Background: The gender-age-physiology (GAP) model was developed to predict the risk of death. Comorbidities are common in idiopathic pulmonary fibrosis (IPF) and may impact on survival. We evaluated the ability of comorbidities to improve prediction of survival in IPF patients beyond the variables included in the GAP model.
Methods: We developed a prediction model named TORVAN using data from two independent cohorts. Continuous and point-score prediction models were developed with estimation of full and sparse versions of both. Model discrimination was assessed using the C-index and calibrated by comparing predicted and observed cumulative mortality at 1-5 years.
Results: Discrimination was similar for the sparse continuous model in the derivation and validation cohorts (C-index 71.0 versus 70.0, respectively), and significantly improved the performance of the GAP model in the validation cohort (increase in C-index of 3.8, p=0.001). In contrast, the sparse point-score model did not perform as well in the validation cohort (C-index 72.5 in the derivation cohort versus 68.1 in the validation cohort), but still significantly improved upon the performance of the GAP model (C-index increased by 2.5, p=0.037).
Conclusions: The inclusion of comorbidities in TORVAN models significantly improved the discriminative performance in prediction of risk of death compared to GAP.
Copyright ©ERS 2019.