A Systematic Review and Meta-Analysis of the Significance of Diabetes on Kidney Cancer Outcomes and the Role of Metformin.

The effect of diabetes and metformin on renal cell carcinoma (RCC) outcomes has not been well established.

A systematic review and meta-analysis were performed to investigate the influence of diabetes on various outcome measures in renal cell carcinoma (RCC). We have also investigated the effect of metformin as a potential strategy to improve prognosis. A computerized systematic search of Medline, Embase, ProQuest, PubMed, and Google Scholar for literature was performed between its inception and September 2024 according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines.

A total of 41 published studies were included in the analysis. Patients without diabetes were associated with improved RCC-specific survival (hazard ratios [HR] 1.38, 95% confidence intervals [CI], 1.23-1.55), progression-free survival (HR 1.61, 95% CI, 1.26-2.07), and overall survival (HR 1.51, 95% CI, 1.34-1.70) compared to patients with diabetes. Among patients with diabetes, metformin use was associated with more favorable survival outcomes; however, these findings are observational and are subject to time-related biases. Key limitations included observational study design, substantial heterogeneity, limited reporting on diabetes severity and glycemic control, and a high likelihood of time-related and indication biases, including immortal time bias.

This largest systematic review demonstrates that diabetes mellitus is associated with worse RCC outcomes across all outcomes. Further research is warranted to confirm its significance on RCC prognosis. Although metformin use was associated with improved outcomes, this association is likely substantially affected by time-related biases, including immortal time bias. These findings should be considered hypothesis-generating, and metformin should not be considered prognostic or therapeutic based on current evidence. Randomized controlled trials or new-user cohort designs with time-dependent exposure modeling are essential before any clinical recommendations can be made.

Clinical genitourinary cancer. 2026 Feb 20 [Epub ahead of print]

Lawrence H Kim, Jeffrey Y Tai, Thomas Li, Raymond Hayler, Henry Wang, Howard M Lau, Henry Pleass, Visalini Nair-Shalliker, David Smith, Manish I Patel

Department of Urology, Westmead Hospital, Sydney, New South Wales, Australia; Specialty of Surgery, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia. Electronic address: ., Department of Radiology, Mater Hospital, North Sydney, New South Wales, Australia., Department of Urology, Westmead Hospital, Sydney, New South Wales, Australia; Specialty of Surgery, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia., Specialty of Surgery, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia; Department of Surgery, Westmead Hospital, Sydney, New South Wales, Australia., Department of Urology, Westmead Hospital, Sydney, New South Wales, Australia., Daffodil Centre, Sydney University, A Joint Venture With Cancer Council New South Wales, Sydney, New South Wales, Australia; Department of Clinical Medicine, Macquarie University, North Sydney, New South Wales, Australia., Daffodil Centre, Sydney University, A Joint Venture With Cancer Council New South Wales, Sydney, New South Wales, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.