Evidence map›Paper›PMID 37511077›Full record

ReviewInternational journal of molecular sciences2023

Translating Molecular Biology Discoveries to Develop Targeted Cancer Interception in Barrett's Esophagus.

Sohini Samaddar, Daniel Buckles, Souvik Saha, Qiuyang Zhang, Ajay Bansal

Open access · goldAbstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 1 country.

Sohini SamaddarDepartment of Internal Medicine, University of Kansas Health System, Kansas City, KS 66160, USA.
Daniel BucklesDepartment of Gastroenterology and Hepatology, University of Kansas Health System, Kansas City, KS 66160, USA.
Souvik SahaDepartment of Internal Medicine, University of Kansas Health System, Kansas City, KS 66160, USA.ORCID 0000-0002-2640-7533
Qiuyang ZhangCenter for Esophageal Diseases, Department of Medicine, Baylor University Medical Center, Dallas, TX 75246, USA.
Ajay BansalDepartment of Gastroenterology and Hepatology, University of Kansas Health System, Kansas City, KS 66160, USA.
University of Kansas · USBaylor University Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal adenocarcinoma (EAC) is a rapidly increasing lethal tumor. It commonly arises from a metaplastic segment known as Barrett's esophagus (BE), which delineates the at-risk population. Ample research has elucidated the pathogenesis of BE and its progression from metaplasia to invasive carcinoma; and multiple molecular pathways have been implicated in this process, presenting several points of cancer interception. Here, we explore the mechanisms of action of various agents, including proton pump inhibitors, non-steroidal anti-inflammatory drugs, metformin, and statins, and explain their roles in cancer interception. Data from the recent AspECT trial are discussed to determine how viable a multipronged approach to cancer chemoprevention would be. Further, novel concepts, such as the repurposing of chemotherapeutic drugs like dasatinib and the prevention of post-ablation BE recurrence using itraconazole, are discussed.

Indexed as

AdenocarcinomaBarrett EsophagusEsophageal NeoplasmsHumansMetaplasiaRisk FactorsBarrett’s esophaguschemopreventionesophageal adenocarcinoma

Identifiers

PMID37511077
PMCPMC10379200
OpenAlexW4384039606

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.