Wang LJ, Lei CL, Wang TA, Lin ZF, Feng SJ, Wei T, Li YQ, Shen MR, Li Y, Liao LF. Prognostic value of the preoperative systemic immune-inflammation nutritional index in patients with gastric cancer. World J Clin Oncol 2025; 16(4): 102294 [DOI: 10.5306/wjco.v16.i4.102294]
Corresponding Author of This Article
Liu-Feng Liao, Department of Pharmacy, Guangxi Medical University Cancer Hospital, No. 71 Heji Road, Qingxiu District, Nanning 530021, Guangxi Zhuang Autonomous Region, China. lcyxllf@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Li-Jing Wang, Ting-An Wang, Shi-Jie Feng, Tao Wei, Yan-Qin Li, Meng-Ru Shen, Yan Li, Liu-Feng Liao, Department of Pharmacy, Guangxi Medical University Cancer Hospital, Nanning 530021, Guangxi Zhuang Autonomous Region, China
Cai-Lu Lei, Zhi-Feng Lin, School of Pharmaceutical Science, Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China
Co-corresponding authors: Yan Li and Liu-Feng Liao.
Author contributions: Wang LJ and Lei CL contributed equally to this manuscript as co-first author. Wang LJ and Wang TA collected the data; Lei CL wrote the paper; Liao LF and Li Y reviewed the paper and they contributed equally to this manuscript as co-corresponding authors; Feng SJ, Wei T, Shen MR, and Li YQ developed the methodology; Lin ZF and Liao LF analyzed the study data through statistics software. All authors contributed to the article and approved the submitted version.
Supported by the Scientific Research Project of Hospital Pharmacy of Guangxi Pharmaceutical Association in 2022, No. GXYXH1-202202.
Institutional review board statement: The study was reviewed and approved by the ethics committee of Guangxi Medical University Cancer Hospital Institutional Review Board, approval No. KY2024869.
Informed consent statement: Written informed consent for participation was not required for this study in accordance with national legislation and institutional requirements.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The raw data supporting the conclusions of this article will be made available by the authors without undue reservation.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Liu-Feng Liao, Department of Pharmacy, Guangxi Medical University Cancer Hospital, No. 71 Heji Road, Qingxiu District, Nanning 530021, Guangxi Zhuang Autonomous Region, China. lcyxllf@163.com
Received: October 14, 2024 Revised: December 4, 2024 Accepted: January 21, 2025 Published online: April 24, 2025 Processing time: 163 Days and 6.6 Hours
Abstract
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.
Core Tip: A retrospective analysis was conducted on the clinical data of patients with gastric cancer (GC) who underwent surgical treatment at the Cancer Hospital of Guangxi Medical University between January 2010 and December 2018. Receiver operating characteristic curves were used to evaluate and compare the prognostic ability of nutritional risk index, prognostic nutritional index, and systemic immune-inflammatory-nutritional index (SIINI). 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). Multifactorial analysis indicated that SIINI was an independent risk factor for the prognosis of patients with GC.
Citation: Wang LJ, Lei CL, Wang TA, Lin ZF, Feng SJ, Wei T, Li YQ, Shen MR, Li Y, Liao LF. Prognostic value of the preoperative systemic immune-inflammation nutritional index in patients with gastric cancer. World J Clin Oncol 2025; 16(4): 102294
According to the National Cancer Center of China, the latest data from 2022 revealed that gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related deaths in China[1]. Globally, GC is the fifth most prevalent cancer and the fourth leading cause of cancer-related mortality[2], posing a significant threat to public health. Surgical resection remains the primary treatment for GC; however, 50% of patients die within 5 years following radical surgery[3]. Although the preoperative tumor, node, metastasis (TNM) stage aids in determining suitable treatment strategies for patients with GC, the TNM stage alone does not accurately predict postoperative complications and patient survival[4]. Consequently, it is crucial to combine the TNM stage with reliable and effective indicators to more accurately predict patient survival.
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[5]. Consequently, nutritional indicators may serve as valuable prognostic predictors for patients with cancer. The prognostic nutritional index (PNI) is a widely used indicator for assessing the nutritional status of patients with cancer and has demonstrated strong prognostic predictive value in patients with cancer[6]. Similarly, the nutritional risk index (NRI), which is based on serum albumin (ALB) levels and body weight, serves as a biological indicator for evaluating the nutritional status of patients with cancer[7]. There is a significant correlation between NRI and clinical outcomes in various cancers, including GC[8].
