Evidence map›Paper›PMID 30768568›Full record

ReviewTransplantation2019

Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring.

Michelle A Wood-Trageser, Andrew J Lesniak, Anthony J Demetris

Abstract readReview
In one paragraph

Review in Transplantation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Commentary: The Digital Fate of Glomeruli in Renal Biopsy.Journal of pathology informatics · 2021
    Article
  10. Article
  11. Machine learning to predict transplant outcomes: helpful or hype? A national cohort study.Transplant international : official journal of the European Society for Organ Transplantation · 2020
    Article
  12. Banff Digital Pathology Working Group: Going digital in transplant pathology.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2020
    Article
  13. Precision transplant pathology.Current opinion in organ transplantation · 2020
    Review
  14. Review
  15. Review
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

3 authors.

Michelle A Wood-TrageserDivision of Transplant Pathology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Andrew J LesniakDivision of Transplant Pathology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Anthony J DemetrisDivision of Transplant Pathology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA.

Funding

Immune Tolerance Network UM1 2023 SupplementUM1AI109565 · NIAID · BENAROYA RESEARCH INST AT VIRGINIA MASON · PI Mark S Anderson, Jane Hoyt Buckner · 2014 to 2026
$451.6M
Immunosuppression Withdrawal for Stable Pediatric Liver Transplant RecipientsU01AI100807 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FENG, SANDY · 2012 to 2016
$9.5M
Transplant Pathology and Tissue Imaging Core (Core B)U19AI131453 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI EZZELARAB, MOHAMED B · 2017 to 2022
$8.4M
Chronic Graft Destruction: Interplay of Allo- and Autoantibodies and NonadherenceU01AI104336 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI WEBBER, STEVEN A. · 2013 to 2018
$4.8M
Polyclonal Tregs to Promote Tolerance in Pediatric Liver Transplant RecipientsU01AI104347 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FENG, SANDY · 2013 to 2017
$4.8M
PROSPECTIVE LONGITUDINAL STUDY OF IWITH SCREEN FAILURES SECONDARY TO HISTOPATHOLOGYR01DK114180 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FENG, SANDY · 2017 to 2019
$1.3M
NIAID NIH HHS U01 AI100807NIAID NIH HHS U01 AI104336NIAID NIH HHS U01 AI104347NIAID NIH HHS U19 AI131453NIAID NIH HHS UM1 AI109565NIDDK NIH HHS R01 DK114180
6 · The paper itself

Abstract

Traditional histopathological allograft biopsy evaluation provides, within hours, diagnoses, prognostic information, and mechanistic insights into disease processes. However, proponents of an array of alternative monitoring platforms, broadly classified as "invasive" or "noninvasive" depending on whether allograft tissue is needed, question the value proposition of tissue histopathology. The authors explore the pros and cons of current analytical methods relative to the value of traditional and illustrate advancements of next-generation histopathological evaluation of tissue biopsies. We describe the continuing value of traditional histopathological tissue assessment and "next-generation pathology (NGP)," broadly defined as staining/labeling techniques coupled with digital imaging and automated image analysis. Noninvasive imaging and fluid (blood and urine) analyses promote low-risk, global organ assessment, and "molecular" data output, respectively; invasive alternatives promote objective, "mechanistic" insights by creating gene lists with variably increased/decreased expression compared with steady state/baseline. Proponents of alternative approaches contrast their preferred methods with traditional histopathology and: (1) fail to cite the main value of traditional and NGP-retention of spatial and inferred temporal context available for innumerable objective analyses and (2) belie an unfamiliarity with the impact of advances in imaging and software-guided analytics on emerging histopathology practices. Illustrative NGP examples demonstrate the value of multidimensional data that preserve tissue-based spatial and temporal contexts. We outline a path forward for clinical NGP implementation where "software-assisted sign-out" will enable pathologists to conduct objective analyses that can be incorporated into their final reports and improve patient care.

Indexed as

Diagnosis, Computer-AssistedImage Interpretation, Computer-AssistedMicroscopyAllograftsBiopsyGraft SurvivalHumansOrgan TransplantationPostoperative ComplicationsPredictive Value of TestsTime FactorsTreatment OutcomeWorkflow

Identifiers

PMID30768568
PMCPMC6594872

What OpenQuestion holds

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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.