Evidence map›Paper›PMID 38622292›Full record

ArticleRadiologie (Heidelberg, Germany)2024

[Current WHO classification (2022) of neuroendocrine neoplasms].

Oliver Buchstab, Thomas Knösel

Abstract readEnglish Abstract
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In one paragraph

Article in Radiologie (Heidelberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Oliver BuchstabPathologisches Institut, Ludwig-Maximilians-Universität (LMU), Thalkirchnerstr. 36, 80337, München, Deutschland.
Thomas KnöselPathologisches Institut, Ludwig-Maximilians-Universität (LMU), Thalkirchnerstr. 36, 80337, München, Deutschland. Thomas.Knoesel@med.uni-muenchen.de.
Ludwig-Maximilians-Universität München · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

clinical issueAfter the first description of the "carcinoid tumors" by the pathologist Siegfried Oberndorfer in Munich, the classification system of neuroendocrine neoplasms (NENs) is still a challenge and an evolving concept. METHODICAL INNOVATIONS: The new WHO classification system proposed a framework for universal classification. ACHIEVEMENTS: The new WHO classification system recognizes two distinct families distinguished by genetic, morphology and clinical behaviour: Well differentiated NENs are defined as neuroendocrine tumor (NET G1, G2, G3), while poorly differentiated ones are defined as neuroendocrine carcinoma (NEC, G3) and further subdivided into small and large cell carcinoma. All NENs are characterized by the expression of synaptophysin and chromogranin A, Ki-67 and morphology. MOLECULAR PATHOLOGY: The morphological NEN dichotomy is supported by genetic alterations. NECs show TP53 and RB1 alterations that are absent in NETs and are therefore useful for differentiating between NETs and NECs. PRACTICAL RECOMMENDATIONS: All NENs are divided into well-differentiated neuroendocrine tumor (NET G1, G2, G3) or poorly differentiated neuroendocrine carcinoma (NEC, G3). They are categorized by morphology, mitotic count and immunohistochemistry with synaptophysin, chromogranin and Ki-67.

Indexed as

Neuroendocrine TumorsWorld Health OrganizationHumansCarcinoidKi-67 immunohistologyNeuroendocrine carcinomasNeuroendocrine tumorsWHO Classification

Identifiers

PMID38622292
OpenAlexW4394811963

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.