Evidence map›Paper›PMID 28664406›Full record

ReviewPflugers Archiv : European journal of physiology2017

Renal biopsy-driven molecular target identification in glomerular disease.

Maja T Lindenmeyer, Matthias Kretzler

Abstract readReview
PubMed Publisher
In one paragraph

Review in Pflugers Archiv : European journal of physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Advances in Renal Cell Imaging.Seminars in nephrology · 2018
    Review
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

2 authors.

Maja T LindenmeyerNephrological Center, Medical Clinic and Policlinic IV, University of Munich, Munich, Germany.
Matthias KretzlerDepartment of Medicine, University of Michigan, Ann Arbor, MI, USA. kretzler@med.umich.edu.

Funding

University of Michigan O'Brien Kidney Translational Core CenterP30DK081943 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PENNATHUR, SUBRAMANIAM · 2008 to 2022
$12.9M
NIDDK NIH HHS P30 DK081943
6 · The paper itself

Abstract

Chronic kidney disease has severe impacts on the patient and represents a major burden to the health care systems worldwide. Despite an increased knowledge of pathophysiological processes involved in kidney diseases, the progress in defining novel treatment strategies has been limited. One reason is the descriptive disease categorization used in nephrology based on clinical findings or histopathological categories irrespective of potential different molecular disease mechanisms. To accelerate progress toward a targeted treatment, a definition of human disease extending from phenotypic disease classification to mechanism-based disease definitions is needed. In recent years, we have witnessed a major transition in biomedical research from a single gene research to an information rich and collaborative science. Tissue-based analysis in renal disease allows to link structure to molecular function. In our review, we introduce the concept of precision medicine in nephrology, describe several large cohort studies established for molecular analysis of kidney diseases, and highlight examples of renal biopsy-driven target identification by integrative systems biology approaches. Furthermore, we give an outlook on how the new disease definitions can be used for patient stratification in clinical trial design. Finally, we introduce the concept of an informational commons of renal precision medicine for joint analyses of large-scale data sets in renal failure.

Indexed as

Clinical Trials as TopicGlomerulonephritisHumansKidneyMolecular Diagnostic TechniquesMolecular Targeted TherapyTissue BanksBiomarkersOmics dataPrecision medicineRenal biopsySystems biology approach

Identifiers

What OpenQuestion holds

Textmetadata
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.