Song Q, Niu HS. Correlation of systemic immune-inflammation and prognostic nutritional indices with pathological characteristics and prognosis in gastric cancer. World J Gastrointest Surg 2026; 18(5): 116701 [DOI: 10.4240/wjgs.v18.i5.116701]
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Song Q, Niu HS. Correlation of systemic immune-inflammation and prognostic nutritional indices with pathological characteristics and prognosis in gastric cancer. World J Gastrointest Surg 2026; 18(5): 116701 [DOI: 10.4240/wjgs.v18.i5.116701]
Author contributions: Song Q designed the study, wrote the manuscript, and revised the manuscript; Song Q and Niu HS collected and analyzed the data, participated in collection of the data. All authors approved the final version of the manuscript.
Institutional review board statement: Given the retrospective design and data anonymization, approval from the Ethics Review Committee is waived.
Informed consent statement: As the study used anonymous and pre-existing data, the requirement for the informed consent from patients was waived.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement:
No additional data are available.
Received: January 16, 2026 Revised: February 4, 2026 Accepted: March 10, 2026 Published online: May 27, 2026 Processing time: 131 Days and 5.2 Hours
Abstract
BACKGROUND
An ongoing need persists to identify reliable biological markers for gastric cancer (GC) prognosis, clinicopathological stratification, and survival prediction.
AIM
To determine the correlation of the Systemic Immune-Inflammation Index (SII) and Prognostic Nutritional Index (PNI) with clinicopathological characteristics and prognosis in patients with GC.
METHODS
This study included 107 patients with GC admitted to Inner Mongolia Baogang Hospital between February 2020 and February 2022. Clinical data including SII, PNI, and three-year prognosis were collected to evaluate the potential correlation of SII and PNI with the clinicopathological characteristics in patients with GC. Among the studied patients, receiver operating characteristic curve analysis assessed the prognostic predictive value of SII and PNI, and univariate and Cox multivariate regression analyses identified independent prognostic factors.
RESULTS
In patients with GC, SII levels were closely associated with maximum tumor diameter, invasion depth, metastases to lymph nodes, distant metastasis, tumor-node-metastasis staging, and carbohydrate antigen 199, and PNI levels were closely associated with differentiation degree, invasion depth, distant metastasis, tumor-node-metastasis staging, and carbohydrate antigen 199. The poor prognosis group (n = 37) exhibited notably higher SII levels and lower PNI levels relative to the good prognosis group (n = 70). Survival curve analysis revealed that in GC patients, high SII levels (≥ 607) were significantly correlated with lower three-year overall survival, while low PNI levels (< 44.5) were significantly correlated with lower three-year overall survival. According to the receiver operating characteristic curve, the area under the curve values for predicting GC prognosis using SII and PNI were 0.816 and 0.768, respectively, and the area under the curve of the two combined indices reached 0.866. Univariate and multivariate analyses showed that metastases to lymph nodes, distant metastasis, SII, and PNI were independent factors influencing three-year prognosis in patients with GC.
CONCLUSION
SII and PNI were effective biomarkers for predicting GC prognosis, and the two combined markedly improved predictive efficacy.
Core Tip: This study validated the correlation of the Systemic Immune-Inflammation Index and Prognostic Nutritional Index with clinicopathological characteristics and prognosis in patients with gastric cancer (GC). Analysis of the collected clinical data from patients with GC revealed that Systemic Immune-Inflammation Index and Prognostic Nutritional Index are effective biological markers for predicting GC prognosis, as they reflect patients’ clinicopathological characteristics and prognosis. The combination of the two further enhances prognostic and diagnostic efficacy, and both are also independent predictors for three-year overall survival in such patients.
