Clinical Report: Nutritional and Inflammatory Biomarkers in Gastric Cancer

Overview

This study evaluates the predictive values of nutritional and inflammatory biomarkers, specifically the Prognostic Nutritional Index (PNI), Systemic Immune-inflammation Index (SII), and Creatinine to Cystatin C Ratio (CCR), in locally advanced gastric cancer (LAGC) patients undergoing neoadjuvant immunotherapy.

Background

Locally advanced gastric cancer (LAGC) poses a significant challenge in oncology due to its high mortality rates and variable treatment responses. Neoadjuvant immunotherapy combined with chemotherapy has emerged as a promising approach, yet optimizing patient selection remains critical. Identifying reliable biomarkers for predicting treatment outcomes can enhance personalized therapy and improve patient management.

Data Highlights

Key Findings

• Patients with pathological complete response (pCR) had significantly better overall survival (OS) and disease-free survival (DFS).
• Lower Systemic Immune-inflammation Index (SII) and higher Prognostic Nutritional Index (PNI) and Creatinine to Cystatin C Ratio (CCR) were associated with pCR.
• Restricted Cubic Spline analysis confirmed linear correlations between these indices and survival risks.
• Decision tree analysis identified a predictive model combining PNI, SII, CCR, and CA199 with an AUC of 0.917, indicating strong predictive ability.
• Nomogram models for OS and DFS demonstrated good calibration and discrimination.

Clinical Implications

Integrating nutritional and inflammatory biomarkers into clinical practice can enhance patient stratification for neoadjuvant immunotherapy in LAGC. These biomarkers may guide treatment decisions and improve patient outcomes by identifying those most likely to benefit from therapy, potentially leading to more personalized treatment approaches.

Conclusion

The study underscores the importance of nutritional and inflammatory biomarkers in predicting treatment response and survival in LAGC patients. Their integration into predictive models can facilitate personalized management strategies and inform future research directions.

Related Resources & Content

1. Gastric Cancer, Springer, 2019 -- The Role of Inflammatory and Nutritional Biomarkers in Predicting Survival Outcomes for Gastric Cancer Patients Undergoing Neoadjuvant Chemotherapy and D2 Lymphadenectomy
2. Frontiers in Immunology, 2026 -- An integrated SII-PNI immune-nutritional scoring system predicts efficacy and immune-related adverse events in locally advanced gastric cancer patients undergoing neoadjuvant immunotherapy
3. Frontiers in Immunology, 2026 -- Characterization of the tumor microenvironment in locally advanced gastric cancer and identification of spatially predictive biomarkers associated with beneficial neoadjuvant immunochemotherapy
4. FDA -- FDA approves durvalumab for resectable gastric or gastroesophageal junction adenocarcinoma
5. Frontiers in Immunology — Hematological biomarkers for predicting pathologic response to neoadjuvant immunochemotherapy and cycle optimization in locally advanced gastric cancer
6. NCCN Guidelines for Resectable Gastric/GEJ Adenocarcinoma
7. FDA approves durvalumab for resectable gastric or gastroesophageal junction adenocarcinoma | FDA
8. The prognostic value of systemic inflammation response index in digestive system carcinomas: a systematic review and meta-analysis | BMC Gastroenterology | Springer Nature Link