Zhou PC, Huang R, Wang HT, Yang J, Peng JD, Fu ZX, Liao WJ, Ma HQ, Wu LQ, Li EL. Gamma-glutamyl transferase-to-lymphocyte ratio as a prognostic marker in patients with hepatocellular carcinoma undergoing hepatectomy. World J Gastrointest Surg 2025; 17(2): 98578 [DOI: 10.4240/wjgs.v17.i2.98578]
Corresponding Author of This Article
En-Liang Li, DPhil, Doctor, Department of General Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1 Minde Road, Donghu District, Nanchang 330008, Jiangxi Province, China. lienliangyx@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/
Peng-Cheng Zhou, Jun Yang, Jian-Dong Peng, Zi-Xuan Fu, Wen-Jun Liao, Lin-Quan Wu, En-Liang Li, Department of General Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang 330008, Jiangxi Province, China
Rui Huang, Hai-Qiang Ma, School of Statistics and Data Science, Jiangxi University of Finance and Economics, Nanchang 330013, Jiangxi Province, China
Hai-Tao Wang, Department of General Surgery and Thoracic Surgery, Jishui County People's Hospital, Ji’an 331600, Jiangxi Province, China
Co-corresponding authors: Lin-Quan Wu and En-Liang Li.
Author contributions: Zhou PC, Yang J, and Li EL designed this work; Peng JD, Wang HT, and Fu ZX collected the clinical data; Zhou PC and Huang R performed the statistical analyses; Zhou PC and Huang R wrote this article; Liao WJ, Ma HQ, and Wu LQ revised and reviewed the manuscript; All authors reviewed the manuscript. Zhou PC was responsible for patient screening, enrollment, and collection of clinical data, and wrote the first draft of the manuscript. Huang R completed the data analysis and revised the initial draft. Both authors made critical and indispensable contributions to the completion of the project and thus qualify as co-first authors of the paper. Li EL and Wu LQ played important and indispensable roles in experimental design, data interpretation, and manuscript preparation, serving as co-corresponding authors. Li EL applied for and obtained funding for this research project, and conceptualized, designed, and supervised the entire project process as well as revised the early version of the manuscript. Wu LQ was instrumental in the re-analysis and interpretation of data, figure plotting, comprehensive literature review, and preparation and submission of the current version of the manuscript. The collaboration between Li EL and Wu LQ was crucial for the publication of this manuscript and other manuscripts still in preparation.
Supported by the National Natural Science Foundation of China, No. 82060447 and No. 82260553; the Key Project of Jiangxi Provincial Natural Science Foundation, No. 20224ACB206035; the General Project of Jiangxi Provincial Natural Science Foundation, No. 20232BAB206109; Jiangxi Provincial Natural Science Foundation, No. 20242BAB26002, and the Youth Project of Jiangxi Provincial Natural Science Foundation, No. 20224BAB216057.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the Second Affiliated Hospital of Nanchang University.
Informed consent statement: This study was a retrospective study analyzing electronic medical records and is subject to exemption from consent.
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 author En-liang Li (lienliangyx@163.com) upon reasonable request.
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: En-Liang Li, DPhil, Doctor, Department of General Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, No. 1 Minde Road, Donghu District, Nanchang 330008, Jiangxi Province, China. lienliangyx@163.com
Received: June 29, 2024 Revised: October 19, 2024 Accepted: December 10, 2024 Published online: February 27, 2025 Processing time: 206 Days and 15.1 Hours
Abstract
BACKGROUND
We investigated the utility of gamma-glutamyl transferase-to-lymphocyte ratio (GLR) as a predictive indicator for postoperative survival in patients with hepatocellular carcinoma (HCC) across different time periods and developed a predictive model based on this.
AIM
To evaluate the prognostic accuracy of GLR for overall survival (OS) in patients with HCC and its impact over time.
METHODS
This study enrolled 301 patients with HCC treated with curative hepatectomy. Exclusion criteria included non-HCC hepatic malignancies, inadequate records, and prior cancer treatments. Baseline demographics, clinical features, and hematological parameters were recorded. Time-dependent receiver operating characteristic curve analysis was used to determine the optimal GLR threshold for survival prediction at 13 months. Statistical analyses included the Kaplan-Meier method, multivariate Cox regression, and the creation of a prognostic nomogram.