Citation: Song Q, Niu HS. Correlation of systemic immune-inflammation and prognostic nutritional indices with pathological characteristics and prognosis in gastric cancer. World J Gastrointest Surg 2026; 18(5): 116701
Gastric cancer (GC) is the third leading cause of cancer death worldwide; key risk factors for GC involve Helicobacter pylori (H. pylori) infection, specific diet, and unhealthy lifestyle habits (e.g., consumption of salt-cured foods, alcohol abuse, and smoking)[1,2]. Global epidemiological data indicate approximately 1 million new GC cases and nearly 700000 associated deaths annually, with increasing early-onset incidence among individuals under 50 years of age[3]. Most patients infected with H. pylori remain asymptomatic, but the infection may progressively lead to gastritis, followed by gastroduodenal ulcer development and, ultimately, GC[4]. GC progression is complex and is associated with driver genes, chronic inflammation caused by H. pylori infection, malignant ascites, and immunosuppression[5]. Treatment options for patients with GC include radical surgical resection, neoadjuvant therapy, and chemotherapy. Although these treatments contribute to improved survival outcomes and quality of life, overall prognostic improvement remains limited[6]. Once patients with GC develop tumor metastasis, the prognosis becomes poor, with five-year overall survival (OS) below 10%[7]. Reliable biological markers for predicting GC prognosis remain unexplored. Systemic Immune-Inflammation Index (SII) and Prognostic Nutritional Index (PNI), respectively, reflect the systemic inflammatory response and nutritional status of the body; SII and PNI are indicators derived from conventional hematological parameters through distinct formulas, showing certain potential in cancer diagnosis and prognosis prediction[8,9]. Ding et al[9] indicated that low-cost stratification based on SII-PNI scores can aid the prediction of tumor response and prognosis in locally advanced GC. Ding et al[10] reported that the combined use of the two indices predicts imatinib neoadjuvant therapy efficacy and relapse-free survival in patients with locally advanced gastrointestinal stromal tumors. Ni et al[11] applied SII and PNI in patients with breast cancer undergoing neoadjuvant chemotherapy to help identify high-risk populations with no response to treatments and predict efficacy.
This study hypothesized that SII and PNI were significantly associated with clinicopathological characteristics and prognosis in patients with GC and may be used to differentiate such characteristics and predict survival outcomes to some extent.
MATERIALS AND METHODS
Patient information
Inclusion criteria: Individuals with GC diagnosed by endoscopy and pathological biopsy[12]; individuals who received surgery followed by standardized treatment (with consistent adjuvant therapy regimens); individuals who did not receive neoadjuvant chemotherapy and antineoplastic drugs before admission; individuals with no history of non-steroidal anti-inflammatory drugs, other immunosuppressants, or hormonal drugs in the past six months; individuals with a life expectancy of at least three months; individuals with complete clinical data.
Exclusion criteria: Individuals with residual GC; individuals who died due to non-tumor causes; individuals complicated with other malignant tumors; pregnant or lactating women; individuals complicated with other serious infectious diseases or autoimmune diseases; individuals complicated with serious liver or kidney insufficiency; individuals with cardiovascular and cerebrovascular diseases, diabetes mellitus, or serious cardiovascular, cerebrovascular, and pulmonary diseases; individuals with recent blood transfusion; individuals with hematological diseases.
In this study, 107 GC patients admitted to Inner Mongolia Baogang Hospital from February 2020 to February 2022 were strictly screened and enrolled as study subjects against the above inclusion and exclusion criteria.
Methods
Clinicopathological data were collected from patients before surgery: Gender, age, maximum tumor diameter, differentiation degree, tumor location, Borrmann type, invasion depth, metastases to lymph nodes, distant metastasis, tumor-node-metastasis (TNM) staging, carbohydrate antigen 199 (CA199), carcinoembryonic antigen (CEA), neutrophil, platelet, and lymphocyte counts, and serum albumin. All biochemical markers were obtained from 5 mL of serum collected from the patient’s fasting elbow vein at 8:00 one day before surgery. The product of neutrophil and platelet counts was then divided by lymphocyte count to calculate SII, and PNI was calculated by serum albumin value plus five times lymphocyte count.
