Frontiers in nutrition · 2026
Development and validation of a prognostic nutritional-inflammatory-immune score and web-based dynamic nomogram for gastric cancer following radical gastrectomy: a multicenter study.
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Yu Changxin, Wang Zhen, Feng Shanshan, Cao Hongjuan, Gong Dandan, Zhang Lixia, Bo Wei, Guo Hao, Jiang Xiaoyang, Ma Xinghao
Аннотация
INTRODUCTION: Although nutritional, inflammatory, and immune status are key factors in gastric cancer (GC) prognosis, tools integrating these three dimensions for survival prediction remain limited. We developed and internally validated a prognostic nutritional-inflammatory-immune (PNII) score and a dynamic nomogram to predict overall survival (OS) after radical gastrectomy.
METHODS: A total of 841 patients from five centers who underwent radical gastrectomy were randomly divided into a training cohort (n = 588) and an internal validation cohort (n = 253). The PNII score was constructed from 12 candidate preoperative biomarkers using LASSO Cox regression. A prognostic nomogram integrating the PNII score with clinicopathological variables was developed and internally validated.
RESULTS: The PNII score, comprising nutritional, inflammatory, and immune markers, was identified as an independent prognostic factor. High PNII scores were associated with adverse tumor characteristics and poorer OS. The nomogram incorporating PNII, age, pT stage, pN stage, and CA125 achieved a C-index of 0.754 in both cohorts and outperformed the base clinical model without PNII (ΔAUC = 0.014; DeLong p = 0.0325). Time-dependent ROC analysis yielded 5-year AUCs of 0.831 (training) and 0.823 (validation), and decision curve analysis indicated net clinical benefit.
CONCLUSION: The PNII-based dynamic nomogram may serve as a promising postoperative risk-stratification tool for patients with GC. Independent external validation and prospective clinical evaluation are required before routine clinical use.
METHODS: A total of 841 patients from five centers who underwent radical gastrectomy were randomly divided into a training cohort (n = 588) and an internal validation cohort (n = 253). The PNII score was constructed from 12 candidate preoperative biomarkers using LASSO Cox regression. A prognostic nomogram integrating the PNII score with clinicopathological variables was developed and internally validated.
RESULTS: The PNII score, comprising nutritional, inflammatory, and immune markers, was identified as an independent prognostic factor. High PNII scores were associated with adverse tumor characteristics and poorer OS. The nomogram incorporating PNII, age, pT stage, pN stage, and CA125 achieved a C-index of 0.754 in both cohorts and outperformed the base clinical model without PNII (ΔAUC = 0.014; DeLong p = 0.0325). Time-dependent ROC analysis yielded 5-year AUCs of 0.831 (training) and 0.823 (validation), and decision curve analysis indicated net clinical benefit.
CONCLUSION: The PNII-based dynamic nomogram may serve as a promising postoperative risk-stratification tool for patients with GC. Independent external validation and prospective clinical evaluation are required before routine clinical use.