de Liège - ULiège > Département des sciences de la santé publique > Education thérapeutique du patient au service des soins intégrés
Zahrei, Halehsadat; Department of Public Health, Biostatistics Unit, University of Liège, Liege, Belgium
Donneau, Anne-Françoise ; Université de Liège - ULiège > Département des sciences de la santé publique
Henket, Monique ; Centre Hospitalier Universitaire de Liège - CHU > > Service de pneumologie - allergologie
PAULUS, Virginie ; Centre Hospitalier Universitaire de Liège - CHU > > Service de pneumologie - allergologie
GUISSARD, Françoise ; Centre Hospitalier Universitaire de Liège - CHU > > Service de pneumologie - allergologie
Louis, Renaud ; Centre Hospitalier Universitaire de Liège - CHU > > Service de pneumologie - allergologie
Pétré, Benoît ; Université de Liège - ULiège > Département des sciences de la santé publique > Education thérapeutique du patient au service des soins intégrés
Language :
English
Title :
Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
Publication date :
2023
Journal title :
ERJ Open Research
eISSN :
2312-0541
Publisher :
European Respiratory Society (ERS)
Pages :
00451-2022
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
BELSPO - Belgian Science Policy Office ERDF - European Regional Development Fund
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