Follow-up
The follow-up period lasted for three years. Patients were mainly followed by telephone contact and outpatient visits. OS represents the duration from the date of pathological diagnosis to the date of last follow-up or death, calculated in months.
Statistical analysis
The SII and PNI values in predicting GC prognosis were evaluated using the receiver operating characteristic (ROC) curve. The Kaplan-Meier method was applied to plot survival curves, with the log-rank test for inter-group comparisons. Independent factors influencing GC prognosis were identified with univariate and multivariate Cox analyses. A multicollinearity test was performed via linear regression analysis. A variance inflation factor (VIF) > 10 or a tolerance < 0.1 indicates severe multicollinearity; 5 < VIF ≤ 10 indicates moderate multicollinearity; a VIF ≤ 5 is often considered to indicate no significant multicollinearity. Enumeration data were expressed in n (%), with the χ2 test for inter-group comparisons; measurement data were expressed in mean ± SD, with inter-group comparisons using the independent sample t-test and comparisons among three groups using the one-way analysis of variance. SPSS 22.0 statistical software was utilized for all data analyses, and GraphPad Prism 7.0 software was used for generating figures. A P < 0.05 was considered statistically significant.
RESULTS
Correlation of SII with clinicopathological characteristics
As shown in Table 1, in patients with GC, SII level was not closely related to gender, age, differentiation degree, tumor location, Borrmann type, or CEA (P > 0.05), but was closely related to maximum tumor diameter, invasion depth, metastases to lymph nodes, distant metastasis, TNM staging, and CA199 (P < 0.05).
Table 1 Correlation between Systemic Immune-Inflammation and clinical pathological characteristics of gastric cancer patients, mean ± SD.
Correlation of PNI with clinicopathological characteristics
As shown in Table 2, in patients with GC, PNI level was not closely related to gender, age, maximum tumor diameter, tumor location, Borrmann type, metastases to lymph nodes, or CEA (P > 0.05), but closely related to differentiation degree, invasion depth, distant metastasis, CA199, and TNM staging (P < 0.05).
Table 2 Correlation of Prognostic Nutritional Index and clinical pathological characteristics of gastric cancer patients, median (interquartile rage)/mean ± SD.
Potential correlation of SII and PNI with prognosis
Patients with GC were followed up for three years and were further classified into a good prognosis group (n = 70) and a poor prognosis group (n = 37). Figure 1 shows that the poor prognosis group had notably higher SII levels and lower PNI levels than the good prognosis group (all P < 0.001). Survival curves were plotted after patient grouping (high-level and low-level groups) according to the cutoff values of the two indicators for predicting prognosis. Significant associations were observed between high SII levels (≥ 607) and lower three-year OS (P = 0.004), and between low PNI levels (< 44.5) and lower three-year OS (P = 0.031).
Figure 1 Potential correlation of Systemic Immune-Inflammation Index and Prognostic Nutritional Index with prognosis in gastric cancer patients.
A: Systemic Immune-Inflammation Index levels in the good prognosis group (n = 70) and the poor prognosis group (n = 37); B: Prognostic Nutritional Index levels in the good prognosis group (n = 70) and the poor prognosis group (n = 37); C: Survival curve analysis of the correlation between Systemic Immune-Inflammation Index and 3-year overall survival in gastric cancer patients; D: Survival curve analysis of the correlation between Prognostic Nutritional Index and 3-year overall survival in gastric cancer patients. SII: Systemic Immune-Inflammation Index; PNI: Prognostic Nutritional Index.
