Prognostic predictive value of the preoperative systemic immunoinflammatory index combined with the neutrophil‑to‑lymphocyte ratio in patients with primary liver cancer undergoing transarterial chemoembolization
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- Published online on: June 27, 2025 https://doi.org/10.3892/ol.2025.15160
- Article Number: 414
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Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Primary liver cancer (PLC) is the third leading cause of cancer mortality, and has one of the worst 5-year survival rates worldwide. Epidemiological data estimate 905,700 cases and 830,200 associated deaths globally each year (1,2); therefore, PLC poses a serious threat to human life and health. According to the Guidelines for the Diagnosis and Treatment of Primary Liver Cancer (2024 Edition) (3), common treatments for PLC include percutaneous hepatic artery chemoembolization, hepatic resection, radiofrequency ablation, radiation therapy and liver transplantation, with hepatic resection serving as the primary treatment for PLC. However, most patients have progressed to the middle and late stages by the time of consultation, missing the best time for surgery. Transarterial chemoembolization (TACE), which causes minimal trauma and is characterized by strong targeting, is the preferred option for patients who cannot undergo surgical resection. Embolization can block the blood supply of liver tumors, and the local injection of antitumor drugs, which can control tumor growth, prompt their necrosis and shrinkage in order to improve patient prognosis (4). Clinical indicators of prognosis include α-fetoprotein, tumor stage, vascular tumor thrombosis and tumor size (5), but their predictive value is limited, and they do not meet clinical needs. In recent years, the systemic immunoinflammatory index (SII) and the neutrophil-to-lymphocyte ratio (NLR) have become the hotspots of clinical research and the most promising new prognostic indicators for various types of cancer, such as bladder (6), colorectal (7), lung (8) and prostate (9) cancer. Existing studies have confirmed that preoperative SII and NLR, respectively, are strong predictors of prognosis in patients with PLC (10–13). Therefore, changes in preoperative SII and NLR can predict the prognosis of patients with PLC. However, separate prognostic indicators have limitations, and the lack of efficient and powerful indicators that can predict PLC prognosis poses a clinical challenge. Therefore, in order to fill in the gaps in this area of research and guide clinical practice, the present study explored the value of preoperative SII combined with NLR in assessing the prognosis of patients with PLC through retrospective analysis.
Materials and methods
Approval
The present study received approval from the Medical Ethics Committee of Liuzhou Hospital of Traditional Chinese Medicine (Liuzhou, China), and all procedures involving human participants adhered to the principles outlined in the Declaration of Helsinki.
Patient selection
The clinical data of 311 patients diagnosed with PLC at Liuzhou Hospital of Traditional Chinese Medicine between March 2017 and October 2019 were retrospectively analyzed. A total of 122 patients with PLC met the inclusion criteria and had complete follow-up data. All patient data were derived from the electronic medical records of Liuzhou Traditional Chinese Medicine Hospital. Relevant records, encompassing clinical data of patients diagnosed with PLC between March 2017 and October 2019, were systematically accessed and extracted in November 2024.
The inclusion criteria were as follows: i) According to the relevant criteria in the Diagnostic Criteria for Primary Liver Cancer (14), the diagnosis was confirmed clinically, and the tumor was confirmed to be unresectable PLC by imaging; ii) the tumor diameter was ≤10 cm, and the number of tumors was ≤3; iii) there was no extra-hepatic metastasis; iv) the patients underwent percutaneous hepatic arterial chemoembolization and did not succumb during the perioperative period; v) the data on preoperative SII, NLR and clinicopathological features were complete; vi) the patient could be followed up normally for at least 3 months after the surgery with no omission of clinical data.
The exclusion criteria were as follows: i) Previous liver surgery; ii) a combination of malignant tumors other than PLC; iii) a combination of other acute or chronic diseases or immune system disorders; iv) long-term use of anti-inflammatory medications; v) an estimated survival time of <6 months; and vi) patients with incomplete or lost follow-up information.
Clinical data and calculations
The collected data included sex, age, smoking history, drinking history, platelet (PLT), neutrophil (NEUT), lymphocyte (LYM), albumin (ALB), total bilirubin (TBIL) and aspartate transaminase (AST) levels, SII, NLR, prognostic nutritional index (PNI), platelet-to-lymphocyte ratio (PLR), AST to platelet ratio index (APRI) and overall survival (OS). The formulae used were as follows: SII=N × P/L; and NLR=N/L. Where P, N and L were the absolute values of PLT count, absolute NEUT count and absolute LYM count, respectively, in the routine blood count (the first routine blood count during hospitalization).