Recent studies have highlighted the crucial role of the body’s inflammatory response, immunity, and nutritional status in the emergence and progression of tumors[9-11]. The systemic immune-inflammatory-nutritional index (SIINI) is a comprehensive indicator that assesses the immune, inflammatory, and nutritional conditions of the body, providing a more accurate reflection of the overall status of a patient before treatment. Although SIINI has proven to be an effective prognostic predictor for patients with non-small-cell lung cancer undergoing nonsurgical treatment[12,13], its role in predicting the prognosis of patients with GC remains unclear. This study examined the prognostic value of NRI, PNI, and SIINI in 803 postoperative patients with GC, aiming to provide a reference basis for postsurgical strategies and to enhance patient survival.
MATERIALS AND METHODS
Patients
Based on the inclusion and exclusion criteria, the clinical data of patients who underwent GC surgery at the Guangxi Medical University Cancer Hospital from January 2010 to December 2018 were collected and reviewed. In total, 803 cases were included in this study (Table 1).
Table 1 Baseline patient characteristics based on nutritional risk index, prognostic nutritional index and systemic immuno-inflammatory-nutritional index.
The criteria for patient inclusion were as follows: (1) Diagnosis of GC confirmed by preoperative pathology; (2) No prior treatments, such as radiotherapy, chemotherapy, or biotherapy, before surgery; (3) Absence of acute or chronic inflammation before surgery; (4) Surgery involving standard lymph node dissection; and (5) No preoperative blood transfusions. The exclusion criteria were as follows: (1) Loss of medical records or follow-up data; (2) Refusal of surgical treatment; (3) Preoperative hematological disorders; (4) Preoperative presence of other serious infectious diseases, autoimmune diseases, or serious cardio-cerebral and pulmonary diseases; and (5) Diagnosis of malignant tumors other than GC. Pathological stage was determined using the 8th edition of the Union for International Cancer Control/American Joint Committee on Cancer staging system[14], and pathological diagnosis and classification of GC were based on treatment guidelines established by the Japanese Gastric Cancer Association[15].
Data collection
The following data were collected: (1) General information, including age, gender, height, weight, and weight loss rate; (2) Hematological indices, such as neutrophil, platelet, and lymphocyte counts; (3) Biochemical indicators, including ALB and prealbumin levels; (4) Tumor markers, such as carcinoembryonic antigen (CEA), cancer antigen [carbohydrate antigen 125 (CA125), CA19-9, CA153], and alpha-fetoprotein; and (5) Tumor characteristics, including tissue type, plasma membrane infiltration, lymph node metastasis, TNM stage, postoperative complications, tumor size, and the extent of gastric resection. NRI, PNI, and SIINI were computed as follows: NRI = 1.489 × serum ALB + 0.417 × [present body weight/ideal body weight (kg) × 100], ideal body weight (kg) = height (cm) - 105; PNI = serum ALB + 5 × total lymphocyte count; SIINI = [neutrophil count × platelet count × hemoglobin/(lymphocyte count × body mass index × serum ALB level)].
Follow-up
Patients were followed up postoperatively every 3 months via telephone calls or outpatient visits. The observation cutoff time was defined as the time of the outcome event (death). The cutoff time was the actual date of death for patients who died. For patients who survived, the follow-up continued for up to 5 years, with a follow-up cutoff date of December 2023. Overall survival was calculated from the date of admission to diagnosis until the final follow-up cutoff date or the date of death.
Statistical analysis
Data analysis was conducted using R version 4.2.3. The area under the receiver operating characteristic (ROC) curve (AUC) was calculated using ROC curve analysis, and the optimal cutoff values for NRI, PNI, and SIINI were determined using the Youden index. The Pearson χ² test or Fisher exact test was used to compare different categories of categorical variables. Survival analysis was conducted using The Kaplan-Meier method, and differences in survival were assessed using the Log-Rank test. Univariate and multivariate analyses were conducted using the Cox proportional hazards regression model. A P value < 0.05 was considered statistically significant.
RESULTS
ROC analysis
The ROC curves revealed that the AUC for NRI was 0.559, with an optimal cutoff point of 99.7. For PNI, the AUC was 0.576 with an optimal cutoff point of 49.3. For SIINI, the AUC was 0.603, with an optimal cutoff point of 103.0. The sensitivity and specificity were 0.6 and 0.5 for NRI, 0.7 and 0.4 for PNI, and 0.4 and 0.7 for SIINI (Figure 1). The AUC of SIINI (0.603) was higher than those of NRI (0.559) and PNI (0.576), indicating that SIINI is a more accurate predictor of prognosis in patients undergoing surgery for GC than NRI and PNI.
