Evidence map›Paper›PMID 28219345›Full record

SynthesisBMC nephrology2017

Biomarkers for the detection of renal fibrosis and prediction of renal outcomes: a systematic review.

Sherry G Mansour, Jeremy Puthumana, Steven G Coca, Mark Gentry, Chirag R Parikh

Open access · goldAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC nephrology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 1 pooled it
5.1field-weighted citation impact, top 4% 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

70 citing papers in PubMed, 1 synthesis or guideline pooled it, 112 citations in OpenAlex.

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  5. Kidney Elastography in Adult Nephrology: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026
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10 more citing papers are in PubMed but not listed here.

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

5 authors at 2 institutions in 1 country.

Sherry G MansourProgram of Applied Translational Research, Department of Medicine, Yale University, School of Medicine, New Haven, CT, USA.
Jeremy PuthumanaProgram of Applied Translational Research, Department of Medicine, Yale University, School of Medicine, New Haven, CT, USA.
Steven G CocaDepartment of Medicine, Division of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Mark GentryHarvey Cushing/John Hay Whitney Medical Library, Yale University, New Haven, CT, USA.
Chirag R ParikhProgram of Applied Translational Research, Department of Medicine, Yale University, School of Medicine, New Haven, CT, USA. chirag.parikh@yale.edu.
Yale University · USIcahn School of Medicine at Mount Sinai · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
PATHOPHYSIOLOGY OF ACUTE AND CHRONIC RENAL DISEASET32DK007276 · NIDDK · YALE UNIVERSITY · PI ARONSON, PETER S., CANTLEY, LLOYD G · 1986 to 2022
$9.3M
NCATS NIH HHS UL1 TR001863NIDDK NIH HHS T32 DK007276
6 · The paper itself

Abstract

backgroundFibrosis is the unifying pathway leading to chronic kidney disease. Identifying biomarkers of fibrosis may help predict disease progression.

methodsWe performed a systematic review to evaluate the reliability of blood and urine biomarkers in identifying fibrosis on biopsy as well as predicting renal outcomes. Using MEDLINE and EMBASE, a two-stage search strategy was implemented. Stage I identified a library of biomarkers correlating with fibrosis on biopsy. Stage II evaluated the association between biomarkers identified in stage I, and renal outcomes. Only biomarkers with moderate positive correlation with fibrosis (r > 0.40) or acceptable area under the curve (AUC >0.65) advanced to stage II.

resultsStage I identified 17 studies and 14 biomarkers. Five biomarkers met criteria to advance to stage II, but only three were independently associated with renal outcomes. Transforming growth factor β (TGF-β) correlated with fibrosis (r = 0.60), and was associated with 1.7-3.9 times the risk of worsening renal function in 426 patients. Monocyte chemoattractant protein-1 (MCP-1) diagnosed fibrosis with AUC of 0.66 and was associated with 2.3-11.0 times the risk of worsening renal function in 596 patients. Matrix metalloproteinase-2 (MMP-2) correlated with fibrosis (r = 0.41), and was associated with 2.5 times the risk of worsening renal function.

conclusionsGiven the heterogeneity of the data due to diverse patient populations along with differing renal outcomes, a meta-analysis could not be conducted. Nonetheless we can conclude from the published data that TGF-β, MCP-1 and MMP-2 may identify patients at risk for renal fibrosis and hence worse renal outcomes.

Indexed as

Area Under CurveBiomarkersChemokine CCL2Disease ProgressionFibrosisHumansKidneyKidney DiseasesMatrix Metalloproteinase 2PrognosisReproducibility of ResultsTransforming Growth Factor betaBiomarkersCCL2 protein, humanChemokine CCL2Matrix Metalloproteinase 2MMP2 protein, humanTransforming Growth Factor betaBiomarkersChronic kidney diseaseFibrosisOutcomesRenal biopsyRenal disease progression

Identifiers

PMID28219345
PMCPMC5319065
OpenAlexW2590708408

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.