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Mayo classification by ultrasound useful in predicting rapid progression of rare kidney disease

Clinical Kidney Journal
Reuters Health - 10/01/2022 - The Mayo classification (MC) of autosomal dominant polycystic kidney disease (ADPKD) based on ultrasound rather than magnetic resonance imaging (MRI) findings performs well, especially at the extremes of the MC (classes 1A, 1D, and 1E), and could be an option in hospitals with limited access to MRI, report clinicians from Spain.

ADPKD is the most common cause of inherited kidney disease and shows a broad phenotypic spectrum. Identifying patients at high risk for rapid progression has become increasingly important given the availability of new treatments, such as tolvaptan, recently approved for rapidly progressing ADPKD.

There are several tools to help predict disease progression in ADPKD, but no consensus on the optimal prediction model for the identification of rapid progression, note Dr. Javier Naranjo of Puerta del Mar University Hospital, in Cadiz, and colleagues in the Clinical Kidney Journal.

They assessed the performance of the following tools to identify rapid progression (RP) of ADPKD: the decision algorithm from the European Renal Association-European Dialysis and Transplant Association (ERA-EDTA) Working Groups of Inherited Kidney Disorders and European Renal Best Practice (ERA-EDTA WGIKD/ERBP); total kidney volume; kidney length > 16.5 cm plus age younger than 45; MC by ultrasound (US); age plus estimated glomerular filtration rate (eGFR); and the Predicting Renal Outcome in Polycystic Kidney Disease (PROPKD) score.

The researchers defined RP as MC categories 1C, 1D or 1E, using MC by MRI, the most widely accepted prediction tool, as the gold standard. Among 164 ADPKD patients, 118 were in categories 1C to 1E.

All imaging prediction tools had more agreement with MC than the other prediction tools, the analysis showed.

Assessing the MC by US had "high levels" of agreement with MC MRI data, especially for 1A, 1D and 1E. "All patients classified as MC 1A by US corresponded to non-RP according to MC by MRI. On the other hand, all patients with MC 1D or 1E on US corresponded to RP according to MC by MRI," Dr. Naranjo and colleagues report.

"However, classification as MC 1B and 1C by US did not perform well enough to discriminate between RP and non-RP. In hospitals where access to MRI is complicated, MC by US could be used to guide the decision to order an MRI to assess disease progression," they note.

As for the other prediction tools, the ERA-EDTA WGIKD/ERBP algorithm had a low sensitivity in identifying MC 1C-1E; sensitivity and specificity of total kidney volume to predict RP depended on the cut-off used; and kidney length >16.5 cm before age 45 years had high specificity but low sensitivity.

eGFR decline was very sensitive for RP but had low specificity. However, indexing eGFR by age could represent a simple prognostic tool, the researchers say.

Stratification of patients based on age and eGFR proved to be "very specific" and it has the advantage of always being available but also the limitation of not being useful in young patients with preserved kidney function. However, larger studies are needed to define the eGFR decline threshold that performs best in predicting RP, the researchers say.

The PROPKD score for predicting RP was also very specific but had poor sensitivity.

"The PROPKD score has been proved to be an excellent predictor of RP. In our cohort, 95% of patients who had a PROPKD score >6 were considered to have RP according to MC, this being the most specific but least sensitive non-imaging prediction tool," the researchers report.

"Interestingly," they write, hypertension present before age 35 years was a good solo clinical predictor of MC 1C-1E. "This single item of clinical data could draw attention to a high possibility of RP," they say.

Summing up, the researchers say, "Probably, the task of prediction cannot be absolutely entrusted to a single tool, but the common sense of the nephrologist in conjunction with use of several of the above-mentioned prediction tools, as well as new ones based mostly on biomarkers, will help to identify the subpopulation of ADPKD patients who will experience RP."

The study had no commercial funding and the authors have no relevant conflicts of interest.

SOURCE: https://bit.ly/3mOMPDm Clinical Kidney Journal, online December 28, 2021.

By Reuters Staff

© 2023 The Author(s). Published by Medicom Medical Publishers.
User license: Creative Commons Attribution – NonCommercial (CC BY-NC 4.0)

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