Evidence map›Paper›PMID 24976720›Full record

ReviewWorld journal of gastroenterology2014

Pancreatic biomarkers: could they be the answer?

Angela Lamarca, Jaime Feliu

Abstract readReview
In one paragraph

Review in World journal of gastroenterology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. High expression of TGR5 predicts a poor prognosis in patients with pancreatic cancer.International journal of clinical and experimental pathology · 2018
    Article
  3. Biomarkers in pancreatic ductal adenocarcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2017
    Review
  4. 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.

Angela LamarcaAngela Lamarca, Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester M20 4BX, United Kingdom.
Jaime FeliuAngela Lamarca, Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester M20 4BX, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic ductal adenocarcinoma (PDA) is known for its poor prognosis. Most of the patients are diagnosed with advanced stages, when no curative treatment is available. Currently, despite extensive clinical research on PDA, the median overall survival remains short. Diagnosis delay and primary chemo-resistance due to its intrinsic biological nature may explain the challenges to improve our results. Our knowledge about the molecular biology of PDA has exponentially increased during the last decades and its use for the development of biomarkers could help to reach better results in the clinical setting. These biomarkers could be the clue for the improvement in PDA clinical research by earlier detection strategies with diagnostic biomarkers, and by an individualization of treatment approach with prognostic and predictive biomarkers. This review summarizes the current knowledge about the molecular biology of PDA and the status of the most important prognostic and predictive biomarkers.

Indexed as

AnimalsBiomarkers, TumorCarcinoma, Pancreatic DuctalGene Expression Regulation, NeoplasticGenetic Predisposition to DiseaseHumansPancreatic NeoplasmsPatient SelectionPhenotypePrecision MedicinePredictive Value of TestsRisk FactorsTreatment OutcomeBiomarkers, TumorBiomarkersDiagnosisPancreatic adenocarcinomaPredictivePrognosticTreatment

Identifiers

PMID24976720
PMCPMC4069311

What OpenQuestion holds

Textmetadata
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.