Evidence map›Paper›PMID 33178733›Full record

ReviewVisceral medicine2020

Biomarkers for Precision Treatment in Gastric Cancer.

Angelica Petrillo, Elizabeth C Smyth

Open access · bronzeAbstract readReview
In one paragraph

Review in Visceral medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.8field-weighted citation impact, top 12% 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

18 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Predictive biomarkers in gastric cancer.Journal of cancer research and clinical oncology · 2023
    Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. The emerging role of miR-10 family in gastric cancer.Cell cycle (Georgetown, Tex.) · 2021
    Review
  16. Article
  17. Review
  18. 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

2 authors at 2 institutions in 2 countries.

Angelica PetrilloMedical Oncology Unit, Ospedale del Mare, Naples, Italy.
Elizabeth C SmythCambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom.
Cambridge University Hospitals NHS Foundation Trust · GBUniversity of Campania "Luigi Vanvitelli" · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGastric cancer (GC) is one of the most lethal cancers worldwide. Although GC was historically considered a single entity within the organ of origin, nowadays it is acknowledged that GC represents a heterogeneous disease. Nevertheless, in this field there is still a lack of biomarkers able to guide the choice of the best treatment options for each patient. This review aims to summarize the prognostic and predictive biomarkers evaluated in GC and their role as a guide for treatment for precision medicine. SUMMARY: Human epidermal growth factor receptor 2 overexpression represents the only predictive molecular biomarker validated in GC, while its prognostic role is still controversial. Microsatellite instability and Epstein-Barr virus status are promising for prediction of the response to immunotherapy. The role of other biomarkers (ctDNA, programmed death ligand 1 [PD-L1], and TMB), as well as the practical application of molecular classifications, requires further evaluation before use in clinical practice. 18-FDG-PET scan could be useful as a predictive tool in non-metastatic GC patients receiving a perioperative approach. Finally, the tumor microenvironment may have an evolving role in the future. KEY MESSAGES: GC is a heterogeneous disease and targeted approaches are needed. The finding of prognostic and predictive factors is a hot topic in the field of GC personalized medicine.

Indexed as

ctDNAHuman epidermal growth factor receptor 2Microsatellite instabilityPrognostic factorsProgrammed death ligand 1

Identifiers

PMID33178733
PMCPMC7590759
OpenAlexW3088796302

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.