Brett Ley1, Williamson Z Bradford2, Eric Vittinghoff3, Derek Weycker4, Roland M du Bois5, Harold R Collard1. 1. 1 Department of Medicine and. 2. 2 InterMune Inc., Brisbane, California. 3. 3 Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California. 4. 4 Policy Analysis Inc., Brookline, Massachusetts; and. 5. 5 Imperial College, London, United Kingdom.
Abstract
RATIONALE: Mortality prediction is well studied in idiopathic pulmonary fibrosis (IPF), but little is known about predictors of premortality disease progression. Identification of patients at risk for disease progression would be useful for clinical decision-making and designing clinical trials. OBJECTIVES: To develop prediction models for disease progression in IPF. METHODS: In a large clinical trial cohort of patients with IPF (n = 1,113), we comprehensively screened multivariate models of candidate baseline and past-change predictors for disease progression defined by 48-week worsening of FVC, dyspnea (University of California, San Diego Shortness of Breath Questionnaire [UCSD SOBQ]), 6-minute-walk distance (6MWD), and occurrence of respiratory hospitalization, or death. Progression outcomes were modeled as appropriate, by slope change using linear regression models and time to binary outcomes using Cox proportional hazards models. MEASUREMENTS AND MAIN RESULTS: The overall cohort experienced considerable disease progression. Top-performing prediction models did not meaningfully predict most measures of disease progression. For example, prediction modeling explained less than or equal to 1% of the observed variation in 48-week slope change in FVC, UCSD SOBQ, and 6MWD. Models performed better for binary measures of time to disease progression but were still largely inaccurate (cross-validated C statistic ≤0.63 for ≥10% decline in FVC or death, ≤0.68 for ≥20-U increase in UCSD SOBQ or death, ≤0.70 for ≥100 m decline in 6MWD or death). Models for time to respiratory hospitalization or death (C statistic ≤0.77) or death alone (C statistic ≤0.81) demonstrated acceptable discriminative performance. CONCLUSIONS: Clinical prediction models poorly predicted physiologic and functional disease progression in IPF. This is in contrast to respiratory hospitalization and mortality prediction.
RCT Entities:
RATIONALE: Mortality prediction is well studied in idiopathic pulmonary fibrosis (IPF), but little is known about predictors of premortality disease progression. Identification of patients at risk for disease progression would be useful for clinical decision-making and designing clinical trials. OBJECTIVES: To develop prediction models for disease progression in IPF. METHODS: In a large clinical trial cohort of patients with IPF (n = 1,113), we comprehensively screened multivariate models of candidate baseline and past-change predictors for disease progression defined by 48-week worsening of FVC, dyspnea (University of California, San Diego Shortness of Breath Questionnaire [UCSD SOBQ]), 6-minute-walk distance (6MWD), and occurrence of respiratory hospitalization, or death. Progression outcomes were modeled as appropriate, by slope change using linear regression models and time to binary outcomes using Cox proportional hazards models. MEASUREMENTS AND MAIN RESULTS: The overall cohort experienced considerable disease progression. Top-performing prediction models did not meaningfully predict most measures of disease progression. For example, prediction modeling explained less than or equal to 1% of the observed variation in 48-week slope change in FVC, UCSD SOBQ, and 6MWD. Models performed better for binary measures of time to disease progression but were still largely inaccurate (cross-validated C statistic ≤0.63 for ≥10% decline in FVC or death, ≤0.68 for ≥20-U increase in UCSD SOBQ or death, ≤0.70 for ≥100 m decline in 6MWD or death). Models for time to respiratory hospitalization or death (C statistic ≤0.77) or death alone (C statistic ≤0.81) demonstrated acceptable discriminative performance. CONCLUSIONS: Clinical prediction models poorly predicted physiologic and functional disease progression in IPF. This is in contrast to respiratory hospitalization and mortality prediction.