RESULTS
Out of 301 patients, 293 were eligible for analysis, with a male predominance (84.6%). High preoperative GLR correlated with several adverse clinical features. Optimal cutoff values for GLR were significantly associated with stratification of 13-month OS. Multivariate analysis identified age, liver enzymes, postoperative transarterial chemoembolization, Child-Pugh grade, and inflammatory markers as independent predictors of OS. Notably, GLR had a significant impact on long-term postoperative OS, with its influence becoming more pronounced over time.
CONCLUSION
GLR can serve as a potent prognostic tool for postoperative HCC management, particularly in predicting long-term outcomes.
Core Tip: This study investigated gamma-glutamyl transferase-to-lymphocyte ratio (GLR) as a prognostic biomarker for hepatocellular carcinoma after curative liver resection. GLR was shown to predict both short-term and long-term survival, with its prognostic value increasing over time. A time-dependent Cox regression model and a prognostic nomogram were developed to enhance clinical decision-making. The findings suggested that GLR can provide valuable insights into patient risk stratification and guide postoperative management in patients with hepatocellular carcinoma.
Citation: Zhou PC, Huang R, Wang HT, Yang J, Peng JD, Fu ZX, Liao WJ, Ma HQ, Wu LQ, Li EL. Gamma-glutamyl transferase-to-lymphocyte ratio as a prognostic marker in patients with hepatocellular carcinoma undergoing hepatectomy. World J Gastrointest Surg 2025; 17(2): 98578
Hepatocellular carcinoma (HCC) is a major global health concern, ranking as the sixth most common cancer and the third-leading cause of cancer-related deaths worldwide[1]. Its incidence has been steadily increasing due to factors such as chronic hepatitis B and C infections, alcohol abuse, and nonalcoholic fatty liver disease[2,3]. Despite advances in diagnostic techniques and therapeutic interventions, the prognosis for patients with HCC remains poor, largely due to late diagnoses and high recurrence rates after surgery[4-6]. Early detection and accurate prognostic assessment are crucial for improving patient outcomes. Systemic inflammation has been recognized as a significant contributor to tumor development and progression[7]. Inflammatory markers derived from routine blood tests have gained attention for their prognostic value in various cancers, including HCC[8].
Among these, the g-glutamyl transferase (GGT)-to-lymphocyte ratio (GLR) has emerged as a promising biomarker[8,9]. GGT is an enzyme involved in glutathione metabolism and is indicative of oxidative stress within the body[10]. Elevated GGT levels have been associated with tumor aggressiveness and poor prognosis in several cancers[11]. Lymphocytes play a critical role in immune surveillance against tumor cells, and a decreased lymphocyte count can reflect a weakened immune response[12,13]. GLR combines these two parameters, potentially providing a more comprehensive reflection of the tumor microenvironment and host immune status. However, most studies have focused on the static prognostic value of GLR, without considering how its impact may change over time. Traditional Cox regression models assume that the effect of prognostic factors remains constant, which may not capture the dynamic nature of cancer progression[14]. Time-dependent Cox models allow for the evaluation of variables whose effects on survival may vary at different time intervals[15,16].
By investigating the time-dependent effects of GLR and other clinical factors, we aimed to provide a more nuanced understanding of their roles in patient prognosis. This research was significant because it could lead to improved prognostic models for HCC, aiding in risk stratification and personalized treatment planning. If the prognostic value of GLR is shown to vary over time, it could inform the timing and intensity of postoperative interventions. Moreover, this study contributed to the broader effort of integrating dynamic biomarkers into cancer prognosis, which is crucial for adapting to the complexities of tumor biology and patient responses over time.
MATERIALS AND METHODS
Patients
This retrospective cohort study was conducted at the Second Affiliated Hospital of Nanchang University from January 2016 to December 2020. Initially, 301 patients who underwent curative hepatectomy for HCC were considered. After applying inclusion and exclusion criteria, 293 patients were deemed eligible for analysis.
