Evidence map›Paper›PMID 27285824›Full record

Observational studyPloS one2016

Morphometry Predicts Early GFR Change in Primary Proteinuric Glomerulopathies: A Longitudinal Cohort Study Using Generalized Estimating Equations.

Kevin V Lemley, Serena M Bagnasco, Cynthia C Nast, Laura Barisoni, Catherine M Conway, Stephen M Hewitt, Peter X K Song

Open access · goldAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

14 citing papers in PubMed, 18 citations in OpenAlex.

  1. A brief review of some artificial intelligence methods in nephrology.Pediatric nephrology (Berlin, Germany) · 2026
    Review
  2. Review
  3. Article
  4. Article
  5. AI applications in renal pathology.Kidney international · 2021
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Using computer-assisted morphometrics of 5-year biopsies to identify biomarkers of late renal allograft loss.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2019
    Article
  11. CureGN Study Rationale, Design, and Methods: Establishing a Large Prospective Observational Study of Glomerular Disease.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2019
    Observational
  12. Interstitial fibrosis scored on whole-slide digital imaging of kidney biopsies is a predictor of outcome in proteinuric glomerulopathies.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2018
    Article
  13. Review
  14. 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

7 authors at 6 institutions in 1 country.

Kevin V LemleyDepartment of Pediatrics, Division of Pediatric Nephrology, University of Southern California Keck School of Medicine, Los Angeles, California, United States of America.ORCID http://orcid.org/0000-0001-8342-5458
Serena M BagnascoDepartment of Pathology, The Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America.
Cynthia C NastDepartment of Pathology, Cedars-Sinai Medical Center, Los Angeles, California, United States of America.
Laura BarisoniDepartment of Pathology, University of Miami, Miami, Florida, United States of America.
Catherine M ConwayNational Cancer Institute, NIH, Bethesda, Maryland, United States of America.
Stephen M HewittNational Cancer Institute, NIH, Bethesda, Maryland, United States of America.
Peter X K SongDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America.
National Cancer Institute · USCedars-Sinai Medical Center · USJohns Hopkins University · USUniversity of Miami · USUniversity of Michigan · USUniversity of Southern California · US

Funding

Training Program in Clinical & Translationa Research in Human Glomerular DiseaseU54DK083912 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KRETZLER, MATTHIAS · 2009 to 2023
$20.3M
NIDDK NIH HHS U54 DK083912
6 · The paper itself

Abstract

objectiveMost predictive models of kidney disease progression have not incorporated structural data. If structural variables have been used in models, they have generally been only semi-quantitative.

methodsWe examined the predictive utility of quantitative structural parameters measured on the digital images of baseline kidney biopsies from the NEPTUNE study of primary proteinuric glomerulopathies. These variables were included in longitudinal statistical models predicting the change in estimated glomerular filtration rate (eGFR) over up to 55 months of follow-up.

resultsThe participants were fifty-six pediatric and adult subjects from the NEPTUNE longitudinal cohort study who had measurements made on their digital biopsy images; 25% were African-American, 70% were male and 39% were children; 25 had focal segmental glomerular sclerosis, 19 had minimal change disease, and 12 had membranous nephropathy. We considered four different sets of candidate predictors, each including four quantitative structural variables (for example, mean glomerular tuft area, cortical density of patent glomeruli and two of the principal components from the correlation matrix of six fractional cortical areas-interstitium, atrophic tubule, intact tubule, blood vessel, sclerotic glomerulus, and patent glomerulus) along with 13 potentially confounding demographic and clinical variables (such as race, age, diagnosis, and baseline eGFR, quantitative proteinuria and BMI). We used longitudinal linear models based on these 17 variables to predict the change in eGFR over up to 55 months. All 4 models had a leave-one-out cross-validated R2 of about 62%.

conclusionsSeveral combinations of quantitative structural variables were significantly and strongly associated with changes in eGFR. The structural variables were generally stronger than any of the confounding variables, other than baseline eGFR. Our findings suggest that quantitative assessment of diagnostic renal biopsies may play a role in estimating the baseline risk of succeeding loss of renal function in future clinical studies, and possibly in clinical practice.

Indexed as

Glomerular Filtration RateAdultBiopsyChildCohort StudiesDisease ProgressionEarly DiagnosisHumansKidneyKidney DiseasesKidney GlomerulusLinear ModelsLongitudinal StudiesOrgan SizePrognosisProteinuria

Identifiers

PMID27285824
PMCPMC4902229
OpenAlexW2409322573

What OpenQuestion holds

Textmetadata
LicenceCC0
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.