Postoperative follow-up and survival records
All patients were followed up by outpatient follow-up, telephone follow-up or readmission, and survival was calculated at the time of the last follow-up visit [5 years (1,825 days) after surgery]. The median, longest and shortest follow-up periods were 466, 1,825 and 30 days, respectively. The follow-up period ended on October 18, 2024.
Statistical analysis
Statistical software SPSS 29.0 (IBM Corp.) was used for data processing and analysis. Measurements are expressed as the mean ± standard deviation, and comparisons between the two groups were made using the χ2 test. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to determine the optimal cut-off values for SII and NLR. Kaplan-Meier (K-M) survival curves were used to analyze the effect of SII and NLR on the survival time of patients with PLC. Univariate Cox proportional risk regression analysis was first performed to assess the prognostic significance of 15 clinical variables (including sex, drinking history, PLT, NEUT, LYM, AST, PLR, SII and NLR), followed by variance inflation factor (VIF) analysis to exclude variables with severe multicollinearity (VIF ≥10). The remaining variables (sex, drinking history, AST, SII and NLR) were then entered into the multivariate Cox regression model to evaluate their independent predictive value for patient prognosis. ROC curves were used in conjunction with these models to analyze the predictive efficacy of SII and NLR. P<0.05 was considered to indicate a statistically significant difference.
Results
Patient characteristics
A total of 103 men and 19 women with a mean age of 54.99 years (age range, 20–90 years) were included in the study. Among them, 60 patients were <55 years old and 62 patients were ≥55 years old. There were 70 patients with a history of smoking, 62 patients with a history of alcohol consumption, 52 patients without a history of smoking and 60 patients without a history of alcohol consumption. The baseline characteristics of the patients with PLC are listed in Table I.
ROC curve analysis of the SII and the NLR
The optimal cutoff values of 381.79 and 2.83 for SII and NLR, respectively, were derived from the ROC curves, and the patients were categorized into a high (SII ≥381.79; 77 cases) and a low SII subgroup (SI <381.79; 45 cases), and a high (NLR ≥2.83; 67 cases) and a low NLR subgroup (NLR <2.83; 55 cases), based on these. The sensitivity, specificity and AUC of SII, NLR and SII + NLR were evaluated using ROC curves, and the results showed that all of the aforementioned indices had a good prognostic predictive efficacy (Table II; Fig. 1).
 | Table II.Effect of preoperative SII, NLR and SII + NLR on the prognosis of patients with primary liver cancer. |
Comparison of clinical data
Differences in clinical profiles between the high and low SII and NLR groups were compared. The results revealed significant differences (P<0.05) in sex, drinking history, PLT, NEUT, AST, PLR and APRI in the SII group, but no significant differences in other clinical variables. Significant differences (P<0.05) in sex, drinking history, PLT, NEUT, LYM, AST, PLR and PNI were observed in the NLR group, but there were no significant differences in other clinical variables (Table III).
| Table III.Comparison of clinical data for SII [≥381.79 (n=77) vs. <381.79 (n=45)] or NLR [≥2.83 (n=67) vs. <2.83 (n=55)]. |
Prognostic value of the SII and NLR ratio
K-M survival curve analysis showed that patients in the high SII subgroup had significantly shorter survival times than those in the low SII subgroup (P<0.01; Fig. 2A). The survival time of patients in the high NLR subgroup was significantly shorter than that of patients in the low NLR subgroup (P<0.01; Fig. 2B). Patients in the combined high SII and high NLR subgroup exhibited the lowest OS time (P<0.01; Fig. 2C).
Univariate and multivariate analyses of prognostic factors
In the present study, 15 variables were selected for one-way Cox regression analysis. The results showed that sex, drinking history, PLT, NEUT, LYM, AST, PLR, SII and NLR had a significant effect on the OS of patients with PLC (P<0.05; Table IV). However, other clinical variables had no significant effect on OS. After excluding the variables that had no effect on OS in the univariate analysis, VIF analysis was performed to validate multicollinearity, using a threshold of 10 (VIF >10 indicating severe multicollinearity). Following exclusion of highly correlated variables with VIF ≥10 (PLT=13.08, NEUT=17.37, LYM=12.76 and PLR=18.28), the remaining variables (sex=1.056, drinking history=1.088, AST=1.093, SII=5.336 and NLR=5.281) all had VIF <10, confirming low multicollinearity risk. Multivariate Cox regression analysis of these variables revealed that drinking history, AST, SII, and NLR were independent risk factors for OS (Table IV).
