The Effect of GLP-1 Receptor Agonists on Outcomes in Metastatic Renal Cell Carcinoma Patients Undergoing Immune Checkpoint Inhibitor Therapy

Source: 2025 ASCO Annual Meeting. May 30 – June 2, 2025; Chicago, IL. Abstract 4559.

Clinical Bottom Line

GLP-1 receptor agonists in patients with metastatic renal cell carcinoma (mRCC) and type 2 diabetes receiving immune checkpoint inhibitor (ICI) therapy demonstrated 51% lower mortality risk (HR 0.49) and significantly reduced immune-related adverse events. This retrospective analysis of 994 propensity-matched patients suggests GLP-1 agonists may enhance ICI tolerability without compromising efficacy.

Study Design & Population

  • Retrospective cohort study using TriNetX database (120 million US patients, 2012-2024)
  • 994 patients after 1:1 propensity score matching (497 per group)
  • Inclusion criteria: Age ≥18, type 2 diabetes mellitus (T2DM), mRCC, receiving ICI therapy
  • Demographics: 66% male, 77% White, mean age ~65 years
  • Matched variables: Age, sex, race, ICI type, comorbidities, diabetic medications, staging

Key Findings

  • Overall survival: 51% mortality reduction with GLP-1 agonists (HR 0.49, 95% CI: 0.37-0.64)
  • Pneumonitis: 39% risk reduction (HR 0.61, 95% CI: 0.43-0.85)
  • Hematological complications: 22% risk reduction (HR 0.78, 95% CI: 0.64-0.95)
  • Renal complications: 33% risk reduction (HR 0.67, 95% CI: 0.54-0.84)
  • Major adverse cardiovascular events (MACE): No significant difference between groups
  • Other immune-related adverse events: No significant difference

Clinical Implications

  • First real-world evidence suggesting GLP-1 agonists may improve ICI outcomes in mRCC patients with diabetes
  • May inform treatment decisions for diabetic mRCC patients already candidates for GLP-1 therapy
  • Does not establish causation – underlying mechanisms remain unclear and require prospective validation

Limitations

  • Retrospective design limits causal inference despite propensity matching
  • Database study with potential coding errors and unmeasured confounders
  • Single-institution bias despite multi-institutional database
  • No mechanistic data to explain observed protective effects
  • Limited follow-up to 1 year may miss long-term outcomes

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