Evidence map›Paper›PMID 38245210›Full record

ArticleKidney international2024

Rationale and design of the Nephrotic Syndrome Study Network (NEPTUNE) Match in glomerular diseases: designing the right trial for the right patient, today.

Howard Trachtman, Hailey Desmond, Amanda L Williams, Laura H Mariani, Sean Eddy, Wenjun Ju, Laura Barisoni, Heather K Ascani, Wendy R Uhlmann, Cathie Spino and 10 more

Open access · hybridAbstract read
In one paragraph

Article in Kidney international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
7.5field-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

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
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  3. Terms of Engagement.Clinical journal of the American Society of Nephrology : CJASN · 2025
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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

20 authors at 5 institutions in 1 country.

Howard TrachtmanDivision of Nephrology, Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA.
Hailey DesmondDivision of Nephrology, Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA.
Amanda L WilliamsDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Laura H MarianiDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Sean EddyDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Wenjun JuDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
Laura BarisoniDepartment of Pathology and Medicine, Duke University, Durham, North Carolina, USA.
Heather K AscaniDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Wendy R UhlmannDepartment of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA; Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA.
Cathie SpinoStatistical Analysis, Biomedical and Educational Research Unit, University of Michigan, Ann Arbor, Michigan, USA.
Lawrence B HolzmanRenal-Electrolyte and Hypertension Division, Department of Internal Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA.
John R SedorDepartment of Kidney Medicine, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio, USA; Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Crystal GadegbekuDepartment of Kidney Medicine, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Lalita SubramanianDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Chrysta C LienczewskiDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Tina ManieriDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Scott J RobertsDepartment of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.
Debbie S GipsonDivision of Nephrology, Department of Pediatrics, University of Michigan, Ann Arbor, Michigan, USA.
Matthias KretzlerDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA. Electronic address: kretzler@umich.edu.
NEPTUNE investigators
University of Michigan · USCleveland Clinic · USDuke University · USUniversity of Pennsylvania · USMichigan Department of Health and Human Services · US

Funding

The Impact of COVID-19 on People Living with Rare Diseases and Their FamiliesU2CTR002818 · NCATS · CINCINNATI CHILDRENS HOSP MED CTR · PI Maurizio Macaluso, Michael Wagner · 2019 to 2026
$51.2M
Training Program in Clinical & Translationa Research in Human Glomerular DiseaseU54DK083912 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KRETZLER, MATTHIAS · 2009 to 2023
$20.3M
Primary Outcomes in Glomerulonephritis Study (PROGRESS)UM1DK100846 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI HOLZMAN, LAWRENCE B. · 2013 to 2018
$5.8M
NCATS NIH HHS U2C TR002818NIDDK NIH HHS U54 DK083912NIDDK NIH HHS UM1 DK100846
6 · The paper itself

Abstract

Glomerular diseases are classified using a descriptive taxonomy that is not reflective of the heterogeneous underlying molecular drivers. This limits not only diagnostic and therapeutic patient management, but also impacts clinical trials evaluating targeted interventions. The Nephrotic Syndrome Study Network (NEPTUNE) is poised to address these challenges. The study has enrolled >850 pediatric and adult patients with proteinuric glomerular diseases who have contributed to deep clinical, histologic, genetic, and molecular profiles linked to long-term outcomes. The NEPTUNE Knowledge Network, comprising combined, multiscalar data sets, captures each participant's molecular disease processes at the time of kidney biopsy. In this editorial, we describe the design and implementation of NEPTUNE Match, which bridges a basic science discovery pipeline with targeted clinical trials. Noninvasive biomarkers have been developed for real-time pathway analyses. A Molecular Nephrology Board reviews the pathway maps together with clinical, laboratory, and histopathologic data assembled for each patient to compile a Match report that estimates the fit between the specific molecular disease pathway(s) identified in an individual patient and proposed clinical trials. The NEPTUNE Match report is communicated using established protocols to the patient and the attending nephrologist for use in their selection of available clinical trials. NEPTUNE Match represents the first application of precision medicine in nephrology with the aim of developing targeted therapies and providing the right medication for each patient with primary glomerular disease.

Indexed as

Kidney DiseasesNephrotic SyndromeAdultBiomarkersChildClinical Trials as TopicHumansKidney GlomerulusBiomarkersclinical trialsdisease pathwaypatient communication

Identifiers

PMID38245210
PMCPMC11090626
OpenAlexW4391002517

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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 OpenQuestion graph.