Figure 1 Receiver operating characteristic curves of nutritional risk index, prognostic nutritional index, and systemic immune-inflammatory-nutritional index for predicting the prognosis of gastric cancer patients.
ROC: Receiver operating characteristic; NRI: Nutritional risk index; PNI: Prognostic nutritional index; SIINI: Systemic immune-inflammatory-nutritional index; AUC: Area under the receiver operating characteristic curve.
Baseline characteristics of patients
After screening, a total of 803 patients were enrolled in this study, comprising 543 (67.6%) males and 260 (32.4%) females, aged 22-87 years. Table 1 presents the clinicopathological characteristics of the patients. Based on the determined optimal cutoff points, patients with NRI ≥ 99.7, PNI ≥ 49.3, and SIINI ≥ 103.0 were categorized into the high NRI group (301 cases), high PNI group (313 cases), and high SIINI group (243 cases), respectively. Conversely, patients with NRI < 99.7, PNI < 49.3, and SIINI < 103.0 were assigned to the low NRI group (502 cases), low PNI group (490 cases), and low SIINI group (560 cases), respectively.
This study revealed that NRI was significantly associated with gender, age, weight ratio, CEA, CA19-9, alpha-fetoprotein, TNM stage, type of surgery, serous membrane infiltration, extent of gastric resection, clinical stage, hemoglobin, prealbumin, and serum ALB (P < 0.05). PNI was significantly associated with age, weight, CEA, CA125, CA19-9, TNM stage, type of surgery, surgical method, serous membrane infiltration, clinical stage, hemoglobin, prealbumin, and serum ALB (P < 0.05). SIINI was associated with weight, CEA, CA125, CA19-9, TMN stage, type of surgery, serous membrane infiltration, clinical stage, peritoneal metastasis, prealbumin, and serum ALB (P < 0.05) (Table 1).
Prognostic value of NRI, PIN, and SIINI
The median follow-up period was 33.06 months, and the mortality rates at the 1st, 2nd, and 5th years of follow-up were 23.9%, 35.3%, and 37.0%, respectively. Among male postoperative patients with GC, those in the high NRI group had a significantly better survival rate compared with those in the low NRI group (P < 0.0037). Similarly, patients in the high PNI group exhibited significantly better survival rates than those in the low PNI group (P < 0.0001). In addition, survival rates were significantly higher in the low SIINI group than in the high SIINI group for men (P < 0.0001) and women (P < 0.0004) after GC surgery (Figure 2).
Figure 2 Nutritional risk index, prognostic nutritional index, and systemic immune-inflammatory-nutritional index correlate with survival in gastric cancer patients.
NRI: Nutritional risk index; PNI: Prognostic nutritional index; SIINI: Systemic immune-inflammatory-nutritional index.
Univariate and multivariate analyses of factors affecting patient prognosis
Univariate Cox proportional hazards regression analysis revealed that CA125, CA19-9, TNM stage, type of surgery, complications, serous membrane infiltration, extent of gastric resection, clinical stage, peritoneal metastasis, NRI, PNI, and SIINI were significantly associated with patient prognosis (P < 0.05) (Table 2). Multifactorial analysis of factors with P < 0.2 from the univariate analysis indicated that CA19-9, complications, clinical stage, peritoneal metastasis, and SIINI were independent risk factors influencing the prognosis of patients with postoperative GC (P < 0.05) (Table 2).
Table 2 Univariate and multivariate Cox regression analysis of the associations between clinical parameters and overall survival in patients with gastric cancer, n (%).
