Evidence map›Paper›PMID 29457738›Full record

ArticleArchives of pathology & laboratory medicine2018

Reproducibility and Feasibility of Strategies for Morphologic Assessment of Renal Biopsies Using the Nephrotic Syndrome Study Network Digital Pathology Scoring System.

Jarcy Zee, Jeffrey B Hodgin, Laura H Mariani, Joseph P Gaut, Matthew B Palmer, Serena M Bagnasco, Avi Z Rosenberg, Stephen M Hewitt, Lawrence B Holzman, Brenda W Gillespie and 1 more

Abstract read
In one paragraph

Article in Archives of pathology & laboratory medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. A novel agreement statistic using data on uncertainty in ratings.Journal of the Royal Statistical Society. Series C, Applied statistics · 2023
    Article
  4. Review
  5. Quantification of Glomerular Structural Lesions: Associations With Clinical Outcomes and Transcriptomic Profiles in Nephrotic Syndrome.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2022
    Observational
  6. AI applications in renal pathology.Kidney international · 2021
    Review
  7. Article
  8. Article
  9. Review
  10. Observational
  11. Article
  12. Artificial intelligence driven next-generation renal histomorphometry.Current opinion in nephrology and hypertension · 2020
    Review
  13. Ultrastructural Characterization of Proteinuric Patients Predicts Clinical Outcomes.Journal of the American Society of Nephrology : JASN · 2020
    Observational
  14. Homogeneity score test of ACBMC medical research methodology · 2020
    Article
  15. 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
  16. 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

11 authors.

Jarcy Zee
Jeffrey B Hodgin
Laura H Mariani
Joseph P Gaut
Matthew B Palmer
Serena M Bagnasco
Avi Z Rosenberg
Stephen M Hewitt
Lawrence B Holzman
Brenda W Gillespie
Laura BarisoniFrom Biostatistics, Arbor Research Collaborative for Health, Ann Arbor, Michigan (Dr Zee); the Departments of Pathology (Dr Hodgin), Internal Medicine (Dr Mariani), and Biostatistics (Dr Gillespie), University of Michigan, Ann Arbor; Arbor Research Collaborative for Health, Ann Arbor, Michigan (Dr Mariani); the Department of Pathology & Immunology, Washington University, St Louis, Missouri (Dr Gaut); the Departments of Pathology and Laboratory Medicine (Dr Palmer) and Medicine (Dr. Holzman), University of Pennsylvania, Philadelphia; the Department of Pathology, Johns Hopkins University, Baltimore, Maryland (Drs Bagnasco and Rosenberg); the Kidney Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland (Dr Rosenberg); the Laboratory of Pathology, National Cancer Institute, Bethesda, Maryland (Dr Hewitt); and the Department of Pathology, University of Miami, Miami, Florida (Dr Barisoni).

Funding

Training Program in Clinical & Translationa Research in Human Glomerular DiseaseU54DK083912 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HOLZMAN, LAWRENCE B. · 2009 to 2023
$20.3M
Experimental Pathology Laboratory (EPL)ZICBC011638 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI HEWITT, STEPHEN · 2015 to 2025
$16.6M
Computational Pathology of Proteinuric DiseasesR01DK118431 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI BARISONI, LAURA MARIACHIARA, HODGIN, JEFFREY BENTON · 2018 to 2025
$3.6M
NIDDK NIH HHS R01 DK118431NIDDK NIH HHS U54 DK083912
6 · The paper itself

Abstract

Context Testing reproducibility is critical for the development of methodologies for morphologic assessment. Our previous study using the descriptor-based Nephrotic Syndrome Study Network Digital Pathology Scoring System (NDPSS) on glomerular images revealed variable reproducibility. Objective To test reproducibility and feasibility of alternative scoring strategies for digital morphologic assessment of glomeruli and explore use of alternative agreement statistics. Design The original NDPSS was modified (NDPSS1 and NDPSS2) to evaluate (1) independent scoring of each individual biopsy level, (2) use of continuous measures, (3) groupings of individual descriptors into classes and subclasses prior to scoring, and (4) indication of pathologists' confidence/uncertainty for any given score. Three and 5 pathologists scored 157 and 79 glomeruli using the NDPSS1 and NDPSS2, respectively. Agreement was tested using conventional (Cohen κ) and alternative (Gwet agreement coefficient 1 [AC

Indexed as

AlgorithmsDiagnostic ImagingFeasibility StudiesHumansNephrotic SyndromeObserver VariationPathology, ClinicalReproducibility of Results

Identifiers

PMID29457738
PMCPMC5946059

What OpenQuestion holds

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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.