Ayodeji Adegunsoye1, Shehabaldin Alqalyoobi2, Angela Linderholm3, Willis S Bowman3, Cathryn T Lee1, Janelle Vu Pugashetti3, Nandini Sarma3, Shwu-Fan Ma4, Angela Haczku3, Anne Sperling1, Mary E Strek1, Imre Noth4, Justin M Oldham5. 1. Department of Medicine, Section of Pulmonary and Critical Care Medicine, The University of Chicago, Chicago, IL. 2. Department of Internal Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, East Carolina University, Greenville, NC. 3. Department of Internal Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of California at Davis, Sacramento, CA. 4. Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Virginia, Charlotteville, VA. 5. Department of Internal Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, University of California at Davis, Sacramento, CA. Electronic address: joldham@ucdavis.edu.
Abstract
BACKGROUND: A number of circulating plasma biomarkers have been shown to predict survival in patients with idiopathic pulmonary fibrosis (IPF), but most were identified before the use of antifibrotic (AF) therapy in this population. Because pirfenidone and nintedanib have been shown to slow IPF progression and may prolong survival, the role of such biomarkers in AF-treated patients is unclear. RESEARCH QUESTION: To determine whether plasma concentration of cancer antigen 125 (CA-125), C-X-C motif chemokine 13 (CXCL13), matrix metalloproteinase 7 (MMP7), surfactant protein D (SP-D), chitinase-3-like protein-1 (YKL-40), vascular cell adhesion protein-1 (VCAM-1), and osteopontin (OPN) is associated with differential transplant-free survival (TFS) in AF-exposed and nonexposed patients with IPF. STUDY DESIGN AND METHODS: A pooled, multicenter, propensity-matched analysis of IPF patients with and without AF exposure was performed. Optimal thresholds for biomarker dichotomization were identified in each group using iterative Cox regression. Longitudinal biomarker change was assessed in a subset of patients using linear mixed regression modeling. A clinical-molecular signature of IPF TFS was then derived and validated in an independent IPF cohort. RESULTS: Three hundred twenty-five patients were assessed, of which 68 AF-exposed and 172 nonexposed patients were included after propensity matching. CA-125, CXCL13, MMP7, YKL-40, and OPN predicted differential TFS in AF-exposed patients but at higher thresholds than in AF-nonexposed individuals. Plasma biomarker level generally increased over time in nonexposed patients but remained unchanged in AF-exposed patients. A clinical-molecular signature predicted decreased TFS in AF-exposed patients (hazard ratio [HR], 5.91; 95% CI, 2.25-15.5; P < .001) and maintained this association in an independent AF-exposed cohort (HR, 3.97; 95% CI, 1.62-9.72; P = .003). INTERPRETATION: Most plasma biomarkers assessed predicted differential TFS in AF-exposed patients with IPF, but at higher thresholds than in nonexposed patients. A clinical-molecular signature of IPF TFS may provide a reliable predictor of outcome risk in AF-treated patients but requires additional research for optimization and validation.
BACKGROUND: A number of circulating plasma biomarkers have been shown to predict survival in patients with idiopathic pulmonary fibrosis (IPF), but most were identified before the use of antifibrotic (AF) therapy in this population. Because pirfenidone and nintedanib have been shown to slow IPF progression and may prolong survival, the role of such biomarkers in AF-treated patients is unclear. RESEARCH QUESTION: To determine whether plasma concentration of cancer antigen 125 (CA-125), C-X-C motif chemokine 13 (CXCL13), matrix metalloproteinase 7 (MMP7), surfactant protein D (SP-D), chitinase-3-like protein-1 (YKL-40), vascular cell adhesion protein-1 (VCAM-1), and osteopontin (OPN) is associated with differential transplant-free survival (TFS) in AF-exposed and nonexposed patients with IPF. STUDY DESIGN AND METHODS: A pooled, multicenter, propensity-matched analysis of IPF patients with and without AF exposure was performed. Optimal thresholds for biomarker dichotomization were identified in each group using iterative Cox regression. Longitudinal biomarker change was assessed in a subset of patients using linear mixed regression modeling. A clinical-molecular signature of IPF TFS was then derived and validated in an independent IPF cohort. RESULTS: Three hundred twenty-five patients were assessed, of which 68 AF-exposed and 172 nonexposed patients were included after propensity matching. CA-125, CXCL13, MMP7, YKL-40, and OPN predicted differential TFS in AF-exposed patients but at higher thresholds than in AF-nonexposed individuals. Plasma biomarker level generally increased over time in nonexposed patients but remained unchanged in AF-exposed patients. A clinical-molecular signature predicted decreased TFS in AF-exposed patients (hazard ratio [HR], 5.91; 95% CI, 2.25-15.5; P < .001) and maintained this association in an independent AF-exposed cohort (HR, 3.97; 95% CI, 1.62-9.72; P = .003). INTERPRETATION: Most plasma biomarkers assessed predicted differential TFS in AF-exposed patients with IPF, but at higher thresholds than in nonexposed patients. A clinical-molecular signature of IPF TFS may provide a reliable predictor of outcome risk in AF-treated patients but requires additional research for optimization and validation.
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