Parametric Time‐to‐Event Model for Acute Exacerbations in Idiopathic Pulmonary Fibrosis

We describe a parametric time‐to‐event model for idiopathic pulmonary fibrosis (IPF) exacerbations and identify predictors of exacerbation risk using data obtained for the tyrosine‐kinase inhibitor nintedanib in two phase III studies (INPULSIS‐1/2). Parametric survival analysis was performed on time...

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Bibliographic Details
Main Authors: Fei Tang, Benjamin Weber, Susanne Stowasser, Julia Korell
Format: Article
Language:English
Published: Wiley 2020-02-01
Series:CPT: Pharmacometrics & Systems Pharmacology
Online Access:https://doi.org/10.1002/psp4.12485
Description
Summary:We describe a parametric time‐to‐event model for idiopathic pulmonary fibrosis (IPF) exacerbations and identify predictors of exacerbation risk using data obtained for the tyrosine‐kinase inhibitor nintedanib in two phase III studies (INPULSIS‐1/2). Parametric survival analysis was performed on time to first exacerbation (censoring on day 372), with univariate analysis to select statistically significant covariates (P = 0.05). Multivariate covariate models were developed using stepwise covariate modeling with forward inclusion (P = 0.05) and backward elimination (P = 0.01). Sixty‐three first exacerbation events were reported across 1,061 subjects in the INPULSIS studies. Baseline and decline of forced vital capacity (FVC)/percent‐predicted FVC (%pFVC), supplemental oxygen use, baseline CO diffusing capacity and age were statistically significant in the univariate analysis. The final covariate model included decline in FVC to week 52, baseline %pFVC, supplemental oxygen use, and age. The developed model may be used to identify patients at high risk of IPF exacerbations and accelerate development of novel treatments.
ISSN:2163-8306