Julie Morisset1, Eric Vittinghoff2, Bo Young Lee3, Roberto Tonelli4, Xiaowen Hu5, Brett M Elicker6, Jay H Ryu5, Kirk D Jones7, Stefania Cerri4, Andreina Manfredi8, Marco Sebastiani8, Andrew J Gross9, Brett Ley9, Paul J Wolters9, Talmadge E King9, Dong Soon Kim3, Harold R Collard9, Joyce S Lee10. 1. Department of Medicine, University of California, San Francisco, CA, USA. Electronic address: julie.morisset@umontreal.ca. 2. Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA. 3. Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan, Seoul, South Korea. 4. Department of Respiratory Diseases, University of Modena & Reggio Emilia, Modena, Italy. 5. Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USA. 6. Department of Radiology, University of California, San Francisco, CA, USA. 7. Department of Pathology, University of California, San Francisco, CA, USA. 8. Department of Rheumatology, University of Modena & Reggio Emilia, Modena, Italy. 9. Department of Medicine, University of California, San Francisco, CA, USA. 10. Department of Medicine, University of Colorado Denver, CO, USA.
Abstract
BACKGROUND: Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is associated with significant morbidity and mortality. Similarities have been observed between patients with idiopathic pulmonary fibrosis (IPF) and the UIP (usual interstitial pneumonia) form of RA-ILD. The GAP (gender, age, physiology) model has been shown to predict mortality in patients with IPF, but its ability to predict mortality in RA-ILD is not known. METHODS: We identified 309 patients with RA-ILD at 4 academic centers with ongoing longitudinal cohorts of patients with ILD. The primary endpoint was mortality. To handle missing data (n = 219 subjects with complete dataset), multiple imputation by iterative chained equations was used. Using the GAP model as a baseline, we assessed improvements in mortality risk prediction achieved by incorporating additional variables. Model discrimination was assessed using the c-index, and calibration was checked by comparing observed and expected incidence of death. RESULTS: Patients had a mean age of 65 years and were predominantly female (54%). The mean forced vital capacity (FVC) % predicted was 73 and the mean diffusing capacity for carbon monoxide (DLCO) % predicted was 55. Twenty-four percent of the 236 patients with a high-resolution computed tomography scan available for review had a definite UIP pattern. The original GAP model, including gender, age, FVC%, and DLCO%, had a c-index of 0.746 in our cohort. Calibration of this model was satisfactory at 1, 2 and 3 years. Model discrimination was not meaningfully improved by adding other clinical variables. CONCLUSION: The GAP model that was derived for IPF performs similarly as a mortality risk prediction tool in RA-ILD.
BACKGROUND:Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is associated with significant morbidity and mortality. Similarities have been observed between patients with idiopathic pulmonary fibrosis (IPF) and the UIP (usual interstitial pneumonia) form of RA-ILD. The GAP (gender, age, physiology) model has been shown to predict mortality in patients with IPF, but its ability to predict mortality in RA-ILD is not known. METHODS: We identified 309 patients with RA-ILD at 4 academic centers with ongoing longitudinal cohorts of patients with ILD. The primary endpoint was mortality. To handle missing data (n = 219 subjects with complete dataset), multiple imputation by iterative chained equations was used. Using the GAP model as a baseline, we assessed improvements in mortality risk prediction achieved by incorporating additional variables. Model discrimination was assessed using the c-index, and calibration was checked by comparing observed and expected incidence of death. RESULTS:Patients had a mean age of 65 years and were predominantly female (54%). The mean forced vital capacity (FVC) % predicted was 73 and the mean diffusing capacity for carbon monoxide (DLCO) % predicted was 55. Twenty-four percent of the 236 patients with a high-resolution computed tomography scan available for review had a definite UIP pattern. The original GAP model, including gender, age, FVC%, and DLCO%, had a c-index of 0.746 in our cohort. Calibration of this model was satisfactory at 1, 2 and 3 years. Model discrimination was not meaningfully improved by adding other clinical variables. CONCLUSION: The GAP model that was derived for IPF performs similarly as a mortality risk prediction tool in RA-ILD.
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