Nomogram Based on Systemic Immune Inflammation Index and Prognostic Nutrition Index Predicts Recurrence of Hepatocellular Carcinoma After Surgery

Machine Learning Model Based on the Neutrophil-to-Eosinophil Ratio Predicts the Recurrence of Hepatocellular Carcinoma After Surgery

Background

Circulating eosinophils are associated with tumor development. An eosinophil-related index, the neutrophil to eosinophil ratio (NER), can be used to predict the prognosis of patients with tumors. However, there is still a lack of efficient prognostic biomarkers for HCC. In this study, we aimed to investigate the predictive value of the NER and develop an optimal machine learning model for the recurrence of HCC patients. Patients and methods: A retrospective collection of 562 patients who underwent hepatectomy with a pathologic diagnosis of HCC was performed. The relationship between NER and progression-free survival (PFS) was investigated. We developed a new machine learning framework with 10 machine learning algorithms and their 101 combinations to select the best model for predicting recurrence after hepatectomy. The performance of the model was assessed by the area under the curve (AUC) of characteristics and calibration curves, and clinical utility was evaluated by decision curve analysis (DCA).

Results

Kaplan‒Meier curves showed that the PFS in the low NER group was significantly better than that in the high NER group. Multivariate Cox regression analysis showed that NER was an independent risk factor for recurrence after surgery. The random survival forests (RSF) model was selected as the best model that had good predictive efficacy and outperformed the TNM, BCLC, and CNLC staging systems.

Conclusion

The NER has good predictive value for postoperative recurrence in patients with hepatocellular carcinoma. Machine learning model based on NER can be used for accurate predictions.

Construction and validation of a novel prognostic model for intrahepatic cholangiocarcinoma based on a combined scoring system of systemic immune-inflammation index and albumin-bilirubin: a multicenter study

Background

The degree of inflammation and immune status is widely recognized to be associated with intrahepatic cholangiocarcinoma (ICC) and is closely linked to poor postoperative survival. The purpose of this study was to evaluate whether the systemic immune-inflammatory index (SII) and the albumin bilirubin (ALBI) grade together exhibit better predictive strength compared to SII and ALBI separately in patients with ICC undergoing curative surgical resection.

Methods

A retrospective analysis was performed on a cohort of 374 patients with histologically confirmed ICC who underwent curative surgical resection from January 2016 to January 2020 at three medical centers. The cohort was divided into a training set comprising 258 patients and a validation set consisting of 116 patients. Subsequently, the prognostic predictive abilities of three indicators, namely SII, ALBI, and SII+ALBI grade, were evaluated. Independent risk factors were identified through univariate and multivariate analyses. The identified independent risk factors were then utilized to construct a nomogram prediction model, and the predictive strength of the nomogram prediction model was assessed through Receiver Operating Characteristic (ROC) survival curves and calibration curves.

Results

Univariate analysis of the training set, consisting of 258 eligible patients with ICC, revealed that SII, ALBI, and SII+ALBI grade were significant prognostic factors for overall survival (OS) and recurrence-free survival (RFS) (p < 0.05). Multivariate analysis revealed the independent significance of SII+ALBI grade as a risk factor for postoperative OS and RFS (p < 0.05). Furthermore, we conducted an analysis of the correlation between SII, ALBI, SII+ALBI grade, and clinical features, indicating that SII+ALBI grade exhibited stronger associations with clinical and pathological characteristics compared to SII and ALBI. We constructed a predictive model for postoperative survival in ICC based on SII+ALBI grade, as determined by the results of multivariate analysis. Evaluation of the model's predictive strength was performed through ROC survival curves and calibration curves in the training set and validation set, revealing favorable predictive performance.

Conclusion

The SII+ALBI grade, a novel classification based on inflammatory and immune status, serves as a reliable prognostic indicator for postoperative OS and RFS in patients with ICC.

Development of nomograms to predict recurrence after conversion hepatectomy for hepatocellular carcinoma previously treated with transarterial interventional therapy

BACKGROUND

Lack of opportunity for radical surgery and postoperative tumor recurrence are challenges for surgeons and hepatocellular carcinoma (HCC) patients. This study aimed to develop nomograms to predict recurrence risk and recurrence-free survival (RFS) probability after conversion hepatectomy for patients previously receiving transarterial interventional therapy.

METHODS

In total, 261 HCC patients who underwent conversion liver resection and previously received transarterial interventional therapy were retrospectively enrolled. Nomograms to predict recurrence risk and RFS were developed, with discriminative ability and calibration evaluated by C-statistics, calibration plots, and the Area under the Receiver Operator Characteristic (AUROC) curves.

