Scholarlink

Objective <p>This study aimed to establish the G-Risk scoring system, a prognostic model based on inflammatory and tumor biomarkers, to enhance survival predictions for gastric cancer patients without lymphovascular invasion (LVI) and guide more tailored treatment strategies.</p> Methods <p>The key biomarkers associated with survival outcomes were identified using univariate and multivariate Cox regression analyses. These biomarkers were selected from a range of inflammatory and tumor markers to construct the G-Risk scoring system, which was specifically developed to improve prognostic accuracy in patients without LVI.</p> Results <p>The G-Risk score effectively stratified patients into high-risk and low-risk groups, achieving an AUC of 0.660, demonstrating strong predictive performance. Further multivariate analysis validated the G-Risk score as an independent prognostic factor with significant implications for patient survival.</p> Conclusion <p>The G-Risk score was successfully developed and validated as a reliable prognostic tool for gastric cancer patients without LVI. Its clinical implementation offers enhanced precision in assessing prognostic risk, facilitating personalized treatment planning, improving therapeutic outcomes, and reducing unnecessary medical interventions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development of the G-Risk scoring system utilizing inflammatory and tumor biomarkers to improve prognostic accuracy in gastric cancer patients without lymphovascular invasion

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月19日

查看全文
  • Eryu Liu,
  • Boran Xu,
  • Lei Shi,
  • Huannan Guo,
  • Chunfeng Li,
  • Lili Lv

摘要

Objective

This study aimed to establish the G-Risk scoring system, a prognostic model based on inflammatory and tumor biomarkers, to enhance survival predictions for gastric cancer patients without lymphovascular invasion (LVI) and guide more tailored treatment strategies.

Methods

The key biomarkers associated with survival outcomes were identified using univariate and multivariate Cox regression analyses. These biomarkers were selected from a range of inflammatory and tumor markers to construct the G-Risk scoring system, which was specifically developed to improve prognostic accuracy in patients without LVI.

Results

The G-Risk score effectively stratified patients into high-risk and low-risk groups, achieving an AUC of 0.660, demonstrating strong predictive performance. Further multivariate analysis validated the G-Risk score as an independent prognostic factor with significant implications for patient survival.

Conclusion

The G-Risk score was successfully developed and validated as a reliable prognostic tool for gastric cancer patients without LVI. Its clinical implementation offers enhanced precision in assessing prognostic risk, facilitating personalized treatment planning, improving therapeutic outcomes, and reducing unnecessary medical interventions.