Evidence map›Paper›PMID 40259898›Full record

ReviewEcancermedicalscience2025

Metastatic gastric cancer in fit patients-a practical algorithm of treatment sequencing from the Brazilian Group of Gastrointestinal Tumours (GTG).

Renata D'Alpino Peixoto, Gabriel Prolla, Anelisa Kruschewsky Coutinho, Julia Andrade de Oliveira, Virgilio Souza E Silva, Rachel Riechelmann, Juliana Florinda de Mendonça Rego, Victor Hugo Fonseca de Jesus, Rui Fernando Weschenfelder

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Ecancermedicalscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Renata D'Alpino PeixotoBC Cancer Agency, Vancouver, BC V5Z 4E6, Canada.
Gabriel ProllaOncoclínicas, Porto Alegre 90570-020, Brazil.
Anelisa Kruschewsky CoutinhoClínica AMO (DASA), Salvador 41950-640, Brazil.
Julia Andrade de OliveiraClínica AMO (DASA), Salvador 41950-640, Brazil.
Virgilio Souza E SilvaAC Camargo Cancer Center, São Paulo 01509-001, Brazil.
Rachel RiechelmannAC Camargo Cancer Center, São Paulo 01509-001, Brazil.
Juliana Florinda de Mendonça RegoOncocentro (DASA), Natal 59020-340, Brazil.
Victor Hugo Fonseca de JesusOncoclínicas, Florianopolis 88015-020, Brazil.
Rui Fernando WeschenfelderHospital Moinhos de Vento, Porto Alegre 90035-000, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advancements in biomarker-driven therapies have significantly transformed the treatment paradigm for unresectable metastatic gastric cancer (mGC). These innovations, however, have introduced not only issues related to accessibility but also complexities for treating physicians, particularly general oncologists, in selecting the most appropriate treatment for each patient and deciding on the best sequencing strategy. This manuscript presents an algorithm developed by the Brazilian Group of Gastrointestinal Tumours, designed to provide straightforward guidance in the management of unresectable mGC. This algorithm, grounded in evidence for fit patients, aims to streamline therapeutic decision-making in clinical practice, assuming the absence of access and resource constraints.

Indexed as

algorithmgastroesophageal cancermetastatic gastric cancer

Identifiers

PMID40259898
PMCPMC12010126

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.