The performance of the GAP model in patients with rheumatoid arthritis associated interstitial lung disease

- RA-ILD is associated with high morbidity and mortality.
- The GAP model that was derived for mortality risk prediction in IPF performs similarly in patients with RA-ILD.
- The addition of other clinical variables did not meaningfully improve the performance of the model.

BackgroundRheumatoid 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.MethodsWe 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.ResultsPatients 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.ConclusionThe GAP model that was derived for IPF performs similarly as a mortality risk prediction tool in RA-ILD.