Prognostic predictive value of SII and PNI
In patients with GC, the prognostic predictive value of SII and PNI was evaluated using the ROC curve (Figure 2 and Table 3). ROC analysis yielded area under the curves (AUCs) of 0.816 [95% confidence interval (CI): 0.734-0.898], 0.768 (95%CI: 0.674-0.861), and 0.866 (95%CI: 0.796-0.935) for SII, PNI, and the combined SII-PNI indices in predicting GC prognosis, respectively, with corresponding sensitivities of 86.49%, 81.08%, and 81.08%; specificities of 68.57%, 61.43%, and 84.29%; and optimal cutoffs of 607.00, 44.50, and 0.37.
Figure 2 Receiver operating characteristic curves of Systemic Immune-Inflammation Index and Prognostic Nutritional Index in predicting prognosis in gastric cancer patients.
SII: Systemic Immune-Inflammation Index; PNI: Prognostic Nutritional Index.
Table 3 Prognosis predictive value of Systemic Immune-Inflammation Index and Prognostic Nutritional Index in gastric cancer patients.
Analysis of factors influencing three-year prognosis in patients with GC
The univariate analysis revealed that the poor and good prognosis groups showed no remarkable difference in gender, age, maximum tumor diameter, differentiation degree, tumor location, Borrmann type, invasion depth, CA199, and CEA (P > 0.05), while metastases to lymph nodes, distant metastasis, and TNM staging were closely linked to prognosis (P < 0.05; Table 4).
Table 4 Univariate analysis of factors influencing 3-year prognosis in gastric cancer patients, n (%).
Table 5 presents the results of further analysis in which factors with significant differences in the univariate analysis, as well as SII and PNI, were incorporated into the Cox regression multivariate model. The findings indicated that metastases to lymph nodes [odds ratio (OR) = 2.589, 95%CI: 1.280-5.235], distant metastasis (OR = 2.771, 95%CI: 1.410-5.445), SII (OR = 1.005, 95%CI: 1.003-1.007), and PNI (OR = 0.947, 95%CI: 0.908-0.988) were independent factors influencing three-year prognosis in GC patients (P < 0.05), whereas TNM staging was not (P > 0.05).
Table 5 Cox multivariate analysis of factors influencing 3-year prognosis in gastric cancer patients.
As listed in Table 6, linear regression-based multicollinearity testing yielded VIF values below five for all independent variables, indicating an extremely low degree of multicollinearity.
Table 6 Multicollinearity test for variables included in the Cox regression model.
This study found that in patients with GC, SII levels were closely related to maximum tumor diameter, invasion depth, metastases to lymph nodes, distant metastasis, TNM staging, and CA199, and PNI levels were closely associated with differentiation degree, invasion depth, distant metastasis, TNM staging, and CA199, suggesting that both indices can be important comprehensive indicators for the biological aggressiveness of GC. Dai et al[13] reported that SII and PNI were closely related to metastases to lymph nodes in such patients, which differs from our current findings. Nevertheless, similar results were found in multiple studies. For example, Cao et al[14] suggested that before treatment, SII can serve as an auxiliary predictor for tumor invasion depth, metastases to lymph nodes, TNM staging, and prognosis in patients with GC. Sun et al[15] demonstrated that low PNI levels were significantly associated with worse OS, postoperative complications, and invasion depth in patients with tumors, and were also closely related to TNM staging in patients with colorectal cancer. Yang et al[16] reported that low PNI levels were closely associated with more advanced tumor characteristics in patients with GC, such as deeper tumor invasion depth, more advanced TNM staging, and positive vascular and lymphatic invasion. Liu et al[17] identified PNI as an independent predictor of distant metastasis in patients with GC, corroborating our findings. Elevated SII typically manifests as high neutrophil counts, elevated platelet levels, and low lymphocyte counts, indicating a pro-tumor, pro-inflammatory immune microenvironment. High neutrophil levels suppress cytotoxic T lymphocyte function, leading to immunosuppression[18]; elevated platelet levels may promote immune escape of tumor cells, thereby facilitating angiogenesis and metastasis[19]; while low lymphocyte counts often indicate persistent systemic inflammation, which may mediate signaling pathways such as nuclear factor kappa B to drive chronic inflammation[20]. Conversely, the low albumin and low lymphocyte status reflected by low PNI jointly shape a state of dual depletion in nutrition and immunity, typically associated with muscle wasting and immune dysfunction caused by the competitive consumption of nutrients by tumor cells[21].
