ReviewVirchows Archiv : an international journal of pathology2026
Concept of neuroendocrine neoplasms of all organs with a focus on grading, subtyping.
Review in Virchows Archiv : an international journal of pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- The Genomic Patterns of Well-Differentiated Pancreatic Neuroendocrine Tumors (NETs) Identify Sub-Sets for Rational Therapeutic Targeting.International journal of molecular sciences · 2026Article
- NETest2.0Cancers · 2026Article
- Pancreatic Neuroendocrine Tumor with Acinar Pattern Mimicking Pancreatic Ductal Adenocarcinoma: A Case Report.Surgical case reports · 2026Article
- Pathogenic germline variants identified in pNEN patients during genetic testing.Endocrine oncology (Bristol, England) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuroendocrine neoplasms (NENs) are a heterogeneous group of neoplasms encompassing both well differentiate neuroendocrine tumors (NETs), and poorly differentiated neuroendocrine carcinomas (NECs). This classification is supported by distinct histological, clinical, and molecular profiles. NETs are typically slow-growing and hormone-producing, with organoid architecture and frequent associations with hereditary syndromes such as multiple endocrine neoplasia type 1 (MEN1) and von Hippel-Lindau (VHL) disease. In contrast, NECs are highly malignant, rapidly proliferating tumors characterized by mutations in adenocarcinoma-driver genes and in addition to TP53 mutations and RB1 inactivation, without hereditary links to endocrine tumor syndomes. Recent WHO classifications introduced site-specific grading systems, including NET G3 in the digestive, urogenital, gynecological and head and neck organs. There is growing evidence of progression from NET G1 to G3 with occasionally NEC-like features via acquired TP53 mutations. Advances in transcription factor profiling related to hormonal expression, molecular alterations resulted in further subtyping especially in pancreatic, pulmonary, and pituitary NETs. These tools support more precise treatment strategies. Genomic studies focusing on pancreatic NETs highlighted mutations in MEN1, DAXX, ATRX, and targets in mTOR pathway. NECs display higher tumor mutation burdens and harbor various actionable alterations. Approximately 5-10% of NETs are associated with hereditary syndromes, though recent findings suggest germline pathogenic variants, which were present in additional 5% of apparently sporadic NETs and NECs, requiring further study. An integrated histological, molecular, and clinical approach is essential to improve the classification, prognostication, and management of NENs, while recognizing the distinct biology of individual subtypes.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.