Discussion
Inflammation plays an important role in tumor pathogenesis, progression and therapy, and can inhibit apoptosis, and promote angiogenesis and tumor cell metastasis by influencing the body's immune response. In the inflammatory microenvironment, a variety of cells play different roles. NEUTs release IL-6 and TNF-α, among others, which promote tumor angiogenesis, migration and invasion (15,16). LYMs, particularly cytotoxic T lymphocytes and natural killer cells, play a key role in the body's antitumor immune surveillance and killing mechanisms, and the alteration of their number and function affects tumor progression (17). The NLR can sensitively reflect the development of inflammation and the tendency of the body's immune response. He et al (18) found that a high NLR is also an unfavorable prognostic factor for patients with PLC. Guo et al (19) also confirmed this result. The aforementioned studies suggested that NLR is not only a common inflammatory marker, but also an effective prognostic indicator for malignant tumors. Meanwhile, the PLT count of patients with cancer also has a large impact on their prognosis. PLTs can interact with tumor cells to form PLT-tumor cell aggregates, which protect tumor cells from the body's immune system and contribute to intravascular adherence, migration and distant metastasis of tumor cells (20,21). SII is a systemic inflammatory marker used as an indicator to assess the inflammatory and immune status of an organism. The incorporation of PLT count into SII reflects the role of PLTs in inflammation. Li et al (22) demonstrated the value of preoperative SII in the prognostic assessment of PLC. Xin et al (23) pointed out that the OS time of the low SII group was significantly better than that of the high SII group. Based on the aforementioned information, both high SII and high NLR were considered risk factors for tumorigenesis and were combined in the present study.
To the best of our knowledge, the present study was the first to investigate the prognostic significance of SII combined with NLR in patients with PLC. The findings showed that both preoperative SII and NLR were significantly associated with patient prognosis, and that SII (HR, 1.001; 95% CI, 1.001–1.002; P<0.01) and NLR (HR, 0.873; 95% CI, 0.789–0.0996; P=0.008) were independent risk factors for PLC. Based on K-M survival curve analysis, patients with SII ≥381.79 combined with NLR ≥2.83 had the shortest OS time (P<0.01). A literature review revealed that the NLR cut-off value determined in the present study (cut off, 2.83) is very close to that reported by Öcal et al (24) (NLR, 2.77) and Wang et al (25) (NLR, 2.92). Öcal et al (24) confirmed that NLR (cut-off, 2.77) is a prognostic marker for patients with hepatocellular carcinoma (HCC) treated with sorafenib or radioembolization, while Wang et al (25) reported that high NLR (cut-off, 2.92) is associated with a poor prognosis in patients with resectable HCC. Meanwhile, the SII cut-off value identified in the present study (cut off, 381.79) is also highly similar to that found by Guo et al (19) and Xin et al (23). Guo et al (19) retrospectively studied the predictive value of preoperative SII for early recurrence after hepatic resection in patients with HBV-related HCC, discovering that high SII (SII ≥353.64) was associated with early postoperative recurrence in these patients. Xin et al (23) further verified that SII (cut off, 324.55) is an independent prognostic factor affecting the survival outcomes of patients with early-stage HCC. This fits with several previous studies emphasizing the importance of inflammatory indicators in tumor prognosis (26–29).