Inclusion criteria were patients aged ≥ 18 years, histologically confirmed HCC, and curative resection (R0 resection with negative surgical margins confirmed by pathological examination). Patients had not received any prior treatments such as radiotherapy, chemotherapy, targeted therapy, immunotherapy, or interventional therapy before surgery. All included patients had complete clinical data and follow-up information. Exclusion criteria included postoperative pathology indicating other hepatic malignancies or metastatic tumors, incomplete medical records or loss to follow-up, concurrent primary malignancies in other organs, active infections or inflammatory conditions unrelated to HCC at the time of surgery, death from causes other than HCC during the follow-up period, and noncompliance with postoperative follow-up protocols.
Parameters and measurements
Baseline demographic and clinical characteristics were collected, including age, sex, body mass index (BMI), tumor features (number, size, histological differentiation), microvascular invasion (MVI), preoperative ascites, Child-Pugh grade, and postoperative interventional therapy. Tumor size and number were determined based on preoperative imaging and confirmed by pathological examination. Histological differentiation was graded according to the Edmondson-Steiner system. MVI was assessed through pathological examination and defined as the presence of cancer cell nests within a vascular lumen lined by endothelial cells.
Laboratory data were obtained from routine blood tests conducted within 1 week before surgery, including complete blood count parameters and liver function tests such as alanine aminotransferase, aspartate aminotransferase, total bilirubin (TBIL), direct bilirubin, albumin, alkaline phosphatase, prothrombin time, hepatitis B surface antigen, α-fetoprotein, and GGT. Inflammatory markers were calculated using the following formulas: Neutrophil-to-lymphocyte ratio (NLR) = neutrophil count divided by lymphocyte count; platelet-to-lymphocyte ratio (PLR) = platelet count divided by lymphocyte count; and GLR = GGT level divided by lymphocyte count.
All surgery was performed by experienced hepatobiliary surgeons using open or laparoscopic hepatectomy. The extent of liver resection was determined by tumor size, location, liver function reserve (assessed by Child-Pugh score), and the patient's overall condition. Based on pathological findings and recurrence risk assessments, it was determined whether patients received postoperative transarterial chemoembolization (TACE).
Follow-up
Follow-up with patients was conducted via phone calls or outpatient visits commencing 1 month after discharge and subsequently at intervals of 3-6 months. Out of the initial cohort, 293 patients met the inclusion criteria and were analyzed, with 8 patients excluded. The primary outcome measure was overall survival (OS), defined as the time from the date of surgery to the date of death from any cause or the last follow-up. Recurrence-free survival (RFS) was defined as the time from surgery to the date of the first documented recurrence (intrahepatic or extrahepatic) or the last follow-up.
Statistical analysis
Selection of time points for analysis was informed by the Schoenfeld Residuals Plot, and the adherence to the proportional hazards assumption was verified at these points[14]. Time-dependent receiver operating characteristic curve analysis was used to compute the Youden index[17], thereby identifying optimal threshold values for the PLR, NLR, and GLR at the 13-month OS juncture and to calculate the area under the curve. Based on the derived GLR cutoff, patients were categorized into two cohorts. Comparative analysis of clinical features between these cohorts utilized the χ2 test. Quantitative data were expressed as mean ± standard deviation. The Kaplan-Meier method facilitated survival curve estimation, with the log-rank test applied for comparative purposes. Multivariate survival analysis was conducted using time-dependent Cox regression models with bidirectional stepwise variable selection, presenting hazard ratios and 95% confidence intervals (CI) as measures of relative risk. A prognostic nomogram, incorporating significant independent variables from the multivariate analysis, was constructed to project 1-year OS rates. Calibration of the performance of the nomogram entailed the use of the bootstrap method to produce a calibration curve, correlating predicted probabilities of 1-year OS with the observed rates. The predictive accuracy of the nomogram was assessed using Harrell’s concordance index (C-index). Statistical significance was set at P < 0.05, and all statistical analyses were conducted using R version 4.2.0.
