Preoperative Prognostic Nutrition Index as a Prognostic Indicator of Survival in Elderly Patients Undergoing Gastric Cancer Surgery
- PMID: 34239325
- PMCID: PMC8259731
- DOI: 10.2147/CMAR.S316437
Preoperative Prognostic Nutrition Index as a Prognostic Indicator of Survival in Elderly Patients Undergoing Gastric Cancer Surgery
Abstract
Purpose: Gastric cancer is a common tumor type associated with nutritional and immune status. The aim of the current study was to investigate the prognostic value of a preoperative prognostic nutritional index (PNI), composed of nutritional factors and immune factors in elderly patients undergoing gastric cancer surgery.
Patients and methods: A total of 454 patients undergoing gastric cancer surgery were divided into two groups based on preoperative PNI scores: ≤45.1 (n = 307) and >45.1 (n = 147). Survival analysis was performed using the Kaplan-Meier method and Log rank tests. Univariate and multivariate analyses were conducted to identify independent prognostic factors using a Cox proportional hazards model.
Results: According to the X-tile program, the optimal cutoff value for predicting overall survival (OS) with the PNI was 45.1. The receiver operating characteristic analysis revealed that PNI exhibited 70.6% sensitivity and 56.5% specificity for predicting death during long-term follow-up. The cumulative incidence of postoperative 4-year mortality indicated that the risk of death increased significantly for PNI ≤45.1. In multivariate analysis, preoperative PNI was a significant independent predictor of mortality. In the age-stratified subgroup analysis, preoperative PNI was more sensitive for the old elderly subgroup than for the young elderly subgroup.
Conclusion: Preoperative PNI is a sensitive and specific prognostic predictor among elderly patients undergoing gastric cancer surgery.
Keywords: elderly patients; gastric cancer; prognostic nutritional index; radical gastrectomy.
© 2021 Zhang et al.
Conflict of interest statement
The authors report no conflicts of interest in this work.
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