Gembillo G, Sessa C, Santoro D. Cystatin C-based equations: Enhancing accuracy in kidney function tests for type 2 diabetes. World J Nephrol 2025; 14(3): 102756 [PMID: 41024961 DOI: 10.5527/wjn.v14.i3.102756]
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05319135
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September 24, 2025, 18:49
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World Journal of Nephrology. 2025; 14(3): 102756. DOI: 10.5527/wjn.v14.i3.102756
Dear Editor,
Diabetic kidney disease (DKD) remains the leading cause of chronic kidney disease (CKD) and end-stage kidney disease (ESKD) worldwide, I read with great interest this topic, which highlights the role of cystatin C–based equations in improving the accuracy of renal function assessment in patients with type 2 diabetes mellitus (T2DM).
Strengths of the article:
The paper clearly underscores the limitations of creatinine-based estimated glomerular filtration rate (eGFR), especially in diabetic patients where muscle mass may distort results.
The authors’ emphasis on cystatin C as a more reliable biomarker, along with advocacy for combined creatinine–cystatin C equations as recommended by KDIGO, reflects current evidence-based practice.
The discussion on integrating cystatin C into precision medicine approaches, particularly alongside artificial intelligence (AI), is forward-thinking and aligns with global efforts toward individualized care.
While cystatin C reduces creatinine-related biases, factors such as thyroid dysfunction, systemic inflammation, and corticosteroid use may also influence its levels.
Table 1 offers a concise and summary of the main methods for estimating GFR.
Points for further consideration:
Role of renal biopsy: The article notes the underutilization of renal biopsy in DKD diagnosis. Expanding on how cystatin C may complement, but not replace, biopsy in complex diagnostic scenarios could be useful.
Outcome validation: Future studies should demonstrate whether cystatin C–based eGFR translates into better clinical outcomes (e.g., reduced DKD progression, lower cardiovascular events, delayed dialysis initiation) beyond improved diagnostic precision.
AI applications: The proposed integration of cystatin C into AI-driven models is exciting. Specific examples or pilot studies where biomarker–AI integration has improved predictive accuracy would strengthen this vision.
Conclusion:
This editorial makes an important contribution by advocating for more accurate renal assessment in patients with T2DM. The call for cystatin C integration, particularly in high-risk populations, is well-justified and aligned with evolving guidelines. Broader validation, cost-effectiveness studies, and exploration of biomarker–AI synergy will be critical steps toward translating these insights into standard nephrology practice.
Sincerely,
[Rabie M Ibrahim, MD in urology]
Urology department, Faculty of medicine
Beni-Suef University, Beni-Suef, Egypt.