Evidence map›Paper›PMID 28651471›Full record

ArticleThe journal of histochemistry and cytochemistry : official journal of the Histochemistry Society2017

Grading and Prognostication of Neuroendocrine Tumors of the Pancreas: A Comparison Study of Ki67 and PHH3.

Jessica Tracht, Kui Zhang, Deniz Peker

Abstract readComparative Study
In one paragraph

Article in The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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.

Jessica TrachtDepartment of Pathology, The University of Alabama at Birmingham School of Medicine, Birmingham, Alabama (JT, DP).
Kui ZhangDepartment of Biostatistics, The University of Alabama at Birmingham School of Public Health, Birmingham, Alabama (KZ).
Deniz PekerDepartment of Pathology, The University of Alabama at Birmingham School of Medicine, Birmingham, Alabama (JT, DP).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grading of pancreatic neuroendocrine tumors (pNETs) is currently based on mitotic rate and Ki67 proliferation index. Phosphohistone-H3 (PHH3) is an effective marker for mitosis that has been proposed to use in grading various NETs. It remains unclear which method more accurately predicts grade and clinical outcome. Cases of pNET were evaluated using immunohistochemical stains for Ki67 and PHH3. In addition, each case was evaluated for necrosis, lymphovascular invasion, and perineural invasion and compared with stage. R project statistical analysis was used for comparisons. Sixty-three cases were included in the study including 29 males and 34 females (M:F 0.9) with a median age of 59 years (ranging 34-84). There was not a significant discrepancy in the stratification of tumor grades for Ki67 and PHH3. PHH3 significantly predicted lymph node metastasis ( p=0.041). Necrosis correlated with overall survival ( p=0.017). The results suggest that PHH3 is an effective marker for determining mitotic activity and can be used alternative to Ki67. In addition, necrosis may be included in the reporting of pNET as it may play a prognostic role. Larger scale studies are warranted to understand the biology and behavior of these tumors.

Indexed as

AdultAgedAged, 80 and overBiomarkers, TumorFemaleHistonesHumansKi-67 AntigenMaleMiddle AgedMitosisMitotic IndexNeoplasm GradingPancreasPancreatic NeoplasmsPhosphorylationBiomarkers, TumorHistonesKi-67 AntigenKi67mitosisneuroendocrine tumorpancreasPHH3

Identifiers

PMID28651471
PMCPMC5490847

What OpenQuestion holds

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Registered trials

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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.