A Bayesian network meta-analysis on systemic therapy for previously treated gastric cancer

Area of Science:

• Oncology
• Clinical Trials
• Medical Statistics

Background:

• Advanced gastric cancer (AGC) presents significant treatment challenges.
• Salvage therapy plays a critical role in improving outcomes for patients with advanced disease.
• Identifying optimal treatment strategies is crucial for enhancing overall survival.

Purpose of the Study:

• To systematically review phase III randomized controlled trials (RCTs) for salvage treatment in advanced gastric cancer (AGC).
• To perform a Bayesian network meta-analysis to compare the efficacy of various salvage treatment regimens.
• To identify the most effective second- and third-line treatments for AGC based on overall survival (OS).

Main Methods:

• Systematic literature review of phase III RCTs.
• Bayesian network meta-analysis with a random-effects model.
• Overall survival (OS) as the primary outcome measure.

Main Results:

• Twenty phase III RCTs were included in the analysis.
• For second-line treatment, olaparib plus paclitaxel, paclitaxel plus ramucirumab, and pembrolizumab demonstrated high efficacy in terms of OS.
• Nivolumab, chemotherapy, and apatinib showed significant OS benefits compared to best supportive care in third-line treatment.

Conclusions:

• Pembrolizumab is a preferred second-line option for PD-L1-expressing AGC.
• Paclitaxel-based combinations are recommended for PD-L1-negative AGC as second-line treatment.
• Nivolumab may be the most effective third-line treatment option for AGC.