Prognostic Impact and Risk Factors of Immune-Related Pneumonitis in Patients With Non–Small-Cell Lung Cancer Who Received Programmed Death 1 Inhibitors

医学 彭布罗利珠单抗 无容量 肺炎 内科学 肺癌 不利影响 肿瘤科 阿替唑单抗 免疫系统 癌症 免疫疗法 免疫学
作者
Jun Fukihara,Koji Sakamoto,Junji Koyama,Takayasu Ito,Shingo Iwano,Masahiro Morise,Masahiro Ogawa,Yasuhiro Kondoh,Tomoki Kimura,Naozumi Hashimoto,Yoshinori Hasegawa
出处
期刊:Clinical Lung Cancer [Elsevier BV]
卷期号:20 (6): 442-450.e4 被引量:83
标识
DOI:10.1016/j.cllc.2019.07.006
摘要

Pneumonitis is one of the immune-related adverse events of programmed death 1 (PD-1) inhibitors that sometimes cause lethal outcomes. Although some recent reports have described PD-1 inhibitors as more effective in non-small-cell lung cancer (NSCLC) patients with immune-related adverse events than in those without, few data are available on the prognosis of those treated with PD-1 inhibitors who developed immune-related pneumonitis (IRP). Additionally, the robust risk factors of IRP have not been well elucidated.A retrospective review of patients with recurrent or advanced NSCLC who took a PD-1 inhibitor (nivolumab or pembrolizumab monotherapy) between January 2016 and March 2018 was undertaken. Radiologic findings such as unilateral infiltration were also defined as IRP as long as they were deemed relevant to PD-1 inhibitors.Twenty-seven (16%) of 170 patients developed IRP. Although 22 (81%) of 27 patients with IRP recovered with drug cessation with or without corticosteroid therapy, 8-week landmark analysis showed the overall survival after administration of the PD-1 inhibitor was significantly shorter in patients with IRP than in those without (8.7 vs. 23.0 months, P = .015). Patients with IRP tended to not receive next-line treatment and choose best supportive care after cessation of PD-1 inhibitor therapy. In the multivariate analysis, pembrolizumab (vs. nivolumab) and low serum albumin were independent risk factors for IRP.Development of IRP was correlated with poor prognosis in patients with NSCLC. Further study is necessary for establishing the best prediction and management strategies for IRP.
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