Variable
n
HR (univariate analysis)
HR (multivariate analysis)
SIINI
mean ± SD
114.5 ± 184.3
1.00 (1.00-1.00, P = 0.356)
Gender
Female
260 (32.4)
Male
543 (67.6)
1.00 (0.77-1.30, P = 0.993)
Age
0-51
306 (38.1)
52-62
267 (33.3)
1.19 (0.88-1.60, P = 0.267)
1.04 (0.75-1.43, P = 0.833)
≥ 63
230 (28.6)
1.31 (0.97-1.77, P = 0.074)
1.27 (0.92-1.76, P = 0.145)
Weight ratio
Decrease
246 (30.6)
Stay
381 (47.4)
1.08 (0.82-1.42, P = 0.595)
0.93 (0.68-1.27, P = 0.655)
Increase
176 (21.9)
0.69 (0.48-1.01, P = 0.054)
0.81 (0.49-1.36, P = 0.431)
History of stomach
None/unknown
710 (88.4)
Yes
93 (11.6)
1.32 (0.92-1.89, P = 0.133)
1.03 (0.70-1.53, P = 0.874)
History of surgery
No
797 (99.3)
Yes
6 (0.7)
3.97 (1.27-12.42, P = 0.018)
3.49 (1.02-11.90, P = 0.046)
CEA
Normal
667 (83.1)
High
136 (16.9)
1.36 (1.00-1.85, P = 0.051)
0.76 (0.54-1.06, P = 0.104)
CA125
Normal
741 (92.3)
High
62 (7.7)
2.94 (2.01-4.28, P < 0.001)
1.74 (1.14-2.65, P = 0.010)
CA19-9
Normal
682 (84.9)
High
121 (15.1)
2.28 (1.70-3.04, P < 0.001)
1.60 (1.18-2.16, P = 0.003)
CA153
Normal
778 (96.9)
High
25 (3.1)
1.15 (0.57-2.32, P = 0.701)
AFP
Normal
778 (96.9)
High
25 (3.1)
0.88 (0.42-1.87, P = 0.746)
Pre-tissue
Adenocarcinoma
779 (97.0)
Other/unknown
24 (3.0)
1.37 (0.68-2.76, P = 0.384)
TNM
Early stage
104 (13.0)
Interim stage
264 (32.9)
1.89 (1.15-3.12, P = 0.013)
0.98 (0.58-1.67, P = 0.949)
Advanced stage
435 (54.2)
2.48 (1.54-4.00, P < 0.001)
1.03 (0.61-1.72, P = 0.925)
Surgery way
Radical operation
725 (90.3)
Non-radical surgery
78 (9.7)
3.31 (2.32-4.72, P < 0.001)
1.56 (0.86-2.84, P = 0.143)
Surgery method
Open heart surgery
289 (36.0)
Laparoscopic surgery
514 (64.0)
1.05 (0.81-1.37, P = 0.702)
Complication
No
687 (85.6)
Yes
116 (14.4)
1.49 (1.08-2.06, P = 0.015)
1.61 (1.14-2.26, P = 0.006)
Tumor location
Upper/central
232 (28.9)
Lower section
571 (71.1)
0.79 (0.61-1.02, P = 0.073)
1.14 (0.82-1.59, P = 0.446)
Serous infiltration
No/suspected tumour infiltration
239 (29.8)
Tumour infiltration
564 (70.2)
2.84 (2.03-3.97, P < 0.001)
1.35 (0.94-1.95, P = 0.105)
Gastric resection scope
Total gastrectomy
196 (24.4)
Partial gastrectomy
607 (75.6)
0.61 (0.46-0.79, P < 0.001)
0.71 (0.50-1.01, P = 0.058)
Clinical staging
I
143 (17.8)
II
140 (17.4)
5.95 (2.49-14.24, P < 0.001)
3.69 (1.50-9.06, P = 0.004)
III
416 (51.8)
12.28 (5.44-27.75, P < 0.001)
6.29 (2.67-14.86, P < 0.001)
IV
104 (13.0)
29.69 (12.73-69.25, P < 0.001)
10.24 (3.83-27.38, P < 0.001)
Peritoneal metastasis
No
695 (86.6)
Yes
108 (13.4)
8.06 (6.20-10.48, P < 0.001)
6.06 (4.60-7.98, P < 0.001)
Hb level
Normal
441 (54.9)
Low
346 (43.1)
1.13 (0.89-1.45, P = 0.317)
High
16 (2.0)
0.52 (0.16-1.62, P = 0.256)
PA
Normal
464 (57.8)
Low
333 (41.5)
High
6 (0.7)
ALB
Normal
627 (78.1)
Low
166 (20.7)
1.26 (0.95-1.68, P = 0.108)
0.94 (0.67-1.31, P = 0.704)
High
10 (1.2)
1.70 (0.63-4.57, P = 0.296)
1.45 (0.49-4.31, P = 0.505)
NRI ROC
Low
502 (62.5)
High
301 (37.5)
0.68 (0.52-0.89, P = 0.005)
1.29 (0.85-1.94, P = 0.229)
PNI ROC
Low
490 (61.0)
High
313 (39.0)
0.60 (0.46-0.79, P < 0.001)
0.76 (0.54-1.06, P = 0.103)
SIINI ROC
Low
560 (69.7)
High
243 (30.3)
2.10 (1.64-2.69, P < 0.001)
1.65 (1.26-2.16, P < 0.001)
DISCUSSION
GC is a common malignant tumor of the gastrointestinal tract and a major cause of cancer-related deaths worldwide[16]. Early diagnosis and prompt treatment are crucial for effective treatment and follow-up of the disease. For patients with GC undergoing gastrectomy, pathological TNM staging is a key criterion for predicting prognosis and guiding treatment decisions. However, the survival outcomes of patients with GC vary even at the same disease stage because TNM staging only reflects the biological characteristics of the tumor and does not account for the nutritional status of the patient or the inflammatory response of the tumor and the host[17]. Thus, it is important to integrate TNM staging with additional stable and reliable indicators to more comprehensively analyze and predict patient survival.