RESULTS
Patient and tumor characteristics
Table 1 presents the clinical characteristics of the study participants. From the eligible pool, 293 patients met the inclusion criteria, comprising 248 males (84.6%) and 45 females (15.4%). Twenty-four patients (8.2%) had a BMI < 18.5 kg/m2, indicative of underweight status, while 66 patients (22.5%) had BMI > 24 kg/m2, suggesting overweight or obesity. There were no instances of tumor rupture documented. The population was stratified based on the tumor count, with 251 patients (85.7%) presenting a solitary lesion, and 42 patients (14.3%) exhibiting multiple lesions. Tumor size was categorized as follows: ≤ 2.0 cm (57 patients, 19.5%); 2.1-5.0 cm (122 patients, 41.6%); 5.1-10.0 cm (67 patients, 22.9%); and > 10.0 cm (47 patients, 16.0%). Tumor differentiation status was classified into three groups: Low and low-medium differentiated (50 patients, 17.1%); medium and high-medium differentiated (222 patients, 75.8%); and highly differentiated (21 patients, 7.1%).
Table 1 Correlation between gamma-glutamyl transferase-to-lymphocyte ratio and clinical and pathological characteristics of hepatocellular carcinoma.
Testing of proportional hazards assumption, and critical time points determination
Upon assessment, the proportional hazards assumption did not hold for some covariates. Sex (P = 0.006), GLR (P < 0.001), MVI (P = 0.004), and degree of differentiation (P < 0.001) significantly diverged from the assumption (Table 2), suggesting time-varying effects. According to the Schoenfeld Residuals Plot, the critical time points were established at 13 and 26 months (Figure 1).
Estimation of optimal cutoff values for inflammatory markers in OS prediction
The study identified the optimal cutoff values for GLR, NLR and PLR as 41.49, 2.40 and 114.21, respectively. These thresholds were determined through time-dependent receiver operating characteristic curves for predicting 13-month OS. The corresponding area under the curves for GLR, NLR, and PLR were 0.775, 0.539 and 0.601, respectively (Figure 2). This enabled the categorization of patients into groups with low or high GLR for subsequent analyses.
Figure 2 Receiver operating characteristic analysis of gamma-glutamyl transferase-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and neutrophil-to-lymphocyte ratio.
Area under the curve (AUC) for overall survival was 0.775, 0.601, and 0.539 for gamma-glutamyl transferase-to-lymphocyte ratio (GLR), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR). ROC: Receiver operating characteristic.
Association of inflammatory markers with clinical characteristics
Preoperative GLR levels were significantly associated with sex (χ2 = 7.000, P = 0.008), BMI (χ2 = 10.748, P = 0.005), aspartate aminotransferase (χ2 = 12.848, P < 0.001), alkaline phosphatase (χ2 = 18.103, P < 0.001), TBIL (χ2 = 13.794, P < 0.001), tumor count (χ2 = 9.902, P = 0.002), tumor diameter (χ2 = 28.262, P < 0.001), α-fetoprotein (χ2 = 5.676, P = 0.017), MVI (χ2 = 16.516, P < 0.001), postoperative TACE (χ2 = 5.064, P = 0.024), PLR (χ2 = 22.216, P < 0.001), and NLR (χ2 = 15.753, P < 0.001) but not significantly associated with age (χ2 = 2.731, P = 0.100), ascites (χ2 = 0.210, P = 0.647), WBC (χ2 = 1.629, P = 0.202), monocytes (χ2 = 0.897, P = 0.344), red cell distribution width (χ2 = 0.023, P = 0.880), alanine aminotransferase (χ2 = 1.358, P = 0.244), albumin (χ2 = 4.250, P = 0.039), direct bilirubin (χ2 = 0.300, P = 0.584), prothrombin time (χ2 = 0.028, P = 0.866), hepatitis B surface antigen (χ2 = 0.009, P = 0.925), Child-Pugh grade (χ2 = 2.720, P = 0.099) and degree of differentiation (χ2 = 3.819, P = 0.148).
Multivariate analysis
Within the cohort of 293 individuals, mortality was observed in 80 patients (27.3%), whereas 213 patients (72.7%) remained alive. OS in the cohort with a lower GLR was substantially greater in comparison to their counterparts with elevated GLR levels (Figure 3A). Patients categorized within the lower NLR or PLR groups exhibited a significant extension in OS when contrasted with those in the higher NLR or PLR groups (Figure 3B and C). We also analyzed the association between GLR, NLR, PLR, and RFS. Patients in the lower GLR cohort had significantly longer RFS compared to those in the higher GLR cohort (Supplementary Figure 1). In a multivariate analysis using bidirectional stepwise selection, the following was elucidated. For variables without time dependency, the independent prognostic factors for postoperative OS included age (95%CI: 0.956-0.998, P = 0.024), TBIL (95%CI: 1.008-1.070, P = 0.045), PLR (95%CI: 0.992-0.997, P < 0.001), Child-Pugh grade (95%CI: 0.525-0.849, P = 0.006), and postoperative TACE (95%CI: 0.325-0.601, P = 0.006).