The three-year follow-up analysis revealed that the three-year OS rate among 107 patients with GC was 65.42%, corroborating Ma et al’s findings[22]. Abnormally high SII levels and abnormally low PNI levels were significantly correlated with lower three-year OS in patients with GC. Shen et al[23] found that low SII levels were closely associated with greater survival benefit in advanced GC patients undergoing combined immunotherapy, similar to this study. Borda et al[24] found that GC patients with high PNI levels exhibited higher overall and specific survival rates, corroborating our findings. ROC analysis revealed that the AUC values for predicting GC prognosis using SII and PNI alone were 0.816 and 0.768, respectively, and the AUC increased to 0.866 when the two were combined, with high sensitivity (81.08%) and specificity (84.29%). Univariate and multivariate analyses showed that metastases to lymph nodes, distant metastasis, and SII were independent risk factors for three-year prognosis in patients with GC, while PNI was an independent protective factor for three-year prognosis. To eliminate the impact of multicollinearity, we performed VIF tests on all variables included in the Cox model and ultimately found that multicollinearity was not a significant issue. However, multivariate analysis indicated that TNM staging is not an independent prognostic factor. This may be because the prognostic information contained within TNM staging has likely been largely covered or replaced by more specific and robust indicators (particularly the two core components of TNM, i.e., metastasis to lymph nodes and distant metastasis, and novel inflammatory and nutritional markers such as SII and PNI). Jing et al[25] reported that SII and PNI were independent prognostic factors for radical gastrectomy in early-stage GC patients, corroborating our findings. Prior studies have made significant contributions to prognostic assessment in patients with GC. Du et al[26] demonstrated that the immune-inflammation-nutrition-tumor marker prognostic score constructed using PNI, SII, body mass index, Nutritional Risk Screening 2002, serum albumin, platelet count, D-dimer, CEA, and CA199 can serve as a precise predictor for cachexia and prognosis in patients with GC. Additionally, the Systemic Immune-Inflammation-Nutrition Index was considered an independent risk factor for prognosis in patients with GC, demonstrating greater potential as a prognostic assessment parameter than the nutritional risk index and PNI[27]. This study confirmed the independent prognostic value of SII and PNI in GC. Compared to composite scoring systems requiring multiple indicators (e.g., immune-inflammation-nutrition-tumor marker and Systemic Immune-Inflammation-Nutrition Index), SII and PNI offer advantages in simplicity of calculation and strong clinical accessibility, facilitating rapid assessment and dynamic monitoring. Furthermore, compared to traditional single-dimensional indicators such as the neutrophil-to-lymphocyte ratio and the controlling nutritional status, SII and PNI respectively provide more comprehensive reflections of systemic inflammatory status and combined nutritional-immune status. Moreover, even within models incorporating detailed pathological factors, these two markers continue to provide irreplaceable prognostic information, offering reliable guidance for implementing simpler tools in clinical practice to achieve precise prognostic stratification.
CONCLUSION
In summary, SII and PNI showed potential value in evaluating clinicopathological characteristics and prognosis in patients with GC. Specifically, elevated SII correlated with worse clinicopathological characteristics such as maximum tumor diameter, invasion depth, metastases to lymph nodes, distant metastasis, TNM staging, and CA199, as well as lower three-year OS. Conversely, low PNI was related to worse clinicopathological characteristics such as differentiation grade, invasion depth, distant metastasis, TNM staging, and CA199, as well as lower three-year OS. The combined SII-PNI use further improved the predictive performance for GC prognosis, and both were independent factors influencing the three-year OS in patients with GC.
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