Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disease and shows a wide phenotype. Only patients with rapid progression (RP) are included in clinical trials or are approved to receive disease-modifying drugs. This study aims at comparing different available predictive tools in ADPKD with the Mayo classification (MC) identification of rapid progressors based on high total kidney volume (TKV) according to age.
Methods: A total of 164 ADPKD patients were recruited retrospectively from a single centre. The performance of diverse tools to identify RP defined as being in MC categories 1C-1E was assessed.
Results: A total of 118 patients were MC 1C-1E. The algorithm developed by the European Renal Association-European Dialysis and Transplant Association Working Group on Inherited Kidney Disorders/European Renal Best Practice had a low sensitivity in identifying MC 1C-1E. The sensitivity and specificity of TKV to predict RP depend on the cut-off used. A kidney length of >16.5 cm before age 45 years has high specificity but low sensitivity. Assessing the MC by ultrasonography had high levels of agreement with magnetic resonance imaging (MRI) data, especially for 1A, 1D and 1E. The estimated glomerular filtration rate (eGFR) decline was very sensitive but had low specificity. In contrast, the Predicting Renal Outcome in Polycystic Kidney Disease (PROPKD) score was very specific but had poor sensitivity. Having hypertension before 35 years of age is a good clinical predictor of MC 1C-1E. Family history can be of help in suggesting RP, but by itself it lacks sufficient sensitivity and specificity.
Conclusions: The MC by ultrasonography could be an option in hospitals with limited access to MRI as it performs well generally, and especially at the extremes of the MC, i.e. classes 1A, 1D and 1E. The eGFR decline is sensitive but not very specific when compared with the MC, whereas the PROPKD score is very specific but has low sensitivity. Integrating the different tools currently available to determine RP should facilitate the identification of rapid progressors among patients with ADPKD.
Keywords: ADPKD; Mayo classification; PROPKD; prediction; rapid progression; total kidney volume.
© The Author(s) 2021. Published by Oxford University Press on behalf of the ERA.