Abstract: PO0031
Baseline Urinary Protein Biomarkers as Predictors of eGFR Decline in Cancer Patients Receiving Cisplatin
Session Information
- AKI Epidemiology, Risk Factors, and Prevention: Clinical Research
October 22, 2020 | Location: On-Demand
Abstract Time: 10:00 AM - 12:00 PM
Category: Acute Kidney Injury
- 101 AKI: Epidemiology, Risk Factors, and Prevention
Authors
- Joy, Melanie S., University of Colorado, Skaggs School of Pharmacy, Cancer Center, and Division of Renal Diseases and Hypertension, Denver, Colorado, United States
- George, Blessy, Rutgers University, Ernest Mario School of Pharmacy, Piscataway, New Jersey, United States
- Hu, Yichun, University of North Carolina, Kidney Center, Chapel Hill, North Carolina, United States
- Hogan, Susan L., University of North Carolina, Kidney Center, Chapel Hill, North Carolina, United States
- Wen, Xia, Rutgers University, Ernest Mario School of Pharmacy, Piscataway, New Jersey, United States
- Aleksunes, Lauren, Rutgers University, Ernest Mario School of Pharmacy, Piscataway, New Jersey, United States
Background
Previous data from our group reported significant changes in urinary biomarkers of sub-clinical kidney injury over 10 days after receiving i.v. cisplatin. The current study evaluated the performance of single and a combination of two urinary biomarkers at the time of cisplatin initiation in predicting a reduction in eGFR.
Methods
Patients (n=57) with solid tumors receiving i.v. cisplatin (≥25 mg/m2) were enrolled in a study to characterize concentrations of 9 urinary proteins (Table). For the outcome of eGFR decline, the eGFR (MDRD equation) after the first dose and prior to the second dose was used. Statistical models used the baseline urinary biomarker concentrations as predictors. Logistic regression was used to assess Maximum Likelihood Estimates for models containing single and a combination of two urinary biomarkers for prediction of the reductions in eGFR outcome, and reported as odds ratios (OR) with 95% confidence intervals (CI). ROC curves for each model were based on the eGFR reduction outcome. Models were adjusted for age, gender, race and BMI.
Results
A single model for KIM-1 was significant (p=0.0421; OR 0.08; 95% CI 0.01, 0.91) for capturing eGFR decline according to ROC analysis (Table). The six combined models with ROC >0.70 are included in the Table. KIM-1 was a significant contributor in two models when combined with B2M or albumin, but ROC analyses demonstrated similar AUC as the single significant KIM-1 model. Although cystatin C was not significant in a single model (ROC AUC of 0.75), when combined with B2M the ROC AUC (0.77) was the best of all combined models.
Conclusion
Urinary biomarkers have emerged as tools to identify overt and sub-clinical kidney injury. However, single and double combinations of urinary proteins are insufficient to reliably predict reductions in eGFR as an ideal model outcome. Future studies must determine an improved outcome benchmark for evaluating urinary protein biomarkers.
Funding
- NIDDK Support