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Kidney Week

Abstract: PO0777

Clinical and Histological Predictors of Renal Survival in Patients with Biopsy-Proven Diabetic Nephropathy

Session Information

Category: Diabetic Kidney Disease

  • 602 Diabetic Kidney Disease: Clinical

Authors

  • Zhou, Ting, The Sixth Hospital of Shanghai Affiliated to Shanghai Jiaotong University, Shanghai, China
  • Wang, Yiyun, The Sixth Hospital of Shanghai Affiliated to Shanghai Jiaotong University, Shanghai, China
  • Shen, Li, The Sixth Hospital of Shanghai Affiliated to Shanghai Jiaotong University, Shanghai, China
  • Li, Ze, The Sixth Hospital of Shanghai Affiliated to Shanghai Jiaotong University, Shanghai, China
  • Jia, Junjie, The Sixth Hospital of Shanghai Affiliated to Shanghai Jiaotong University, Shanghai, China
  • Wang, Niansong, The Sixth Hospital of Shanghai Affiliated to Shanghai Jiaotong University, Shanghai, China
  • Fan, Ying, The Sixth Hospital of Shanghai Affiliated to Shanghai Jiaotong University, Shanghai, China
Background

Diabetic nephropathy (DN) is one of the most important complications of diabetes and has become the leading cause of end stage renal disease (ESRD). However, clinical and pathological factors alone can't reliably predict renal survival in patients with biopsy-proven DN, potentially resulting in the delayed treatment of patients at a high risk of renal failure. Therefore, this study sought to develop and validate a predictive model incorporating both clinical and pathological markers to predict renal outcomes in patients with biopsy-proven DN.

Methods

A predictive nomogram was developed based upon data pertaining to 194 patients with biopsy-proven DN. The prognostic relevance of individual clinicopathological variables was assessed through univariate and multivariate Cox regression analyses. A prognostic nomogram was then developed and validated based upon concordance (C)-index values, area under curve (AUC) and calibration curves. Internal validation was conducted through bootstrap resampling, while the clinical utility of this model was assessed via a decision curve analysis (DCA) approach.

Results

Nephrotic-range 24-hour proteinuria, late-stage chronic kidney disease (CKD stage 3-4), glomerular classification III-IV, and an IFTA score 2-3 were all identified as independent predictors of poor renal outcomes in DN patients and were incorporated into our final nomogram. Calibration curves revealed good agreement between predicted and actual 3- and 5-year renal survival in DN patients, while the C-index value for this nomogram was 0.845 (95% CI 0.826–0.864) and the 3- and 5-Year AUC were 0.933 (95%CI 0.898-0.968), 0.923 (95%CI 0.886-0.960). DCA analysis revealed that our nomogram was superior to models based solely upon clinical indicators.

Conclusion

A predictive nomogram incorporating clinical and pathological indicators was developed and validated for the prediction of renal survival outcomes in patients with biopsy-proven DN. This tool will be of value to clinicians, as it can serve as an easy-to-use and reliable tool for physicians to guide patient management based on individualized risk in order to improve patient outcomes.