The present study established a combined preoperative SII and NLR assessment model with enhanced predictive efficacy. Previous investigations (4,22) predominantly focused on individual inflammatory indices (for example, SII or NLR) for tumor prognosis evaluation. Although such parameters demonstrate prognostic utility in colorectal cancer (7), HCC (11) and other malignancies, their limitations remain substantial. Single indices can only reflect isolated aspects of tumor immune-inflammatory microenvironments: NLR emphasizes NEUT-LYM equilibrium to indicate local inflammatory intensity (19), whereas SII incorporates PLT counts to reflect coagulation-inflammation interactions potentially influencing tumor metastasis (13). However, tumor progression involves multifaceted regulatory mechanisms that cannot be captured by unimodal indices monitoring dynamic immune-inflammatory network alterations. The present findings demonstrate that combined preoperative SII and NLR assessment effectively mitigates the inherent limitations of individual indices. Notably, the combined index achieved an AUC of 0.846 (P<0.01) compared with 0.843 and 0.836 for individual SII and NLR, respectively. Furthermore, Kaplan-Meier analysis enabled precise identification of high-risk cohorts (patients with SII ≥381.79 and NLR ≥2.83 showed the shortest OS times; P<0.01). Compared with the restricted prognostic discrimination of single indices in intermediate-risk patients, the combined model leverages integrated ‘inflammation-immunity-coagulation’ pathway information to significantly enhance predictive accuracy and risk stratification capacity. This comprehensive approach better reflects tumor microenvironment characteristics, providing clinicians with a more robust tool for preoperative evaluation, personalized treatment planning and prognostic prediction in patients with PLC.
Certain clinical studies have shown that there is also a close link between preoperative PNI and APRI, and tumor prognosis. Therefore, in the present study, data on preoperative PNI and APRI were also analyzed, but the results showed that PNI (HR, 0.976; 95% CI, 0.943–1.010; P=0.157; AUC=0.438) and APRI (HR, 0.872; 95% CI, 0.627–1.213; P=0.416; AUC=0.481) were not significantly associated with the prognosis of patients with PLC who were treated with transarterial chemoembolization. Furthermore, the male incidence in this study was significantly higher than the female incidence, which is consistent with findings from the studies by Wang et al (30), Karageorgos et al (31) and Liu et al (32). Wang et al (30) reported a 5:1 male-to-female ratio in Chinese patients with HCC, while Karageorgos et al (31) observed a 1.7:1 ratio in Greek patients with cirrhosis and HCC, and Liu et al (32) recorded a 3:1 ratio in American patients with HCC. This phenomenon can be attributed to potential mechanisms such as increased susceptibility to HBV infection in males (33), prolonged alcohol consumption (34) and activation of androgen-driven pathways that facilitate tumor proliferation (35). The geographical origin of the sample and patient population characteristics may also impact the results. Table III shows a significant association between sex and SII/NLR (males accounted for 92.2% in the high SII group and 92.5% in the high NLR group; P<0.01), reflecting a tendency for male patients to have higher SII and NLR values, which may explain the statistical significance of the sex variable in Table III.
The present study was not without its limitations. First, it was a retrospective study with a relatively limited sample source, which may have led to a degree of selection bias. Future prospective studies with multicenter and large samples are needed to further verify the reliability and stability of the present findings. Secondly, there are still a number of other potential influencing factors not included in the model of this study, which may intertwine with the immune-inflammatory response in the process of tumorigenesis and development, and jointly affect the prognosis of patients. Therefore, these factors should be included as comprehensively as possible in subsequent studies to construct a more complete prognostic model to improve the accuracy and comprehensiveness of the prognostic assessment of patients with PLC treated with TACE.
In conclusion, the present study found that sex, drinking history, PLT, NEUT, LYM, AST, PLR, SII and NLR influenced the prognosis of patients with PLC. Among these factors, drinking history, AST, SII and NLR were found to be independent risk factors affecting OS in patients with PLC. In addition, these findings showed that the combination of SII and NLR was more accurate than the use of SII or NLR alone.
Acknowledgements
Not applicable.
Funding
Funding: No funding was received.
Availability of data and materials
The data generated in the present study may be requested from the corresponding author.
Authors' contributions
MZ and QC contributed to the conception and design of the study. MZ wrote the original draft. KY, TM, YC, CZ and JiyZ collected and analyzed the data. JinZ, SC, MY, TZ and CC followed up the survival of patients, analysed the survival outcomes and optimised the linguistic expression of the article. MZ and QC confirm the authenticity of all the raw data. All authors helped conduct the study, and have read and approved the final manuscript.
Ethics approval and consent to participate
This study was performed in accordance with the Declaration of Helsinki Declaration of Helsinki and was approved by the Medical Ethics Committee of Liuzhou Hospital of Traditional Chinese Medicine (Liuzhou, China; initial review approval no. 2023JUL-KY-059-01; follow-up review approval no. 2023JUL-KY-059-02). Given the observational non-interference nature of this study, the Ethics Committee waived the requirement for informed consent.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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