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

特发性肺纤维化急性加重的参数化时间事件模型

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Abstract

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.

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