To assess the relationship between nutrition and postoperative problems, some studies introduced the NRI, which is determined by ALB, present body weight, and usual body weight[18,19]. First defined by Buzby et al[20] in 1980, the PNI is primarily computed by counting peripheral blood lymphocytes and serum ALB. It can accurately represent a patient’s immunological and nutritional condition[21-23]. Its relevance in preoperative nutrition, immunological function, and surgical risk assessment of patients with gastrointestinal cancer was initially suggested by Flavill et al[24]. The SIINI is a new indicator that can comprehensively evaluate the inflammatory, immune, and nutritional levels of the body before treatment, and better reflect the overall state of the body before treatment[12].
This study examined the relationship of NRI, PNI, and SIINI with the prognosis of patients with GC. The correlation analysis indicated that NRI, PNI, and SIINI were associated with factors such as weight ratio, CEA, CA19-9, TNM stage, type of surgery, serous membrane infiltration, clinical stage, peritoneal metastasis, prealbumin, and serum ALB (Table 1). CEA and CA19-9 are commonly employed as key references to monitor tumor activity, whereas pathological features such as the TNM stage are closely associated with tumor progression. Furthermore, prealbumin and serum ALB levels provide insights into the nutritional status and immune-inflammatory response of patients. The relationship of NRI, PNI, and SIINI with clinicopathological factors in patients with GC highlights their potential as valuable biomarkers for prognosis assessment. This underscores the significance of considering the patient’s nutritional status and immune-inflammatory response in the overall management of GC.
This study further examined the value of NRI, PNI, and SIINI in predicting the prognosis of patients with GC. The ROC curve analysis demonstrated that SIINI was more accurate in predicting the prognosis of patients with GC than NRI and PNI (Figure 1). Three nutritional indices (NRI, PNI, and SIINI) were used to evaluate the survival of postoperative patients with GC. This analysis revealed that male postoperative patients with GC in the high NRI group had notably better survival rates than those in the low NRI group (P < 0.0037). Similarly, male postoperative patients with GC in the high PNI group had significantly better survival rates than those in the low PNI group (P < 0.0001). In addition, survival rates were significantly higher in the low SIINI group than in the high SIINI group in males (P < 0.0001) and females (P < 0.0004) (Figure 2). This result revealed that NRI, PNI, and SIINI are valuable prognostic indicators in male postoperative patients with GC, whereas only SIINI had strong prognostic significance in female patients. The limited number of female patients in this study may account for this discrepancy, indicating that a larger sample size is necessary for a more comprehensive analysis. Univariate analysis revealed that NRI, PNI, and SIINI were associated with prognosis (P < 0.05). However, multivariate analysis indicated that only SIINI was an independent prognostic factor for patients with GC (P < 0.05). These findings revealed that SIINI was more effective in differentiating the risk of long-term survival in postoperative patients with GC, which is consistent with existing literature[13]. This may be because the NRI and PNI indicators are limited to nutrition-related markers, such as serum ALB and body mass index, whereas the SIINI offers a comprehensive evaluation by integrating the patient’s immunity, inflammation, and nutrition.
