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

IF 1.2 Q4 ONCOLOGY

ecancermedicalscience Pub Date : 2025-02-13 eCollection Date: 2025-01-01 DOI:10.3332/ecancer.2025.1848

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

{"title":"Metastatic gastric cancer in fit patients-a practical algorithm of treatment sequencing from the Brazilian Group of Gastrointestinal Tumours (GTG).","authors":"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","doi":"10.3332/ecancer.2025.1848","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":11460,"journal":{"name":"ecancermedicalscience","volume":"19 ","pages":"1848"},"PeriodicalIF":1.2000,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12010126/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ecancermedicalscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3332/ecancer.2025.1848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

适合患者的转移性胃癌-巴西胃肠道肿瘤组（GTG）治疗测序的实用算法

生物标志物驱动疗法的最新进展显著改变了不可切除转移性胃癌（mGC）的治疗模式。然而，这些创新不仅带来了与可及性相关的问题，而且给治疗医生，特别是普通肿瘤学家，在为每位患者选择最合适的治疗方法和决定最佳测序策略时带来了复杂性。这篇手稿提出了一种由巴西胃肠道肿瘤组开发的算法，旨在为不可切除的mGC的管理提供直接的指导。该算法以适合患者的证据为基础，旨在简化临床实践中的治疗决策，假设没有访问和资源限制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