Authors: Roland M du Bois; Derek Weycker; Carlo Albera; Williamson Z Bradford; Ulrich Costabel; Alex Kartashov; Talmadge E King; Lisa Lancaster; Paul W Noble; Steven A Sahn; Michiel Thomeer; Dominique Valeyre; Athol U Wells Journal: Am J Respir Crit Care Med Date: 2011-09-22 Impact factor: 21.405
Authors: Roland M du Bois; Carlo Albera; Williamson Z Bradford; Ulrich Costabel; Jonathan A Leff; Paul W Noble; Steven A Sahn; Dominique Valeyre; Derek Weycker; Talmadge E King Journal: Eur Respir J Date: 2013-12-05 Impact factor: 16.671
Authors: Roland M du Bois; Derek Weycker; Carlo Albera; Williamson Z Bradford; Ulrich Costabel; Alex Kartashov; Lisa Lancaster; Paul W Noble; Ganesh Raghu; Steven A Sahn; Javier Szwarcberg; Michiel Thomeer; Dominique Valeyre; Talmadge E King Journal: Am J Respir Crit Care Med Date: 2011-08-15 Impact factor: 21.405
Authors: Luca Richeldi; Christopher J Ryerson; Joyce S Lee; Paul J Wolters; Laura L Koth; Brett Ley; Brett M Elicker; Kirk D Jones; Talmadge E King; Jay H Ryu; Harold R Collard Journal: Thorax Date: 2012-03-17 Impact factor: 9.139
Authors: A Whitney Brown; Chelsea P Fischer; Oksana A Shlobin; Russell G Buhr; Shahzad Ahmad; Nargues A Weir; Steven D Nathan Journal: Chest Date: 2015-01 Impact factor: 9.410
Authors: Margaret L Salisbury; Meng Xia; Yueren Zhou; Susan Murray; Nabihah Tayob; Kevin K Brown; Athol U Wells; Shelley L Schmidt; Fernando J Martinez; Kevin R Flaherty Journal: Chest Date: 2016-01-12 Impact factor: 9.410
Authors: Brett Ley; Christopher J Ryerson; Eric Vittinghoff; Jay H Ryu; Sara Tomassetti; Joyce S Lee; Venerino Poletti; Matteo Buccioli; Brett M Elicker; Kirk D Jones; Talmadge E King; Harold R Collard Journal: Ann Intern Med Date: 2012-05-15 Impact factor: 25.391
Authors: Talmadge E King; Williamson Z Bradford; Socorro Castro-Bernardini; Elizabeth A Fagan; Ian Glaspole; Marilyn K Glassberg; Eduard Gorina; Peter M Hopkins; David Kardatzke; Lisa Lancaster; David J Lederer; Steven D Nathan; Carlos A Pereira; Steven A Sahn; Robert Sussman; Jeffrey J Swigris; Paul W Noble Journal: N Engl J Med Date: 2014-05-18 Impact factor: 91.245
Authors: Changwan Ryu; Huanxing Sun; Mridu Gulati; Jose D Herazo-Maya; Yonglin Chen; Awo Osafo-Addo; Caitlin Brandsdorfer; Julia Winkler; Christina Blaul; Jaden Faunce; Hongyi Pan; Tony Woolard; Argyrios Tzouvelekis; Danielle E Antin-Ozerkis; Jonathan T Puchalski; Martin Slade; Anjelica L Gonzalez; Daniel F Bogenhagen; Varvara Kirillov; Carol Feghali-Bostwick; Kevin Gibson; Kathleen Lindell; Raimund I Herzog; Charles S Dela Cruz; Wajahat Mehal; Naftali Kaminski; Erica L Herzog; Glenda Trujillo Journal: Am J Respir Crit Care Med Date: 2017-12-15 Impact factor: 21.405
Authors: Brett Ley; Jeffrey Swigris; Bann-Mo Day; John L Stauffer; Karina Raimundo; Willis Chou; Harold R Collard Journal: Am J Respir Crit Care Med Date: 2017-09-15 Impact factor: 21.405
Authors: Margaret L Salisbury; David A Lynch; Edwin J R van Beek; Ella A Kazerooni; Junfeng Guo; Meng Xia; Susan Murray; Kevin J Anstrom; Eric Yow; Fernando J Martinez; Eric A Hoffman; Kevin R Flaherty Journal: Am J Respir Crit Care Med Date: 2017-04-01 Impact factor: 21.405
Authors: Ayodeji Adegunsoye; Shehabaldin Alqalyoobi; Angela Linderholm; Willis S Bowman; Cathryn T Lee; Janelle Vu Pugashetti; Nandini Sarma; Shwu-Fan Ma; Angela Haczku; Anne Sperling; Mary E Strek; Imre Noth; Justin M Oldham Journal: Chest Date: 2020-05-22 Impact factor: 9.410