Evidence map›Paper›PMID 29321190›Full record

ReviewThe Journal of endocrinology2018

Genomic landscape of pancreatic neuroendocrine tumours: the International Cancer Genome Consortium.

Andrea Mafficini, Aldo Scarpa

Open access · hybridAbstract readReview
In one paragraph

Review in The Journal of endocrinology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed
8.3field-weighted citation impact, top 2% 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

57 citing papers in PubMed, 97 citations in OpenAlex.

  1. Review
  2. Expanding the clinical tumor phenotype of the EPAS1-asssociated tumor syndrome.The Journal of clinical endocrinology and metabolism · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.The Journal of clinical endocrinology and metabolism · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Circulating hsa-miR-5096 predictsFrontiers in oncology · 2023
    Article
  20. Article
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.

Andrea MafficiniARC-Net Centre for Applied Research on CancerUniversity and Hospital Trust of Verona, Verona, Italy.
Aldo ScarpaARC-Net Centre for Applied Research on CancerUniversity and Hospital Trust of Verona, Verona, Italy aldo.scarpa@univr.it.
University of Verona · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuroendocrine tumours (NETs) may arise throughout the body and are a highly heterogeneous, relatively rare class of neoplasms difficult to study also for the lack of disease models. Despite this, knowledge on their molecular alterations has expanded in the latest years, also building from genetic syndromes causing their onset. Pancreatic NETs (PanNETs) have been among the most studied, and research so far has outlined a series of recurring features, as inactivation of

Indexed as

AdenomaAnimalsEpigenesis, GeneticGenetic Predisposition to DiseaseGenetic TechniquesHumansIntestinal NeoplasmsMiceMutationNeuroendocrine TumorsPancreatic NeoplasmsPhosphatidylinositol 3-KinasesProto-Oncogene ProteinsRNA, MessengerStomach NeoplasmsTOR Serine-Threonine KinasesMEN1 protein, humanMTOR protein, humanPhosphatidylinositol 3-KinasesProto-Oncogene ProteinsRNA, MessengerTOR Serine-Threonine Kinasescancermolecular biologyneuroendocrinologypancreas

Identifiers

PMID29321190
PMCPMC5811627
OpenAlexW2783135417

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.