Predicting Mortality in Patients with Rheumatoid Arthritis Related Interstitial Lung Disease: Expanding The GAP Model

Rationale: Rheumatoid arthritis-associated interstitial lung disease (RA-ILD) is a disease associated with morbidity and mortality. There is a high prevalence of usual interstitial pneumonia (UIP) pattern in RA-ILD and similarities have been observed between patients with idiopathic pulmonary fibrosis (IPF) and the UIP 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 (Mayo Clinic, University of Ulsan, University of California, San Francisco and University of Modena & Reggio Emilia). The primary endpoint was mortality. To handle the issue of missing data, multiple imputation by iterative chained equations was used, resulting in 20 completed datasets. Linear and logistic imputation models were used for continuous and binary covariates, respectively. Using the GAP model as the baseline mortality prediction model, we determined the additive model performance for mortality risk prediction by incorporating additional variables. Model discrimination was assessed using the c-index. Results: Patients had a mean age of 65 years and were predominantly female (54%). The mean forced vital capacity % predicted was 73 and the mean diffusing capacity for carbon monoxide (DLCO) % predicted was 55. The majority of patients had positive rheumatoid factor (RF) (89%) or positive anti-cyclic citrullinated peptide antibody (71%). Twenty-four percent of patients had a definite UIP pattern on high-resolution computed tomography (HRCT). The original GAP model (Gender, Age, FVC%, DLCO%) had a c-index of 0.69 in our cohort. The performance of this model improved by expanding the GAP model to include 2 additional variables: definite UIP pattern on HRCT and positive RF. The c-index of this expanded model was 0.71. Conclusions: The addition of 2 variables, definite UIP pattern on HRCT and RF, improves the performance of the GAP model to predict mortality in patients with RA-ILD.