Features of asthma management: quantifying the patient‘s perspective using discrete choice modelling Source: Eur Respir J 2006; 28: Suppl. 50, 122s Year: 2006
Is it possible to predict asthma outcomes? A disease model for economic analysis. Source: International Congress 2017 – Asthma management Year: 2017
Temporal stability of asthma phenotypes identified by a clustering approach: An ECRHS-SAPALDIA-EGEA study Source: Annual Congress 2012 - Asthma: from childhood environment to adult phenotypes Year: 2012
Asthma as a nonlinear complex dynamic system: a novel approach to understand the temporal behaviour of chronic asthma and its response to β-agonists Source: Eur Respir Rev 2008; 17: 67-69 Year: 2008
A theory explaining time trends in asthma prevalence Source: Eur Respir J 2006; 27: 434-435 Year: 2006
A difficult case: distinctions between difficult asthma, true severe asthma and overlap Source: International Congress 2019 – PG11 Severe paediatric asthma Year: 2019
How much do factors other than smoking explain spatial variations in COPD mortality in the UK? Source: Eur Respir J 2005; 26: Suppl. 49, 217s Year: 2005
The consequences of different definitions in the prediction of asthma in children Source: Annual Congress 2008 - Paediatric airway diseases - pathophysiology and monitoring Year: 2008
Which parameters best reflect the severity of asthma? Analysis of 483 cases Source: Eur Respir J 2001; 18: Suppl. 33, 51s Year: 2001
Hierarchical linear models for longitudinal change in COPD - is there an effect of differential dropout between treatment groups on estimated decline rates? Source: Eur Respir J 2001; 18: Suppl. 33, 151s Year: 2001
Is it possible to identify phenotypes of problematic severe asthma in children using fluctuation based clustering? Source: International Congress 2016 – Paediatric asthma: recurrent, persistent, or severe obstruction and lung function techniques Year: 2016
How to define asthma in large-scale studies? Source: International Congress 2014 – Is asthma prevalence still increasing? Year: 2014
Measuring asthma control: a comparison of three classification systems Source: Eur Respir J 2010; 36: 269 Year: 2010
Measuring asthma control: a comparison of three classification systems Source: Annual Congress 2009 - Aspects of uncontrolled asthma Year: 2009
Which clinical variables best predict asthma control? Source: Annual Congress 2010 - Asthma: breath biomarkers and asthma control Year: 2010
Different definitions in childhood asthma: how dependable is the dependent variable? Source: Eur Respir J 2010; 36: 48-56 Year: 2010
The paradoxes of asthma management: time for a new approach? Source: Eur Respir J, 50 (3) 1701103; 10.1183/13993003.01103-2017 Year: 2017
A multivariate geo-statistical Bayesian model for analyzing the spatial prevalence of COPD: Implications on risk factors Source: International Congress 2015 – Epidemiology of respiratory disease Year: 2015
The influence of different schemes of basic treatment on functional indices in moderate–severe asthma patients Source: Eur Respir J 2006; 28: Suppl. 50, 54s Year: 2006
Comparing the cost-effectiveness of a wide range of COPD interventions using a stochastic population model for COPD Source: Annual Congress 2011 - Respiratory epidemiology: quality of life, therapy and socioeconomics Year: 2011