Evidence map›Paper›PMID 42882251›Full record

ReviewDiagnostics (Basel, Switzerland)2026

Neuroendocrine Tumors (NETs) of the Larynx.

Jan Laco, Abbas Agaimy, Alfio Ferlito

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jan LacoThe Fingerland Department of Pathology, University Hospital Hradec Kralove, 500 05 Hradec Kralove, Czech Republic.ORCID 0000-0002-9602-7501
Abbas AgaimyInstitute of Pathology, Erlangen University Hospital, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany.ORCID 0000-0002-0445-8161
Alfio FerlitoInternational Head and Neck Scientific Group, 35100 Padua, Italy.ORCID 0000-0002-8247-8002

Funding

Charles University Cooperatio Program, research area DIAGMinistry of Education Youth and Sports BBMRI-CZ LM2023033
6 · The paper itself

Abstract

To review the current state of knowledge regarding neuroendocrine tumors (NETs) of the larynx, with a particular focus on their epidemiology, etiopathogenesis, clinico-pathological features, immunohistochemical profile, and differential diagnostics. Narrative review. Diagnostic criteria for laryngeal NETs were recently defined in the 5th edition of the WHO Classification of Head and Neck Tumors, which newly introduces the entity of NET, grade 3 (G3 NET). However, some of these criteria are still considered provisional. The most common NET of the larynx is the G2 NET. These tumors typically affect older men, with the supraglottic region being the most frequent localization. For a definitive diagnosis, it is essential to demonstrate the epithelial origin and neuroendocrine differentiation of these tumors using cytokeratins and neuroendocrine markers (e.g., chromogranin, INSM1, synaptophysin). The differentiation between individual NET types is based on mitotic activity and/or Ki-67 proliferation index, as well as the presence or absence of necrosis. Laryngeal NETs typically exhibit wild-type p53 expression and retained Rb1 and somatostatin receptor 2 expression. This can be utilized in the differential diagnosis from neuroendocrine carcinomas (NECs). Given that laryngeal NETs frequently express calcitonin, they must be differentiated from medullary thyroid carcinoma (MTC), particularly in lymph node metastases. A high frequency of

Indexed as

classificationdiagnosislarynxneuroendocrine neoplasmsneuroendocrine tumorsprognosisterminology

Identifiers

PMID42882251
PMCPMC13664439

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.