Kidney Week

Abstract: TH-PO418

Validation of the Mayo Imaging Classification System for Predicting Renal Outcome in ADPKD

Session Information

• Genetic Diseases: Cystic - Therapeutic Investigations and Prognosis
  November 02, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Genetic Diseases of the Kidneys

• 1201 Genetic Diseases of the Kidneys: Cystic

Authors

• Bais, Thomas, Universitair Medisch Centrum Groningen, Groningen, Groningen, Netherlands

Thomas Bais,

• Geertsema, Paul, Universitair Medisch Centrum Groningen, Groningen, Groningen, Netherlands

Paul Geertsema,

• Knol, Martine Geke Evelien, Universitair Medisch Centrum Groningen, Groningen, Groningen, Netherlands

Martine Geke Evelien Knol,

• van Gastel, Maatje D.A., Universitair Medisch Centrum Groningen, Groningen, Groningen, Netherlands

Maatje D.A. van Gastel,

• Meijer, Esther, Universitair Medisch Centrum Groningen, Groningen, Groningen, Netherlands

Esther Meijer,

• Gansevoort, Ron T., Universitair Medisch Centrum Groningen, Groningen, Groningen, Netherlands

Ron T. Gansevoort,

Group or Team Name

• On Behalf of the DIPAK Consortium.

Background

The Mayo Imaging Classification is used to predict the rate of disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD). The goal of this study was to validate its ability to predict renal prognosis in a large cohort of patients with ADPKD.

Methods

Included were ADPKD patients with ‘typical’ disease, at least one height-adjusted total kidney volume (HtTKV) measurement, ≥3 eGFR estimates and ≥1 year follow-up. The stability of the classification, kidney growth rate and eGFR decline rate were calculated for each Mayo HtTKV class at various timepoints. The observed eGFR decline rate at these timepoints were compared to the values predicted by the Mayo Clinic formula for future eGFR. Kaplan-Meier survival analysis was performed to predict end stage kidney disease (ESKD) using Mayo HtTKV class as a predictor variable.

Results

We included 619 patients with a mean age of 47 ± 11 years and an eGFR of 63 ± 25 ml/min/1.73m² at baseline. The majority of patients (70.0 - 88.9%) remained in their baseline Mayo HtTKV class after 6 years of follow-up. The mean eGFR decline and TKV growth rates during a mean follow-up duration of 5.0 ± 2.2 years were -3.26 ± 2.49 ml/min/1.73m²/year and 5.29 ± 3.97 %/year, respectively. There was considerable variation in kidney growth and eGFR decline rates within each Mayo HtTKV class. The observed eGFR decline at follow-up was not significantly different from the predicted values for Mayo HtTKV classes 1A, 1B, 1C and 1D. However, the observed eGFR decline of Mayo HtTKV class 1E was less than predicted. This was also observed in patients aged <40 years at baseline and in patients with PKD2 mutations. The classification was a strong predictor for ESKD.

Conclusion

The Mayo Imaging Classification demonstrates acceptable stability over time and is predictive of the rate of eGFR decline albeit with wide inter-individual variations. The ability to predict future eGFR decline for individual patients might be improved by developing equations that include additional prognostic covariates.