Evidence map›Paper›PMID 23990678›Full record

ArticleJournal of the American Society of Nephrology : JASN2013

Analysis of a urinary biomarker panel for incident kidney disease and clinical outcomes.

Conall M O'Seaghdha, Shih-Jen Hwang, Martin G Larson, James B Meigs, Ramachandran S Vasan, Caroline S Fox

Open access · greenAbstract read
In one paragraph

Article in Journal of the American Society of Nephrology : JASN, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
4.1field-weighted citation impact, top 6% 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

39 citing papers in PubMed, 2 syntheses or guidelines pooled it, 73 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. The urine-to-plasma urea concentration ratio is associated with eGFR and eGFR decline over time in a population cohort.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2023
    Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. 70-year legacy of the Framingham Heart Study.Nature reviews. Cardiology · 2019
    Review
  17. Biomarkers of Drug-Induced Kidney Toxicity.Therapeutic drug monitoring · 2019
    Review
  18. Article
  19. Article
  20. 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

6 authors at 5 institutions in 3 countries.

Conall M O'SeaghdhaNational Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, Massachusetts;
Shih-Jen Hwang
Martin G Larson
James B Meigs
Ramachandran S Vasan
Caroline S Fox
National Heart Lung and Blood Institute · USBeaumont Hospital · IEBoston University · USBrigham and Women's Hospital · USHarvard University · US

Funding

Framingham Heart Study/FoxZIAHL006094 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI FOX, CAROLINE · 2010 to 2015
$6.9M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N01-HC-25195
6 · The paper itself

Abstract

Whether novel biomarkers improve the assessment of incident kidney disease and related adverse outcomes remains to be tested in longitudinal observational studies. We tested 14 urinary biomarkers for association with incident kidney, cardiovascular, and mortality outcomes in 2948 Framingham Heart Study participants. Baseline examinations were performed between 1995 and 1998; mean follow-up was 10.1 years for renal outcomes and 11.2 years for survival analyses. Primary outcomes were incident CKD, incident albuminuria, incident cardiovascular disease, and all-cause mortality. Secondary analyses assessed incident congestive heart failure (CHF) and mortality with coexistent kidney disease. Biomarkers were tested for association with renal end points using logistic regression and incident cardiovascular and mortality outcomes in proportional hazards models; α1-microglobulin, Kim-1, and TFF-3 predicted all-cause mortality (hazard ratio per SD increase in log-transformed biomarker [HR] range, 1.15 to 1.21; 95% confidence interval [CI] range, 1.04 to 1.34; P values=0.007 to <0.001), whereas α1-microglobulin, β2-microglobulin, KIM-1, and TFF-3 associated with death with coexistent kidney disease (HR range, 1.72-2.25; 95% CI, 1.17 to 3.24; P values<0.01). KIM-1 also associated with the risk of incident CHF (HR, 1.32; 95% CI, 1.07 to 1.63; P=0.008). CTGF associated nominally with CKD (HR, 0.83; 95% CI, 0.71 to 0.98; P=0.03), but no other biomarkers associated with incident CKD or albuminuria. Addition of α1-microglobulin and TFF-3 resulted in a nonsignificant net reclassification index (NRI) of 3% for all-cause mortality beyond clinical risk factors. In conclusion, components of a panel of 14 subclinical biomarkers of kidney injury were associated with important clinical outcomes and merit additional investigation.

Indexed as

AgedAlbuminuriaAlpha-GlobulinsBiomarkersCardiovascular DiseasesCause of DeathFemaleHepatitis A Virus Cellular Receptor 1HumansKidney DiseasesMaleMembrane GlycoproteinsMiddle AgedNeoplasmsPeptidesProportional Hazards Modelsalpha-1-microglobulinAlpha-GlobulinsBiomarkersHAVCR1 protein, humanHepatitis A Virus Cellular Receptor 1Membrane GlycoproteinsPeptidesReceptors, VirusTFF3 protein, humanTrefoil Factor-3

Identifiers

PMID23990678
PMCPMC3810081
OpenAlexW2132627258

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.