Prognostic value of the preoperative systemic immune-inflammation nutritional index in patients with gastric cancer
Li-Jing Wang1, Cai-Lu Lei2, Ting-An Wang1
1Department of Pharmacy, Guangxi Medical University Cancer Hospital, Nanning 530021, Guangxi Zhuang Autonomous Region, China.
Background:
Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related deaths in China. Many patients with GC frequently experience symptoms related to the disease, including anorexia, nausea, vomiting, and other discomforts, and often suffer from malnutrition, which in turn negatively affects perioperative safety, prognosis, and the effectiveness of adjuvant therapeutic measures. Consequently, some nutritional indicators such as nutritional risk index (NRI), prognostic nutritional index (PNI), and systemic immune-inflammatory-nutritional index (SIINI) can be used as predictors of the prognosis of GC patients.
Aim:
To examine the prognostic significance of PNI, NRI, and SIINI in postoperative patients with GC.
Methods:
A retrospective analysis was conducted on the clinical data of patients with GC who underwent surgical treatment at the Guangxi Medical University Cancer Hospital between January 2010 and December 2018. The area under the receiver operating characteristic (ROC) curve was assessed using ROC curve analysis, and the optimal cutoff values for NRI, PNI, and SIINI were identified using the You-Review-HTMLden index. Survival analysis was performed using the Kaplan-Meier method. In addition, univariate and multivariate analyses were conducted using the Cox proportional hazards regression model.
Results:
This study included a total of 803 patients. ROC curves were used to evaluate the prognostic ability of NRI, PNI, and SIINI. The results revealed that SIINI had superior predictive accuracy. Survival analysis indicated that patients with GC in the low SIINI group had a significantly better survival rate than those in the high SIINI group (P < 0.05). Univariate analysis identified NRI [hazard ratio (HR) = 0.68, 95% confidence interval (CI): 0.52-0.89, P = 0.05], PNI (HR = 0.60, 95%CI: 0.46-0.79, P < 0.001), and SIINI (HR = 2.10, 95%CI: 1.64-2.69, P < 0.001) as prognostic risk factors for patients with GC. However, multifactorial analysis indicated that SIINI was an independent risk factor for the prognosis of patients with GC (HR = 1.65, 95%CI: 1.26-2.16, P < 0.001).
Conclusion:
Analysis of clinical retrospective data revealed that SIINI is a valuable indicator for predicting the prognosis of patients with GC. Compared with NRI and PNI, SIINI may offer greater application for prognostic assessment.
