Real life data on nintedanib safety: idiopathic pulmonary fibrosis versus systemic sclerosis-interstitial lung disease and strategies adopted to manage adverse effects

Inflammopharmacology(2023)

引用 0|浏览19
暂无评分
摘要
Objective Nintedanib (NIN) is an antifibrotic drug approved to slow the progression of idiopathic pulmonary fibrosis (IPF) and systemic sclerosis-related interstitial lung disease (SSc-ILD). NIN can frequently cause gastrointestinal adverse effects. We aimed to investigate the NIN safety profile in a real life setting, comparing IPF and SSc-ILD patients and evaluating the strategies adopted to manage NIN adverse effects. Methods Patients taking NIN for IPF or SSc-ILD were enrolled. Alongside epidemiological and disease-specific data, the period of NIN use and the need for dosage reduction and/or interruption were investigated. Particular attention was paid to possible adverse effects and strategies adopted to manage them. Results Twenty-seven SSc-ILD and 82 IPF patients were enrolled. No significant differences emerged between the two cohorts regarding the frequency of any possible adverse effect. Although the rates of NIN dosage reduction or interruption were similar between the two subgroups, SSc-ILD presented a mean period before NIN dosage reduction and NIN interruption significantly shorter than IPF (3 ± 2.6 vs 10.5 ± 8.9 months—p < 0.001 and 2.3 ± 0.5 vs 10.3 ± 9.9 months—p = 0.008, respectively). Several different strategies were tried to manage NIN adverse effects: especially in SSc-ILD, the variable combination of diet adjustment set by a nutritionist, probiotics and diosmectite was ultimately successful in maintaining patients on an adequate dose of NIN. Conclusion We presented data on the NIN safety profile in a real life setting, which was similar between SSc-ILD and IPF. A combination of multiple managing strategies and dose adjustment appears essential to cope optimally with NIN adverse effects.
更多
查看译文
关键词
Nintedanib,Systemic sclerosis,Idiopathic pulmonary fibrosis,Safety,Adverse effects,Management strategies
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要