Evidence map›Paper›PMID 33537001›Full record

ReviewFrontiers in endocrinology2020

Molecular Signatures and Their Clinical Utility in Pancreatic Neuroendocrine Tumors.

Praveen Dilip Chatani, Sunita Kishore Agarwal, Samira Mercedes Sadowski

Abstract readReview
In one paragraph

Review in Frontiers in endocrinology, 2020. 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
–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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
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.

Praveen Dilip ChataniEndocrine Surgery Section, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States.
Sunita Kishore AgarwalMetabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, United States.
Samira Mercedes SadowskiEndocrine Surgery Section, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States.

Funding

Genes associated with endocrine tumorigenesisZIADK075035 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI AGARWAL, SUNITA · 2009 to 2025
$6.9M
Intramural NIH HHS ZIA DK075035
6 · The paper itself

Abstract

Pancreatic neuroendocrine tumors (PNETs) are classified based on their histologic differentiation and proliferative indices, which have been used extensively to determine prognosis. Advances in next-generation sequencing and other high-throughput techniques have allowed researchers to objectively explore tumor specimens and learn about the genetic alterations associated with malignant transformation in PNETs. As a result, targeted, pathway-specific therapies have been emerging for the treatment of unresectable and metastatic disease. As we continue to trial various pharmaceutical products, evidence from studies using multi-omics approaches indicates that clinical aggressiveness stratifies along other genotypic and phenotypic demarcations, as well. In this review, we explore the clinically relevant and potentially targetable molecular signatures of PNETs, their associated trials, and the overall differences in reported prognoses and responses to existing therapies.

Indexed as

Gene Expression Regulation, NeoplasticAntineoplastic AgentsBiomarkers, TumorHumansNeuroendocrine TumorsPancreatic NeoplasmsPrognosisAntineoplastic AgentsBiomarkers, Tumorclinical trialmolecular signaturesneuroendocrine carcinomapancreatic neuroendocrine tumorsignaling pathwaytumorigenesis

Identifiers

PMID33537001
PMCPMC7848028

What OpenQuestion holds

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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.