Patients with cancer are often susceptible to malnutrition due to the high metabolism and rapid proliferation of tumor cells. In particular, patients with GC are more vulnerable to malnutrition because of the specific anatomical structure[25]. Malnutrition not only impairs treatment efficacy but also weakens immune function, thereby reducing the body’s resistance to tumors and accelerating tumor growth[26,27]. Several nutrition-related indicators, including serum ALB, body mass index, PNI, and NRI, are associated with the prognosis of patients with GC[8,28-30]. Monitoring and addressing malnutrition during treatment is crucial. In addition to nutrition, inflammation is a significant aspect of cancer[31]. High levels of inflammatory mediators can trigger an inflammatory cascade response and tissue atrophy, which may enhance tumor growth and metastasis[32,33]. Systemic inflammation causes pain, anorexia, cachexia, and reduced survival in patients with cancer, and it is also exacerbated by the nutritional status and hypoxia of the organism[34]. Consequently, the systemic inflammatory response plays a significant role in tumorigenesis and tumor prognosis of patients with tumors. There is also a close correlation between the immune status of the body and tumor development, and recent advancements in tumor immunotherapy aim to combat malignant tumors by activating the host immune system and providing passive or active immunity[35]. SIINI comprises peripheral blood neutrophils, platelets, lymphocyte counts, hemoglobin, serum ALB, and body mass index. It provides a comprehensive assessment of pre-treatment immune, inflammatory, and nutritional status and can better reflect the comprehensive status of a patient before treatment. SIINI is effective in predicting the prognosis of non-small-cell lung cancer[12]. The mechanisms by which SIINI predicts prognosis can be delineated as follows: (1) Lower ALB levels typically indicate malnutrition and poor nutritional status. Elevated SIINI scores reflect decreased serum ALB levels. A decrease in immune function is associated with reduced nutritional health, which can accelerate disease progression[36]; (2) A higher SIINI score reflects a higher platelet and/or neutrophil count relative to the lymphocyte count. Neutrophils significantly diminish the cytotoxic effects of lymphokine-activated killer cells, thereby suppressing the patient’s cellular immune response to the tumor. In addition, neutrophils release vascular endothelial growth factor, a pro-angiogenic factor linked to tumor infiltration, metastasis, and tumor development[37,38]. Furthermore, elevated platelet counts contribute to tumor growth by excessively producing vascular endothelial growth factor and platelet-derived growth factor. They also help the tumor system adhere to blood vessels, thereby enhancing the spread of metastatic cells[39,40]; and (3) A higher SIINI score indicates a relative decrease in lymphocyte counts, implying immunodeficiency or immunosuppression. This adversely affects patient prognosis and promotes tumor progression[41,42]. SIINI, to a certain extent, could be used as a reference for predicting the prognosis of GC patients and guiding individualized therapy strategy. In order to predict the prognosis and inform future treatment options, it is advised that patients with GC utilize SIINI to evaluate their general health prior to surgery.
Further research is required to address the limitations of this study. First, given the single-center retrospective design, the findings may have been influenced by selection bias. Second, the optimal critical values for NRI, PNI, and SIINI determined using the ROC curves in this study differed from those reported in other studies. To establish universal critical values and validate these findings, future research should include larger samples and prospective designs. In addition, this study’s limitation of collecting blood samples at only a single time point indicates the need for further research involving collecting blood samples at multiple time points to better understand the dynamics of SIINI in patients.
CONCLUSION
The SIINI index provides a thorough evaluation of the immune, nutritional, and inflammatory status of patients. In addition, it demonstrated greater accuracy in predicting the clinical outcomes of patients with GC than NRI and PNI. Moreover, SIINI has the characteristics of simplicity, ease of calculation, repeatability, universality, non invasiveness, and low cost, and is expected to become an indicator for evaluating the prognosis of GC patients. Therefore, SIINI is recommended as a standard biomarker to assess the comprehensive status of patients after GC surgery. Patients with SIINI values above 103.0 should be subjected to active intervention to achieve better therapeutic outcomes.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Gastroenterology and hepatology
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade B, Grade C
Novelty: Grade C, Grade C
Creativity or Innovation: Grade B, Grade C
Scientific Significance: Grade C, Grade C
P-Reviewer: Yu YW S-Editor: Wang JJ L-Editor: A P-Editor: Zhao YQ
Lin F, Xia W, Chen M, Jiang T, Guo J, Ouyang Y, Sun H, Chen X, Deng W, Guo L, Lin H. A Prognostic Model Based on Nutritional Risk Index in Operative Breast Cancer.Nutrients. 2022;14.
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