Evidence map›Paper›PMID 21993584›Full record

ArticleKidney international2012

A composite urine biomarker reflects interstitial inflammation in lupus nephritis kidney biopsies.

Xiaolan Zhang, Haikady N Nagaraja, Tibor Nadasdy, Huijuan Song, Alison McKinley, Jason Prosek, Swapna Kamadana, Brad H Rovin

Abstract read
In one paragraph

Article in Kidney international, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 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, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Lupus nephritis.Nature reviews. Disease primers · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Lupus nephritis.Nature reviews. Disease primers · 2020
    Review
  11. Article
  12. Review
  13. Nonproliferative Forms of Lupus Nephritis: An Overview.Rheumatic diseases clinics of North America · 2018
    Review
  14. Precision medicine in lupus nephritis: can biomarkers get us there?Translational research : the journal of laboratory and clinical medicine · 2018
    Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Xiaolan ZhangDivision of Nephrology, Department of Medicine, The Ohio State University College of Medicine, Columbus, Ohio 43210, USA.
Haikady N Nagaraja
Tibor Nadasdy
Huijuan Song
Alison McKinley
Jason Prosek
Swapna Kamadana
Brad H Rovin
The Ohio State University · US

Funding

University of Iowa Clinical and Translational Science Program (TL1)UL1RR025755 · NCRR · OHIO STATE UNIVERSITY · PI JACKSON, REBECCA D · 2008 to 2011
$26.3M
Modeling SLE Nephritis Through Urine MCP-1R01DK074661 · NIDDK · OHIO STATE UNIVERSITY · PI ROVIN, BRAD H · 2008 to 2010
$669k
Protein Phenotyping of SLE Nephritis Flare CycleR21DK077331 · NIDDK · OHIO STATE UNIVERSITY · PI ROVIN, BRAD H · 2008 to 2009
$413k
NCRR NIH HHS UL1 RR025755NIDDK NIH HHS R01 DK074661NIDDK NIH HHS R21 DK077331
6 · The paper itself

Abstract

The initial treatment of lupus nephritis is usually based on a renal biopsy. Subsequent disease flares, however, are often treated without the benefit of kidney pathology because repeat biopsies are infrequent. A noninvasive, real-time method to assess renal pathology would be useful to adjust treatment and improve outcome. To develop such a method we collected urine samples at or close to the time of 64 biopsies from 61 patients with lupus nephritis to identify potential biomarkers of tubulointerstitial inflammation and correlated these to biopsy parameters scored by a renal pathologist using a semiquantitative scale. Linear discriminant analysis was used to weight variables and derive composite biomarkers that identified the level of tubulointerstitial inflammation based on urine concentrations of monocyte chemotactic protein-1, hepcidin (a marker of active lupus), and liver fatty acid-binding protein. The discriminant function that described the most accurate composite biomarkers included urine monocyte chemotactic protein-1 and serum creatinine as the independent variables. This composite had sensitivity, specificity, positive predictive value, and negative predictive value of 100, 81, 67, and 100%, respectively. Only 14% of the biopsies were misclassified. Thus, specific renal pathologic lesions can be modeled by composite biomarkers to noninvasively follow and adjust the treatment of lupus nephritis reflecting renal injury.

Indexed as

AdolescentAdultAntimicrobial Cationic PeptidesBiomarkersBiopsyChemokine CCL2CreatinineFatty Acid-Binding ProteinsFemaleHepcidinsHumansLinear ModelsLupus NephritisMaleMiddle AgedNephritis, InterstitialAntimicrobial Cationic PeptidesBiomarkersChemokine CCL2CreatinineFatty Acid-Binding ProteinsHAMP protein, humanHepcidins

Identifiers

PMID21993584
PMCPMC3640330
OpenAlexW2003941029

What OpenQuestion holds

Textmetadata
LicenceTDM
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.