Predicting Survival Across Chronic Interstitial Lung Disease The ILD-GAP Model

Background: Risk prediction is challenging in chronic interstitial lung disease (ILD) because of heterogeneity in disease-specific and patient-specific variables. Our objective was to determine whether mortality is accurately predicted in patients with chronic ILD using the GAP model, a clinical prediction model based on sex, age, and lung physiology, that was previously validated in patients with idiopathic pulmonary fibrosis. Methods: Patients with idiopathic pulmonary fibrosis (n = 307), chronic hypersensitivity pneumonitis (n = 206), connective tissue disease-associated ILD (n = 281), idiopathic nonspecifi c interstitial pneumonia (n = 45), or unclassifi able ILD (n = 173) were selected from an ongoing database (N = 1,012). Performance of the previously validated GAP model was compared with novel prediction models in each ILD subtype and the combined cohort. Patients with follow-up pulmonary function data were used for longitudinal model validation. Results: The GAP model had good performance in all ILD subtypes (c-index, 74.6 in the combined cohort), which was maintained at all stages of disease severity and during follow-up evaluation. The GAP model had similar performance compared with alternative prediction models. A modifi ed ILD-GAP Index was developed for application across all ILD subtypes to provide diseasespecifi c survival estimates using a single risk prediction model. This was done by adding a disease subtype variable that accounted for better adjusted survival in connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, and idiopathic nonspecifi c interstitial pneumonia. Conclusion: The GAP model accurately predicts risk of death in chronic ILD. The ILD-GAP model accurately predicts mortality in major chronic ILD subtypes and at all stages of disease.