Role of immune checkpoint inhibitor-based therapies for metastatic renal cell carcinoma in the first-line setting: A Bayesian network analysis.

BACKGROUND

Several novel immune checkpoint inhibitor (ICI)-based treatments exhibited promising survival benefits for metastatic renal cell carcinoma (mRCC), yet there is no current guidance regarding the optimum first-line regimen. We performed this network analysis to compare the efficacy and safety of all available treatments for mRCC.

METHODS

A systematic search of literature was conducted up to April 30, 2019, and the analysis was done on a Bayesian fixed-effect model.

FINDINGS

Twenty-five randomized clinical trials (RCTs) involving 13,010 patients were included in this study. The results showed that for overall survival, pembrolizumab plus axitinib (hazard ratio [HR]: 0.53; 95% credible interval [CrI]: 0.38-0.73) and nivolumab plus ipilimumab (HR: 0.63; 95% CrI: 0.50-0.79) were significantly more effective than sunitinib, and pembrolizumab plus axitinib was probably (68%) to be the best choice. For progression-free survival, cabozantinib (HR: 0.66; 95% CrI: 0.46-0.94), pembrolizumab plus axitinib (HR: 0.69; 95% CrI: 0.57-0.84), avelumab plus axitinib (HR: 0.69; 95% CrI: 0.56-0.85), nivolumab plus ipilimumab (HR: 0.82; 95% CrI: 0.68-0.99), and atezolizumab plus bevacizumab (HR: 0.86; 95% CrI: 0.74-0.99) were statistically superior to sunitinib, and cabozantinib was likely (43%) to be the preferred options. Nivolumab plus ipilimumab (OR: 0.50; 95% CrI: 0.28-0.84), and atezolizumab plus bevacizumab (OR: 0.56; 95% CrI: 0.36-0.83) were associated with significantly lower rate of high-grade adverse events than sunitinib.

INTERPRETATION

Our findings demonstrate that pembrolizumab plus axitinib might be the best treatment for mRCC, while nivolumab plus ipilimumab has the most favorable balance between efficacy and acceptability, and may provide new guidance to make treatment decisions. FUND: This research was supported by the Henan Provincial Scientific and Technological Research Project (Grant No. 192102310036).