The Gender-Age-Physiology (GAP) model is a validated, baseline-risk prediction model for mortality in idiopathic pulmonary fibrosis. Longitudinal variables have been shown to contribute to risk prediction in idiopathic pulmonary fibrosis and may improve the predictive performance of the baseline GAP model. Our aims were to further validate the GAP model and evaluate whether the addition of longitudinal variables improves its predictive performance. The study population was derived from a large clinical trials cohort of patients with idiopathic pulmonary fibrosis (n=1109). Model performance was determined by improvement in the C-statistic, net reclassification improvement, clinical net reclassification improvement, and a goodness-of-fit test. The GAP model had good discriminative performance with a C-statistic of 0.757 (95% CI 0.750-0.764). However, the original GAP model tended to overestimate risk in this cohort. A novel, easy to use model, consisting of the original GAP predictors plus history of respiratory hospitalisation and 24-week change in forced vital capacity (the longitudinal GAP model) improved model performance with a C-statistic of 0.785 (95% CI 0.780-0.790), net reclassification improvement of 8.5%, clinical net reclassification improvement of 25%, and a goodness-of-fit test of 0.929. The LongitudinalGAP model, along with the original GAP model, may unify baseline and longitudinal mortalityrisk prediction in idiopathic pulmonary fibrosis.
