Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Louis, Gilles, Schleich, Florence, Guillaume, Michèle, Kirkove, Delphine, Nekoee Zahrei, Halehsadat, Donneau, Anne-Françoise, Henket, Monique, Paulus, Virginie, Guissard, Françoise, Louis, Renaud, Pétré, Benoit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Respiratory Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900444/
https://www.ncbi.nlm.nih.gov/pubmed/36755965
http://dx.doi.org/10.1183/23120541.00451-2022
_version_ 1784882849144373248
author Louis, Gilles
Schleich, Florence
Guillaume, Michèle
Kirkove, Delphine
Nekoee Zahrei, Halehsadat
Donneau, Anne-Françoise
Henket, Monique
Paulus, Virginie
Guissard, Françoise
Louis, Renaud
Pétré, Benoit
author_facet Louis, Gilles
Schleich, Florence
Guillaume, Michèle
Kirkove, Delphine
Nekoee Zahrei, Halehsadat
Donneau, Anne-Françoise
Henket, Monique
Paulus, Virginie
Guissard, Françoise
Louis, Renaud
Pétré, Benoit
author_sort Louis, Gilles
collection PubMed
description 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 (F(ENO)) 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 (FEV(1))) and/or a positive bronchial challenge test (provocative concentration of methacholine causing a 20% fall in FEV(1) ≤8 mg·mL(−1)). In order to assess the diagnostic performance of symptoms, spirometric indices and F(ENO), 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, FEV(1) (% pred), FEV(1)/forced vital capacity (%) and F(ENO) 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 F(ENO) may help in improving asthma diagnosis accuracy in clinical practice.
format Online
Article
Text
id pubmed-9900444
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher European Respiratory Society
record_format MEDLINE/PubMed
spelling pubmed-99004442023-02-07 Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis Louis, Gilles Schleich, Florence Guillaume, Michèle Kirkove, Delphine Nekoee Zahrei, Halehsadat Donneau, Anne-Françoise Henket, Monique Paulus, Virginie Guissard, Françoise Louis, Renaud Pétré, Benoit ERJ Open Res Original Research Articles 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 (F(ENO)) 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 (FEV(1))) and/or a positive bronchial challenge test (provocative concentration of methacholine causing a 20% fall in FEV(1) ≤8 mg·mL(−1)). In order to assess the diagnostic performance of symptoms, spirometric indices and F(ENO), 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, FEV(1) (% pred), FEV(1)/forced vital capacity (%) and F(ENO) 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 F(ENO) may help in improving asthma diagnosis accuracy in clinical practice. European Respiratory Society 2023-02-06 /pmc/articles/PMC9900444/ /pubmed/36755965 http://dx.doi.org/10.1183/23120541.00451-2022 Text en Copyright ©The authors 2023 https://creativecommons.org/licenses/by-nc/4.0/This version is distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0. For commercial reproduction rights and permissions contact permissions@ersnet.org (mailto:permissions@ersnet.org)
spellingShingle Original Research Articles
Louis, Gilles
Schleich, Florence
Guillaume, Michèle
Kirkove, Delphine
Nekoee Zahrei, Halehsadat
Donneau, Anne-Françoise
Henket, Monique
Paulus, Virginie
Guissard, Françoise
Louis, Renaud
Pétré, Benoit
Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
title Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
title_full Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
title_fullStr Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
title_full_unstemmed Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
title_short Development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
title_sort development and validation of a predictive model combining patient-reported outcome measures, spirometry and exhaled nitric oxide fraction for asthma diagnosis
topic Original Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900444/
https://www.ncbi.nlm.nih.gov/pubmed/36755965
http://dx.doi.org/10.1183/23120541.00451-2022
work_keys_str_mv AT louisgilles developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT schleichflorence developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT guillaumemichele developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT kirkovedelphine developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT nekoeezahreihalehsadat developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT donneauannefrancoise developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT henketmonique developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT paulusvirginie developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT guissardfrancoise developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT louisrenaud developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis
AT petrebenoit developmentandvalidationofapredictivemodelcombiningpatientreportedoutcomemeasuresspirometryandexhalednitricoxidefractionforasthmadiagnosis