Risk prediction and end-points in idiopathic pulmonary fibrosis: one step at a time.

Abstract

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with a median survival of approximately 3 years from diagnosis. Accurate prediction of mortality is important in IPF, as it helps determine the urgency of lung transplantation, guides other management and end-of-life decisions, and facilitates enrichment of clinical trial populations. Although most patients with IPF die from progressive respiratory failure [1], predicting outcomes is challenging due to the heterogeneity of disease progression. In this issue of the European Respiratory Journal , du Bois et al. [2] use the INSPIRE (International Study of Survival Outcomes in Idiopathic Pulmonary Fibrosis with Interferon-γ-1b) dataset to describe a new prediction model that estimates mortality in IPF. The INSPIRE study was a multicentre double-blind randomised trial comparing interferon-γ-1b to placebo in 826 patients with mild to moderate IPF [3]. This trial did not meet its primary end-point but has generated high-quality data that continue to provide valuable insight into the progression of IPF. du Bois et al. [4] have previously used the INSPIRE data to show that age, baseline forced vital capacity (FVC), 24-week change in FVC, and recent respiratory hospitalisation independently predict 1-year mortality in patients with IPF [4]. These authors have now extended their findings by showing that mortality prediction is improved by adding both baseline and 24-week change in 6-min walking distance (6MWD) to this multivariate model [2]. This new study is a noteworthy addition to the literature, providing important data on the prediction of mortality in IPF and suggesting potential options for clinical trial end-points. The model developed by du Bois et al. [2] accurately estimates 1-year mortality in patients with IPF with a C-statistic of 0.80. The C-statistic, or C-index, is a measure …