Evidence map›Paper›PMID 35498884›Full record

ArticleClinical kidney journal2022

Comparative analysis of tools to predict rapid progression in autosomal dominant polycystic kidney disease.

Javier Naranjo, Mónica Furlano, Ferran Torres, Jonathan Hernandez, Marc Pybus, Laia Ejarque, Christian Cordoba, Lluis Guirado, Elisabet Ars, Roser Torra

Open access · goldAbstract read
In one paragraph

Article in Clinical kidney journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Integrated Use of Autosomal Dominant Polycystic Kidney Disease Prediction Tools for Risk Prognostication.Clinical journal of the American Society of Nephrology : CJASN · 2025
    Article
  4. Article
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Javier NaranjoNephrology Department, Hospital Universitario Puerta del Mar, Cádiz, Spain.ORCID https://orcid.org/0000-0002-7004-6122
Mónica FurlanoInherited Kidney Diseases, Nephrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB-Sant Pau), Medicine Department, Universitat Autónoma de Barcelona, REDinREN, Barcelona, Spain.ORCID https://orcid.org/0000-0003-1025-3901
Ferran TorresBiostatistics Unit, Faculty of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain.
Jonathan HernandezRadiology Department, Fundació Puigvert, Barcelona, Spain.
Marc PybusMolecular Biology Laboratory, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB Sant Pau), Universitat Autónoma de Barcelona, REDinREN, Barcelona, Spain.
Laia EjarqueMolecular Biology Laboratory, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB Sant Pau), Universitat Autónoma de Barcelona, REDinREN, Barcelona, Spain.
Christian CordobaNephrology Department, Fundació Puigvert, REDinREN, IIB Sant Pau, Universitat Autónoma de Barcelona, Barcelona, Spain.
Lluis GuiradoNephrology Department, Fundació Puigvert, REDinREN, IIB Sant Pau, Universitat Autónoma de Barcelona, Barcelona, Spain.
Elisabet ArsMolecular Biology Laboratory, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB Sant Pau), Universitat Autónoma de Barcelona, REDinREN, Barcelona, Spain.
Roser TorraInherited Kidney Diseases, Nephrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB-Sant Pau), Medicine Department, Universitat Autónoma de Barcelona, REDinREN, Barcelona, Spain.ORCID https://orcid.org/0000-0001-8714-2332
Universitat Autònoma de Barcelona · ESPuigvert Foundation · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ADPKDMayo classificationpredictionPROPKDrapid progressiontotal kidney volume

Identifiers

PMID35498884
PMCPMC9050526
OpenAlexW4206072711

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.