Evidence map›Paper›PMID 30172916›Full record

ArticleHuman pathology2019

Comparison of evaluation techniques, including digital image analysis, for MYC protein expression by immunohistochemical stain in aggressive B-cell lymphomas.

Meghan Hupp, Sarah Williams, Brian Dunnette, Katelyn M Tessier, Elizabeth L Courville

Abstract readComparative Study
In one paragraph

Article in Human pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 1 institution in 1 country.

Meghan HuppDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA.
Sarah WilliamsDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA.
Brian DunnetteDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA.
Katelyn M TessierMasonic Cancer Center Biostatistics Core, University of Minnesota, Minneapolis, MN 55455, USA.
Elizabeth L CourvilleDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA. Electronic address: ecourvil@umn.edu.
University of Minnesota · US

Funding

Women's CancerP30CA077598 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Jeffrey S. Miller · 1998 to 2026
$100.4M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR000114 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$35.0M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR002494 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R, WEISDORF, DANIEL J · 2018 to 2022
$34.9M
NCATS NIH HHS UL1 TR000114NCATS NIH HHS UL1 TR002494NCI NIH HHS P30 CA077598
6 · The paper itself

Abstract

Incorporation of an MYC immunohistochemical stain in the workup of large B-cell lymphomas has become common in hematopathology practice. Evaluation of this stain can be difficult because of staining heterogeneity and can have interobserver variability, particularly when performed on the entire tumor sections. We identified 87 cases of aggressive B-cell lymphoma (34 core needle and 53 excisional biopsies) and compared the following methods of MYC immunohistochemical staining evaluation: the original pathologist's interpretation, a systematic retrospective method of evaluation by manual analysis, and a retrospective method of evaluation by digital image analysis (using scanned slides analyzed via the Aperio Nuclear algorithm). Overall, concordance among these methods was around 80% with κ statistics showing good agreement. However, nearly one-third of our cases had a percent MYC positivity in the 30% to 50% range, and for these cases, concordance among the various methods was marginal/poor. This suggests limited utility as a prognostic or predictive marker using 40% as a cutoff value. In our series, core biopsy specimens were poor predictors of MYC gene rearrangement, and there was no association between MYC immunohistochemical stain and MYC gene gain/amplification. Our retrospective digital image analysis showed strong correlation in MYC percent positivity with our retrospective manual review (correlation coefficient of 0.90) and similar concordance to pathologist interpretation as among pathologists, suggesting that digital image analysis is a viable alternative to manual determination of MYC percent positivity. Digital image analysis provides further opportunities for more sophisticated and standardized scoring systems, which may be helpful in future prognostic/predictive studies.

Indexed as

AdolescentAdultAgedAged, 80 and overBiomarkers, TumorChildChild, PreschoolFemaleHumansImage Processing, Computer-AssistedImmunohistochemistryLymphoma, B-CellMaleMiddle AgedProto-Oncogene Proteins c-mycRetrospective StudiesBiomarkers, TumorMYC protein, humanProto-Oncogene Proteins c-mycDiffuse large B-cell lymphomaDigital image analysisDLBCLHigh-grade B-cell lymphomaImmunohistochemistryMYCPrognosis

Identifiers

PMID30172916
PMCPMC6365198
OpenAlexW2889366444

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.