Year: 2023
Type: article
Study design: Observational Study
Abstract: Background Idiopathic pulmonary fibrosis (IPF) with co-existent emphysema, termed combined pulmonary fibrosis and emphysema (CPFE) may be associated with reduced FVC decline compared to non-CPFE IPF patients. We examined associations between mortality and functional measures of disease progression in two IPF cohorts. Methods Visual emphysema extent (CPFE:non-CPFE: derivation cohort=317:183; replication cohort=358:152), scored on computed tomography imaging subgrouped CPFE patients using either a) 10%, or b) 15% visual emphysema threshold, or c) an unsupervised machine learning model considering emphysema and ILD extents. Baseline characteristics, 1-year forced vital capacity (FVC) and diffusion capacity for carbon monoxide (DLco) decline (linear mixed effects models), and their associations with mortality (multivariable Cox regression models) were compared across CPFE and non-CPFE subgroups. Results In both IPF cohorts, CPFE patients with >10% emphysema had a greater smoking history and lower baseline DLco compared to CPFE patients with <10% emphysema. Using multivariable Cox regression analyses in patients with >10% emphysema, 1-year DLco decline was a better indicator of mortality than 1-year FVC decline. Results were maintained in patients suitable for therapeutic IPF trials. Results were replicated in the >15% emphysema population and using unsupervised machine learning. Importantly, the unsupervised machine learning approach identified CPFE patients in whom FVC decline did not associate strongly with mortality. In non-CPFE IPF patients, 1-year FVC declines >5% and >10% showed comparable mortality associations. Conclusion When assessing disease progression in IPF, DLco decline should be considered in patients with >10% emphysema and a >5% 1-year FVC decline threshold considered in non-CPFE IPF patients.
Source: European Respiratory Journal
Authors: An Zhao, Eyjolfur Gudmundsson, Nesrin Mogulkoc, Coline van Moorsel, Tamera J. Corte, Pardeep Vasudev, Chiara Romei, Robert Chapman, Tim J.M. Wallis, Emma Denneny, Tinne Goos, Recep Savas, Asia Ahmed, Christopher J. Brereton, Hendrik W. van Es, Helen Jo, Annalisa De Liperi, Mark Duncan, Katarina Pontoppidan, Laurens J. De Sadeleer, Frouke van Beek, Joseph Barnett, Gary Cross, Alex Procter, Marcel Veltkamp, Peter Hopkins, Yuben Moodley, Alessandro Taliani, Magali Taylor, Stijn Verleden, Laura Tavanti, Marie Vermant, Arjun Nair, Iain Stewart, Sam M. Janes, Alexandra L. Young, David Barber, Daniel C. Alexander, Joanna C. Porter, Athol U. Wells, Mark G. Jones, Wim A. Wuyts, Joseph Jacob
Institutions: University College London, Ege Üniversitesi Tıp Fakültesi Hastanesi, St. Antonius Ziekenhuis, The University of Sydney, Royal Prince Alfred Hospital, University of Pisa, Azienda Ospedaliera Universitaria Pisana, University College London Hospitals NHS Foundation Trust, NIHR Southampton Biomedical Research Centre, University of Southampton, Universitair Ziekenhuis Leuven, KU Leuven, University College Hospital, Helmholtz Munich, Royal Free London NHS Foundation Trust, Royal United Hospital, Royal United Hospital Bath NHS Trust, University Medical Center Utrecht, Prince Charles Hospital, The University of Western Australia, Fiona Stanley Hospital, University of Antwerp, Imperial College London, King's College London, Royal Brompton Hospital
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funders: American Thoracic Society, GlaxoSmithKline, Sanofi, Biogen, Wellcome Trust, National Institute for Health and Care Research, University College London, European Commission, Fonds Wetenschappelijk Onderzoek, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, China Scholarship Council, Lung Foundation Australia, University College London Hospitals NHS Foundation Trust, Vlaamse regering, National Institute for Health Research Southampton Biomedical Research Centre, HORIZON EUROPE Framework Programme, Medical Research Council, Engineering and Physical Sciences Research Council
Awards: G1735096943, G2810537366, Medical image computing for next-generation healthcare technology, G339059223, G3533933950, Computer-based analysis of early fibrosing lung disease, Early detection of familial idiopathic pulmonary fibrosis: lessons for the whole spectrum of interstitial lung diseases, G4804885063, G5337825365, Computer-based analysis of early fibrosing lung disease
OpenAlex ID: W4388722161