Figure 3 Kaplan-Meier survival curves for overall survival based on gamma-glutamyl transferase-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio in patients with hepatocellular carcinoma.
A: Kaplan-Meier curve for overall survival (OS) based on low and high gamma-glutamyl transferase-to-lymphocyte ratio (GLR) groups; B: Kaplan-Meier curve for OS based on low and high neutrophil-to-lymphocyte ratio (NLR) groups; C: Kaplan-Meier curve for OS based on low and high platelet-to-lymphocyte (PLR) ratio groups.
For time-dependent variables, sex was an independent risk factor for OS within the first 0-13 months after surgery (95%CI: 1.234-3.508, P = 0.024), but its impact was no longer significant beyond 13 months. Similarly, MVI was an independent risk factor for OS during the first 0-13 months postoperatively (95%CI: 1.295-3.613, P = 0.003), although its effect diminished after 13 months. Tumor differentiation was an independent risk factor for OS during 0-13 months (95%CI: 0.223-0.561, P < 0.001) and 14-26 months (95%CI: 0.332-0.881, P = 0.004), with a stronger impact in the earlier period. GLR was an independent risk factor across all time intervals examined: 0-13 months (95%CI: 1.002-1.005, P = 0.022), 14-26 months (95%CI: 1.004-1.010, P < 0.001), and > 26 months (95%CI: 1.007-1.014, P < 0.001), with its impact intensifying over time (Table 3).
Table 3 Multivariate analysis of different factors for overall survival.
After conducting the multivariate analysis, a nomogram was constructed based on its results (Figure 4). In constructing the prognostic nomogram, multivariate Cox regression analysis delineated age, TBIL, PLR, postoperative TACE, sex, Child-Pugh grade, MVI, tumor differentiation, and GLR as independent prognostic indicators. The nomogram integrated these variables to forecast the individual 1-year OS probability. For validation, we implemented 1000 bootstrap resamples and employed a calibration plot for internal validation. The prognostic accuracy of the nomogram was substantiated by its strong concordance with the actual OS rates derived from Kaplan-Meier analysis (Figure 5). The model achieved a C-index of 0.837, with a standard error of 0.028, indicating that it could distinguish the prognosis with an accuracy rate of 83.7% between 2 randomly chosen patients from the cohort.
Figure 5 Calibration curve of the prognostic nomogram for overall survival in patients with hepatocellular carcinoma.
The 1-year overall survival (OS) prediction from the nomogram compared with the actual 1-year OS.
DISCUSSION
The development and progression of HCC are influenced by multiple factors, including HBV infection and prolonged alcohol consumption. However, the precise pathogenic mechanisms remain incompletely understood. Recent studies have highlighted the pivotal role of inflammation in cancer development. Inflammation can promote carcinogenesis through various pathways, such as inducing genetic mutations, enhancing cancer cell proliferation, and promoting angiogenesis within tumors[13].
Systemic inflammatory markers such as PLR, NLR, and GLR have been identified as independent predictors of postoperative prognosis in patients with HCC[18,19]. GGT, an enzyme involved in glutathione metabolism, serves as a biomarker for several diseases, including liver disorders, diabetes, coronary artery disease, and chronic obstructive pulmonary disease[20-24]. Elevated GGT levels have been associated with malignancies such as cholangiocarcinoma and HCC, potentially due to its pro-oxidative activity and involvement in carcinogenic inflammation[11,25-27]. Lymphocyte count, reflecting systemic immune status, also holds prognostic value in various primary malignancies[28]. These findings underscore the significant impact of systemic inflammation on cancer progression and metastasis[13].
In our study, we analyzed the clinical and prognostic factors in 293 patients with HCC who underwent curative resection, incorporating time-dependent variables. Utilizing the proportional hazards assumption test, we assessed the time-dependent effects of each variable and divided the postoperative survival time into three stages: 0-13 months, 14-26 months, and > 26 months. Our results showed that factors like age, TBIL, PLR and TACE consistently influenced survival across all time periods.
