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<p>Gastric cancer, a leading cause of cancer-related mortality globally, lacks robust biomarkers for comprehensive prognosis. Accordingly, we examined the prognostic utility of combining the albumin-prealbumin-globulin ratio (APGR) with mid-arm circumference (MAC) for assessing survival, malnutrition, and metastasis in gastric cancer. A multicenter cohort comprising 1,803 patients with gastric cancer was categorized into three groups based on APGR and MAC values: normal, moderate-risk, and high-risk grades. Associations with overall survival (OS), malnutrition, and metastasis were evaluated using Cox proportional hazard regression and logistic regression analyses. Normal grade patients exhibited the highest OS (68.6%), followed by those with medium-risk (53.9%) and high-risk (39.9%) grades (<i>P</i> &lt; 0.001). Normal grade individuals had a 50% lower mortality risk (Hazard ratio [HR], 0.500, 95% confidence interval [CI]: 0.411–0.609; <i>P</i> &lt; 0.001) than high-risk grade patients, with moderate-risk grade patients demonstrating a 27.2% reduction (HR, 0.728, 95% CI: 0.617–0.860; <i>P</i> &lt; 0.001). Normal grade independently predicted a reduced risk of malnutrition (Odds ratio [OR], 0.249, 95% CI: 0.188–0.329; <i>P</i> &lt; 0.001) and lower odds of metastasis (OR, 0.477, 95% CI: 0.324–0.701; <i>P</i> &lt; 0.001). The composite index exhibited better discriminative ability (C-index = 0.595) than APGR (0.572) and MAC (0.558). Subgroup analyses revealed excellent prognostic discriminative ability across all TNM stages and sex subgroups, with sensitivity analysis, excluding early mortality, confirming the robustness of these findings. By integrating serological and anthropometric parameters, this composite index offers a clinically actionable framework for risk stratification in gastric cancer, improving the prognostic accuracy for survival, malnutrition, and metastasis. Its adoption can guide personalized interventions and improve clinical outcomes.</p>

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Integrating visceral protein ratios and mid-arm circumference predicts survival and malnutrition in gastric cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月18日

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  • Shulin Xian,
  • Bopei Li,
  • Pei Zhong,
  • Shuyao Wang,
  • Xingan Qin,
  • Hanping Shi,
  • Hailun Xie

摘要

Gastric cancer, a leading cause of cancer-related mortality globally, lacks robust biomarkers for comprehensive prognosis. Accordingly, we examined the prognostic utility of combining the albumin-prealbumin-globulin ratio (APGR) with mid-arm circumference (MAC) for assessing survival, malnutrition, and metastasis in gastric cancer. A multicenter cohort comprising 1,803 patients with gastric cancer was categorized into three groups based on APGR and MAC values: normal, moderate-risk, and high-risk grades. Associations with overall survival (OS), malnutrition, and metastasis were evaluated using Cox proportional hazard regression and logistic regression analyses. Normal grade patients exhibited the highest OS (68.6%), followed by those with medium-risk (53.9%) and high-risk (39.9%) grades (P < 0.001). Normal grade individuals had a 50% lower mortality risk (Hazard ratio [HR], 0.500, 95% confidence interval [CI]: 0.411–0.609; P < 0.001) than high-risk grade patients, with moderate-risk grade patients demonstrating a 27.2% reduction (HR, 0.728, 95% CI: 0.617–0.860; P < 0.001). Normal grade independently predicted a reduced risk of malnutrition (Odds ratio [OR], 0.249, 95% CI: 0.188–0.329; P < 0.001) and lower odds of metastasis (OR, 0.477, 95% CI: 0.324–0.701; P < 0.001). The composite index exhibited better discriminative ability (C-index = 0.595) than APGR (0.572) and MAC (0.558). Subgroup analyses revealed excellent prognostic discriminative ability across all TNM stages and sex subgroups, with sensitivity analysis, excluding early mortality, confirming the robustness of these findings. By integrating serological and anthropometric parameters, this composite index offers a clinically actionable framework for risk stratification in gastric cancer, improving the prognostic accuracy for survival, malnutrition, and metastasis. Its adoption can guide personalized interventions and improve clinical outcomes.