Evidence map›Paper›PMID 33313853›Full record

ArticleNephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association2021

Urine proteomics for prediction of disease progression in patients with IgA nephropathy.

Michael Rudnicki, Justyna Siwy, Ralph Wendt, Mark Lipphardt, Michael J Koziolek, Dita Maixnerova, Björn Peters, Julia Kerschbaum, Johannes Leierer, Michaela Neprasova and 10 more

Open access · hybridAbstract readMulticenter Study
In one paragraph

Article in Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
7.4field-weighted citation impact, top 2% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

  1. Pooled it
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  17. Urinary peptide analysis to predict the response to blood pressure medication.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article
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  20. Urinary peptidomic liquid biopsy for non-invasive differential diagnosis of chronic kidney disease.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2024
    Article
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

20 authors at 9 institutions in 7 countries.

Michael RudnickiDepartment of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria.
Justyna SiwyMosaiques Diagnostics GmbH, Hannover, Germany.
Ralph WendtDivision of Nephrology and KfH Renal Unit, Hospital St Georg, Leipzig, Germany.
Mark LipphardtDepartment of Nephrology and Rheumatology, University Medical Centre Göttingen, Göttingen, Germany.
Michael J KoziolekDepartment of Nephrology and Rheumatology, University Medical Centre Göttingen, Göttingen, Germany.
Dita MaixnerovaDepartment of Nephrology, 1st School of Medicine and General University Hospital, Charles University, Prague, Czech Republic.
Björn PetersDepartment of Nephrology, Skaraborg Hospital, Skövde, Sweden.
Julia KerschbaumDepartment of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria.
Johannes LeiererDepartment of Internal Medicine IV, Nephrology and Hypertension, Medical University Innsbruck, Innsbruck, Austria.
Michaela NeprasovaDepartment of Nephrology, 1st School of Medicine and General University Hospital, Charles University, Prague, Czech Republic.
Miroslaw BanasikDepartment of Nephrology and Transplantation Medicine, Wroclaw Medical University, Wroclaw, Poland.
Ana Belen SanzResearch Health Institute, Fundación Jiménez Díaz University, Madrid, Spain.
Maria Vanessa Perez-GomezResearch Health Institute, Fundación Jiménez Díaz University, Madrid, Spain.ORCID 0000-0003-4558-5236
Alberto OrtizResearch Health Institute, Fundación Jiménez Díaz University, Madrid, Spain.
Bernd StegmayrDepartment of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Vladimir TesarDepartment of Nephrology, 1st School of Medicine and General University Hospital, Charles University, Prague, Czech Republic.
Harald MischakMosaiques Diagnostics GmbH, Hannover, Germany.
Joachim BeigeDivision of Nephrology and KfH Renal Unit, Hospital St Georg, Leipzig, Germany.ORCID 0000-0002-1907-825X
Heather N ReichDepartment of Medicine, Division of Nephrology, University Health Network, University of Toronto, Toronto, Canada.
PERSTIGAN working group
Hospital Universitario Fundación Jiménez Díaz · ESInnsbruck Medical University · ATKlinikum St. Georg · DEMosaiques Diagnostics and Therapeutics (Germany) · DECharles University · CZSkaraborg Hospital · SEUniversity Health Network · CAUmeå University · SEWroclaw Medical University · PL

Funding

CIHR
6 · The paper itself

Abstract

backgroundRisk of kidney function decline in immunoglobulin A (IgA) nephropathy (IgAN) is significant and may not be predicted by available clinical and histological tools. To serve this unmet need, we aimed at developing a urinary biomarker-based algorithm that predicts rapid disease progression in IgAN, thus enabling a personalized risk stratification.

methodsIn this multicentre study, urine samples were collected in 209 patients with biopsy-proven IgAN. Progression was defined by tertiles of the annual change of estimated glomerular filtration rate (eGFR) during follow-up. Urine samples were analysed using capillary electrophoresis coupled mass spectrometry. The area under the receiver operating characteristic curve (AUC) was used to evaluate the risk prediction models.

resultsOf the 209 patients, 64% were male. Mean age was 42 years, mean eGFR was 63 mL/min/1.73 m2 and median proteinuria was 1.2 g/day. We identified 237 urine peptides showing significant difference in abundance according to the tertile of eGFR change. These included fragments of apolipoprotein C-III, alpha-1 antitrypsin, different collagens, fibrinogen alpha and beta, titin, haemoglobin subunits, sodium/potassium-transporting ATPase subunit gamma, uromodulin, mucin-2, fractalkine, polymeric Ig receptor and insulin. An algorithm based on these protein fragments (IgAN237) showed a significant added value for the prediction of IgAN progression [AUC 0.89; 95% confidence interval (CI) 0.83-0.95], as compared with the clinical parameters (age, gender, proteinuria, eGFR and mean arterial pressure) alone (0.72; 95% CI 0.64-0.81).

conclusionsA urinary peptide classifier predicts progressive loss of kidney function in patients with IgAN significantly better than clinical parameters alone.

Indexed as

Glomerulonephritis, IGAAdultDisease ProgressionGlomerular Filtration RateHumansMaleProteinuriaProteomicsbiomarkerglomerulonephritisIgANprogressionurine proteomics

Identifiers

PMID33313853
PMCPMC8719618
OpenAlexW3033838163

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.