Evidence map›Paper›PMID 29520581›Full record

ReviewDiabetologia2018

Biomarkers of diabetic kidney disease.

Helen M Colhoun, M Loredana Marcovecchio

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Diabetologia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 158 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
158citing papers in PubMed, 3 pooled it
–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

158 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Effects of Selonsertib in Patients with Diabetic Kidney Disease.Journal of the American Society of Nephrology : JASN · 2019
    Trial
  6. Review
  7. Article
  8. Article
  9. Diabetic kidney disease, biomarkers, and finerenone.Diabetes, obesity & metabolism · 2026
    Review
  10. Spatial transcriptomics identifies IL-32 as a lipid droplet-associated cytokine linked to tubular injury in human diabetic kidney disease.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Observational
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

98 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

2 authors.

Helen M ColhounMRC Institute of Genetics & Molecular Medicine, The University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK. Helen.colhoun@igmm.ed.ac.uk.
M Loredana MarcovecchioDepartment of Paediatrics, University of Cambridge, Cambridge, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in diabetes. The quest for both prognostic and surrogate endpoint biomarkers for advanced DKD and end-stage renal disease has received major investment and interest in recent years. However, at present no novel biomarkers are in routine use in the clinic or in trials. This review focuses on the current status of prognostic biomarkers. First, we emphasise that albuminuria and eGFR, with other routine clinical data, show at least modest prediction of future renal status if properly used. Indeed, a major limitation of many current biomarker studies is that they do not properly evaluate the marginal increase in prediction on top of these routinely available clinical data. Second, we emphasise that many of the candidate biomarkers for which there are numerous sporadic reports in the literature are tightly correlated with each other. Despite this, few studies have attempted to evaluate a wide range of biomarkers simultaneously to define the most useful among these correlated biomarkers. We also review the potential of high-dimensional panels of lipids, metabolites and proteins to advance the field, and point to some of the analytical and post-analytical challenges of taking initial studies using these and candidate approaches through to actual clinical biomarker use.

Indexed as

Glomerular Filtration RateAlbuminuriaAlgorithmsAnimalsBiomarkersDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Diabetic NephropathiesDisease ProgressionHumansKidneyKidney Failure, ChronicMetabolomicsMicroRNAsPrognosisProgrammed Cell Death 1 Ligand 2 ProteinBiomarkersMicroRNAsPDCD1LG2 protein, humanProgrammed Cell Death 1 Ligand 2 ProteinBiomarkerDiabetic kidney diseaseEpidemiologyNephropathyReview

Identifiers

PMID29520581
PMCPMC6448994

What Socratic 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 Socratic graph.