Alessandro Marcon1, Isa Cerveri2, Matthias Wjst3, Josep Antó4, Joachim Heinrich5, Christer Janson6, Deborah Jarvis7, Bénédicte Leynaert8, Nicole Probst-Hensch9, Cecilie Svanes10, Kjell Toren11, Peter Burney7, Roberto de Marco12. 1. Unit of Epidemiology and Medical Statistics, Department of Public Health and Community Medicine, University of Verona, Verona, Italy. Electronic address: alessandro.marcon@univr.it. 2. Istituto di Ricovero e Cura a Carattere Scientifico San Matteo Hospital Foundation, University of Pavia, Pavia, Italy. 3. Comprehensive Pneumology Center (CPC), Institute of Lung Biology and Disease (iLBD), Helmholtz Zentrum Muenchen, German Research Center for Environmental Health (GmbH), Munich, Germany; Institute of Medical Statistics and Epidemiology, Technische Universitaet Muenchen, Munich, Germany. 4. Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Universitat Pompeu Fabra, Departament de Ciències Experimentals i de la Salut, Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain. 5. Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Munich, Germany. 6. Department of Medical Sciences, Respiratory Medicine and Allergology, Uppsala University, Akademiska Sjukhuset, Uppsala, Sweden. 7. Respiratory Epidemiology and Public Health Group, National Heart and Lung Institute, Imperial College, London, United Kingdom. 8. Institut National de la Santé et de la Recherche Médicale, U700-Epidemiology, Faculté Paris Diderot, Paris VII, Paris, France. 9. Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland. 10. Bergen Respiratory Research Group, Institute of Medicine, University of Bergen, Bergen, Norway; Department of Occupational Medicine, Haukeland University Hospital, Bergen, Norway. 11. Section of Occupational and Environmental Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. 12. Unit of Epidemiology and Medical Statistics, Department of Public Health and Community Medicine, University of Verona, Verona, Italy.
Abstract
BACKGROUND: Evidence on the longitudinal association of airway responsiveness with respiratory diseases is scarce. The best indicator of responsiveness is still undetermined. OBJECTIVE: We investigated the association of airway responsiveness with the incidence of asthma, chronic obstructive pulmonary disease (COPD), and allergic rhinitis. METHODS: We studied 3851 subjects who underwent spirometry and methacholine challenge tests both at baseline (1991-1993), when they were 20 to 44 years old, and at follow-up (1999-2002) in the European Community Respiratory Health Survey. Airway responsiveness was defined based on the methacholine dose-response slope on both occasions. Incidence rate ratios for the association of airway responsiveness with disease occurrence were computed by using Poisson regression. RESULTS: With respect to reference (slope of the fourth quintile or greater), subjects with the greatest degree of airway responsiveness (slope less than the first quintile) showed the greatest risk of developing asthma, COPD, and allergic rhinitis (incidence rate ratios of 10.82, 5.53, and 4.84, respectively; all P < .01). A low slope predicted disease occurrence, even in subjects who did not reach a 20% decrease in FEV1 at the cumulative dose of 1 mg of methacholine (PD20 >1 mg). A decrease in slope over time was an independent predictor of disease risk. CONCLUSION: Airway responsiveness predicted new-onset asthma, COPD, and allergic rhinitis. Our study supports the use of a continuous noncensored indicator of airway responsiveness, such as the slope of the methacholine dose-response curve, in clinical practice and research because it showed clear advantages over PD20.
BACKGROUND: Evidence on the longitudinal association of airway responsiveness with respiratory diseases is scarce. The best indicator of responsiveness is still undetermined. OBJECTIVE: We investigated the association of airway responsiveness with the incidence of asthma, chronic obstructive pulmonary disease (COPD), and allergic rhinitis. METHODS: We studied 3851 subjects who underwent spirometry and methacholine challenge tests both at baseline (1991-1993), when they were 20 to 44 years old, and at follow-up (1999-2002) in the European Community Respiratory Health Survey. Airway responsiveness was defined based on the methacholine dose-response slope on both occasions. Incidence rate ratios for the association of airway responsiveness with disease occurrence were computed by using Poisson regression. RESULTS: With respect to reference (slope of the fourth quintile or greater), subjects with the greatest degree of airway responsiveness (slope less than the first quintile) showed the greatest risk of developing asthma, COPD, and allergic rhinitis (incidence rate ratios of 10.82, 5.53, and 4.84, respectively; all P < .01). A low slope predicted disease occurrence, even in subjects who did not reach a 20% decrease in FEV1 at the cumulative dose of 1 mg of methacholine (PD20 >1 mg). A decrease in slope over time was an independent predictor of disease risk. CONCLUSION: Airway responsiveness predicted new-onset asthma, COPD, and allergic rhinitis. Our study supports the use of a continuous noncensored indicator of airway responsiveness, such as the slope of the methacholine dose-response curve, in clinical practice and research because it showed clear advantages over PD20.
Authors: Anunya Hiranrattana; Debra A Stern; Stefano Guerra; Marilyn Halonen; Anne L Wright; Michael Daines; Fernando D Martinez; Wayne J Morgan Journal: Thorax Date: 2018-03-21 Impact factor: 9.139
Authors: Bruno Sposato; Marco Scalese; Maria Giovanna Migliorini; Maurizio Di Tomassi; Raffaele Scala Journal: Allergy Asthma Immunol Res Date: 2014-02-11 Impact factor: 5.764