Metastatic sites as predictors in advanced NSCLC treated with PD-1 inhibitors: a systematic review and meta-analysis

ABSTRACT

Background

Programmed cell death protein 1 (PD-1) inhibitors are the first-line treatment for advanced non-small-cell lung cancer (NSCLC) patients. However, their efficacy in metastatic NSCLC patients remains controversial.

Aim of the study

The aim of our study was to evaluate the prognosis of advanced metastatic NSCLC patients treated with PD-1 inhibitors, and discuss the predictive effect of metastatic site on the long-term outcome.

Methods

The Embase, Ovid Medline, Cochrane Central Register of Controlled Trials, and PubMed databases were systematically screened up to February 10, 2020. Twenty-five eligible studies, involving 8,067 patients that assessed the impact of metastatic sites on survival outcome were incorporated in our study. Overall survival (OS) and progression-free survival (PFS) were described as hazard ratio (HR) with 95% confidence interval (CI).

Results

Among the advanced NSCLC patients, the median proportion of brain, liver, bone, and adrenal gland metastases were 21%, 17%, 35%, and 21%, respectively. Patients with metastases to the brain, liver, and bone had worse OS compared to patients without these metastases when treated with PD-1 inhibitors. Similarly, patients with metastasis to the brain and liver were more likely to progress when treated with PD-1 inhibitors. Besides, patients with multiple metastatic sites had worse PFS compared to patients with one metastatic site, while no significant difference was found in terms of OS.

Conclusions

Based on the findings of our systematic review and meta-analysis, metastatic sites were independent predictors of the survival outcome for advanced NSCLC patients treated with PD-1 inhibitors.

KEYWORDS:

• Non-small cell lung cancer
• PD-1
• metastatic site

Disclosure of potential conflicts of interest

No potential conflicts of interest were disclosed.

Author’s contribution

Design of the meta-analysis: Yangyun Huang, Lihuan Zhu and Xiaojie Pan

Literature screening: Tianxing Guo and Wenshu Chen

Quality assessment: Zhenlong Zhang and Wujin Li

Statistics analysis: Yangyun Huang and Lihuan Zhu

Write and revise: Yangyun Huang, Lihuan Zhu, Tianxing Guo, Wenshu Chen, Zhenlong Zhang, Wujin Li, and Xiaojie Pan