Meta-Analysis of Effect of Nintedanib on Reducing FVC Decline Across Interstitial Lung Diseases.

ABSTRACT

INTRODUCTION: The effect of nintedanib on slowing the rate of decline in forced vital capacity (FVC) has been investigated in randomized placebo-controlled trials in subjects with idiopathic pulmonary fibrosis (IPF), other progressive fibrosing interstitial lung diseases (ILDs), and ILD associated with systemic sclerosis (SSc-ILD). We assessed the consistency of the effect of nintedanib on the rate of decline in FVC over 52 weeks across four placebo-controlled phase III trials. METHODS: We used data on FVC decline from the INPULSIS-1 and INPULSIS-2 trials in subjects with IPF, the INBUILD trial in subjects with progressing fibrosing ILDs other than IPF, and the SENSCIS trial in subjects with SSc-ILD. In each trial, the primary endpoint was the annual rate of decline in FVC (mL/year) assessed over 52 weeks. We performed fixed effect and random effects meta-analyses based on the relative treatment effect of nintedanib versus placebo on the rate of decline in FVC (mL/year) over 52 weeks. Heterogeneity of the relative treatment effect of nintedanib across populations was assessed using the I2 statistic, τ2 and corresponding p value from a Q test for heterogeneity. RESULTS: The combined analysis comprised 1257 subjects treated with nintedanib and 1042 subjects who received placebo. Nintedanib reduced the rate of decline in FVC (mL/year) over 52 weeks by 51.0% (95% CI 39.1, 63.0) compared with placebo. The relative effect (95% CI) was the same using the fixed effect and random effects models. There was no evidence of heterogeneity in the relative treatment effect of nintedanib across the populations studied (I2 = 0%, τ2 = 0, p = 0.93). CONCLUSIONS: A meta-analysis of data from four placebo-controlled trials demonstrated that nintedanib approximately halved the rate of decline in FVC over 52 weeks across subjects with different forms of pulmonary fibrosis, with no evidence of heterogeneity in its relative treatment effect across patient populations.