We found that GLR is an independent prognostic factor for postoperative survival, with its predictive value increasing over time. Specifically, GLR had a weaker prognostic impact within the first 13 months after surgery but became more significant in later periods. This suggests that GLR may be more valuable in predicting long-term survival outcomes in patients with HCC. Similar findings have been reported in previous studies, where a higher GLR was significantly associated with reduced OS and RFS in patients with cholangiocarcinoma[25].
Our analysis of NLR and PLR revealed that PLR is an independent prognostic factor for OS after HCC surgery, aligning with prior research[19]. However, NLR did not emerge as an independent prognostic factor in our study, which may be attributed to the incorporation of time-dependent factors in our analysis.
The pathological features of tumors, such as MVI and tumor differentiation, exhibited time-dependent effects on postoperative OS. MVI significantly impacted prognosis within the first 13 months after surgery but not thereafter. Similarly, tumor differentiation affected survival during the first 26 months, with a more pronounced effect in the initial 13 months. MVI is defined as the presence of micrometastatic HCC thrombi within intrahepatic vessels, and a lower degree of differentiation typically indicates a higher malignancy of the tumor[29,30]. Both MVI and poor differentiation are known factors for early recurrence and reduced survival[31,32]. We speculate that this time-related effect may be associated with early postoperative tumor recurrence, leading to shorter survival times and limited long-term follow-up data.
Age has been shown to affect postoperative survival in HCC, possibly due to increased postoperative complications and decreased physiological reserves in older patients[33,34]. Liver function parameters such as TBIL were also identified as precise prognostic indicators, which is consistent with previous studies emphasizing the dual challenges of tumor burden and impaired liver function in patients with HCC[35,36]. Our findings suggest that among various liver function metrics, TBIL may serve as a more accurate prognostic indicator, potentially informing clinical decision-making. TACE was found to have a positive impact on survival, aligning with observations from other studies[37,38]. Therefore, we believe that patients in overall good health may achieve better prognosis when receiving postoperative TACE.
We constructed a prognostic nomogram incorporating GLR and other independent risk factors identified through multivariate analysis. The nomogram demonstrated a C-index of 0.837, indicating high predictive accuracy. By integrating variables like GLR, sex, age, TBIL, PLR, MVI, tumor differentiation, Child-Pugh grade, and postoperative TACE, the nomogram may offer a more accurate prediction of OS compared to single biomarkers or traditional Cox regression models.
Our study had some limitations. It was a single-center retrospective analysis with a moderate sample size, which may have introduced selection bias, especially concerning diagnostic and therapeutic decisions over the extended data collection period. Due to strict surgical eligibility criteria, our study included relatively few patients with Child-Pugh grade B and C. Therefore, the assessment of the impact of different Child-Pugh grade on postoperative survival may be subject to selection bias. Future multicenter, large-scale prospective studies are needed to validate our results and potentially refine the prognostic tools for HCC.
CONCLUSION
Our study demonstrated that GLR was an independent prognostic factor for patients with HCC undergoing curative resection, with its predictive value increasing over time. This time-dependent characteristic suggested that GLR could be particularly useful for long-term monitoring and risk assessment. The prognostic nomogram that we developed, incorporating GLR along with other significant clinical variables, offers a practical tool for clinicians to enhance decision-making processes. These findings have several broader implications. Firstly, they underscore the importance of considering temporal dynamics in prognostic modeling, which could be extended to other cancers and biomarkers. Secondly, the study highlights the potential of GLR as not only a prognostic marker but also a possible target for therapeutic intervention, given its association with systemic inflammation and immune response. Lastly, integrating GLR into clinical practice could improve patient stratification, leading to more personalized and effective management strategies for HCC.
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 A, Grade C, Grade D
Novelty: Grade B, Grade B, Grade C
Creativity or Innovation: Grade B, Grade B, Grade C
Scientific Significance: Grade B, Grade B, Grade C
P-Reviewer: Wang Z; Wang W; Xie YF S-Editor: Li L L-Editor: Filipodia P-Editor: Xu ZH
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