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Published on: June 23, 2015
Validation of Combining Total Kidney Volume and Kidney Failure Risk Equation in Autosomal Dominant Polycystic Kidney
Micheli Bevilacqua1,2, Meijiao Guan2, Alexandra Romann2
1Division of Nephrology, University of British Columbia, British Columbia, Canada.
Insights
Adding the kidney failure risk equation (KFRE) to the Mayo Imaging Classification (MIC) improves risk prediction for autosomal dominant polycystic kidney disease (ADPKD) patients with reduced kidney function. This combined approach enhances prognostication for ADPKD progression.
Area of Science:
- Nephrology
- Medical Imaging
- Biostatistics
Background:
- Autosomal dominant polycystic kidney disease (ADPKD) management relies on prognostication tools like Mayo Imaging Classification (MIC).
- Further risk stratification beyond MIC is often necessary for effective ADPKD patient management.
- The kidney failure risk equation (KFRE) is validated for chronic kidney disease (CKD) but its utility in ADPKD alongside MIC is not well-established.
Purpose of the Study:
- To evaluate the impact of incorporating the kidney failure risk equation (KFRE) into risk prediction models for autosomal dominant polycystic kidney disease (ADPKD).
- To assess whether combining KFRE with the Mayo Imaging Classification (MIC) improves prognostic accuracy in ADPKD patients.
Main Methods:
- Retrospective observational study including adult ADPKD patients with computed tomography (CT) or magnetic resonance imaging (MRI) derived total kidney volume (TKV).
- Analysis focused on patients with baseline estimated glomerular filtration rate (eGFR) < 60 ml/min per 1.73 m².
- Predictive performance of models incorporating MIC, eGFR, and KFRE was evaluated using the composite outcome of kidney replacement therapy initiation or eGFR decline of 40%.
Main Results:
- In patients with eGFR < 60 ml/min per 1.73 m², models including KFRE and MIC demonstrated superior predictive performance compared to MIC alone.
- The adjusted model with age, sex, tolvaptan, KFRE, and MIC showed the best performance across 1, 3, and 5 years.
- Combining MIC value and KFRE also significantly improved risk prediction compared to MIC alone.
Conclusions:
- The kidney failure risk equation (KFRE) enhances risk prediction when used in conjunction with the Mayo Imaging Classification (MIC) in ADPKD patients.
- Combining KFRE and MIC offers improved prognostic accuracy for ADPKD patients with reduced kidney function (eGFR < 60 ml/min per 1.73 m²).
- These findings support the combined utilization of KFRE and MIC for better risk stratification in ADPKD management.
Introduction:
Total kidney volume (TKV) interpreted via the Mayo Imaging Classification (MIC) is the recommended prognostication tool in autosomal dominant polycystic kidney disease (ADPKD), but further risk stratification is often needed. The kidney failure risk equation (KFRE) is validated in chronic kidney disease (CKD) of diverse etiologies, but its use in patients with ADPKD already assessed via the MIC is unclear. This study evaluated the impact of adding KFRE to MIC.
Methods:
Adults with ADPKD with ≥1 computed tomography (CT) or magnetic resonance imaging (MRI) derived TKV available between January 2015 and January 2023 were included in this retrospective observational study. The predictive performance of models including the MIC value, baseline estimated glomerular filtration rate (eGFR), and 5-year KFRE score, and fully adjusted models were examined using the composite outcome of kidney replacement therapy initiation or eGFR decline 40%. The primary analysis was in patients with eGFR < 60 ml/min per 1.73 m2.
Results:
In the eGFR < 60 ml/min per 1.73 m2 group, compared with the model showing MIC value alone, the adjusted model including age, sex, tolvaptan, KFRE, and MIC value demonstrated the best performance (Akaike information criterion [AIC] = 631, ΔC-statistic = 0.47, 0.28, and 0.27 at 1, 3, and 5 years respectively), followed closely by the combination of MIC value and KFRE (AIC = 641, ΔC-statistic = 0.47, 0.26, and 0.26), KFRE alone (AIC = 642, ΔC-statistic = 0.47, 0.26, and 0.28) at 1, 3, and 5 years respectively.
Conclusion:
In the cohort with a baseline eGFR < 60 ml/min per 1.73 m2, use of the KFRE in addition to the MIC improved risk prediction, supporting the utilization of these tools together in ADPKD.
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