Evidence map›Paper›PMID 36780331›Full record

ReviewTechnology in cancer research & treatment

Advances in Treatment Models of Advanced Gastric Cancer.

Tao Li, Yufang He, Qinglei Zhong, Jiang Yu, Xinhua Chen

Open access · goldAbstract readReview
In one paragraph

Review in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-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

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Therapeutic efficacy of immunotherapy for gastric cancer metastasis.World journal of gastrointestinal surgery · 2024
    Article
  6. Review
  7. Article
  8. Article
  9. 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

5 authors at 2 institutions in 1 country.

Tao LiDepartment of General Surgery, 198153Nanfang Hospital, 70570Southern Medical University, Guangzhou, China.
Yufang HeThe First Clinical Medical School, 70570Southern Medical University, Guangzhou, Guangdong, China.
Qinglei ZhongThe First Clinical Medical School, 70570Southern Medical University, Guangzhou, Guangdong, China.
Jiang YuDepartment of General Surgery, 198153Nanfang Hospital, 70570Southern Medical University, Guangzhou, China.
Xinhua ChenDepartment of General Surgery, 198153Nanfang Hospital, 70570Southern Medical University, Guangzhou, China.ORCID 0000-0002-1879-4318
Nanfang Hospital · CNSouthern Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prognosis of advanced gastric cancer (AGC) is extremely poor, and the therapeutic effect of traditional palliative chemotherapy is far from satisfactory. To overcome this bottleneck, palliative surgery resection, perioperative chemotherapy combined with surgical resection, hyperthermic intraperitoneal chemotherapy (HIPEC), pressurized intraperitoneal aerosol chemotherapy (PIPAC), radiation therapy, molecular-targeted therapy have been explored in AGC. Although considerable progress has been achieved, there is still no overwhelming therapeutic method. Due to the high heterogeneity of AGC, it is particularly vital to reshaped the paradigm of gastric cancer therapy according to the characteristics of clinical classifications and molecular subtypes.

Indexed as

Hyperthermia, InducedStomach NeoplasmsChemotherapy, AdjuvantCombined Modality TherapyHumansHyperthermic Intraperitoneal Chemotherapycancer treatmentchemotherapyconversion therapygastric cancerHIPECmolecular-targeted therapy

Identifiers

PMID36780331
PMCPMC9478735
OpenAlexW4295939512

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.