RESULTS

Univariate/multivariable logistic regression and Cox regression analyses were used to identify predictive factors for recurrence risk and RFS, respectively. The following factors were selected as predictive of recurrence: age, tumor number, microvascular invasion (MVI) grade, preoperative alpha-fetoprotein (AFP), preoperative carbohydrate antigen 19-9 (CA19-9), and Eastern Cooperative Oncology Group performance score (ECOG PS). Similarly, age, tumor number, postoperative AFP, postoperative protein induced by vitamin K absence or antagonist-II (PIVKA-II), and ECOG PS were incorporated for the prediction of RFS. The discriminative ability and calibration of the nomograms revealed good predictive ability. Calibration plots showed good agreement between the nomogram predictions of recurrence and RFS and the actual observations.

CONCLUSIONS

A pair of reliable nomograms was developed to predict recurrence and RFS in HCC patients after conversion resection who previously received transarterial interventional therapy. These predictive models can be used as guidance for clinicians to help with treatment strategies.

Predictive value of preoperative inflammatory indexes for postoperative early recurrence of hepatitis B-related hepatocellular carcinoma

Objective

To investigate the predictive value of preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammation response index (SIRI), and systemic immune inflammation index (SII) for early recurrence after liver resection in patients with hepatitis B-related hepatocellular carcinoma.

Methods

A retrospective study was conducted on 162 patients who underwent hepatitis B-related hepatocellular carcinoma (HCC) resection between January 2013 and April 2016. The Youden index was utilized to calculate the optimal cut-off value. The Pearson Chi-square test was applied to analyze the relationship between inflammatory indexes and common clinical and pathological features. The Kaplan-Meier method and Log-Rank test were implemented to compare the recurrence-free survival rate within 2 years of the population. The Cox regression analysis was used to identify the risk factors for early postoperative recurrence.

Results

The best cut-off values of SIRI, PLR, NLR and SII were 0.785, 86.421, 2.231 and 353.64, respectively. Tumor diameter, degree of tumor differentiation, vascular invasion, SIRI>0.785, PLR>86.421, NLR>2.231 and SII>353.64 were risk factors for early recurrence. Combining the above seven risk factors to construct a joint index, the AUC of the joint prediction model was 0.804. The areas under the ROC curves of SIRI, PLR, NLR, and SII were 0.659, 0.725, 0.680, and 0.723, respectively. There was no significant difference in the predictive ability between the single inflammatory index models, but the predictive performance of the joint prediction model was significantly higher than that of the single inflammatory index models. The patients with lower SIRI, PLR, NLR, SII and joint index value had longer recurrence-free survival within 2 years.

Conclusion

The joint index CIP, constructed by combining preoperative SIRI, PLR, NLP and SII with pathological features, can better predict the early recurrence of HBV-related HCC patients after surgery, which is beneficial in identifying high-risk patients and assisting clinicians to make better clinical choices.

A new model based on gamma-glutamyl transpeptidase to lymphocyte ratio and systemic immune-inflammation index can effectively predict the recurrence of hepatocellular carcinoma after liver transplantation

Background

Liver transplantation (LT) is one of the most effective treatment modalities for hepatocellular carcinoma (HCC), but patients with HCC recurrence after LT always have poor prognosis. This study aimed to evaluate the predictive value of the gamma-glutamyl transpeptidase-to-lymphocyte ratio (GLR) and systemic immune-inflammation index (SII) in terms of HCC recurrence after LT, based on which we developed a more effective predictive model.

Methods

The clinical data of 325 HCC patients who had undergone LT were collected and analyzed retrospectively. The patients were randomly divided into a development cohort (n = 215) and a validation cohort (n = 110). Cox regression analysis was used to screen the independent risk factors affecting postoperative recurrence in the development cohort, and a predictive model was established based on the results of the multivariate analysis. The predictive values of GLR, SII and the model were evaluated by receiver operating characteristic (ROC) curve analysis, which determined the cut-off value for indicating patients' risk levels. The Kaplan-Meier survival analysis and the competing-risk regression analysis were used to evaluate the predictive performance of the model, and the effectiveness of the model was verified further in the validation cohort.

Results

The recurrence-free survival of HCC patients after LT with high GLR and SII was significantly worse than that of patients with low GLR and SII (P<0.001). Multivariate Cox regression analysis identified GLR (HR:3.405; 95%CI:1.954-5.936; P<0.001), SII (HR: 2.285; 95%CI: 1.304-4.003; P=0.004), tumor number (HR:2.368; 95%CI:1.305-4.298; P=0.005), maximum tumor diameter (HR:1.906; 95%CI:1.121-3.242; P=0.017), alpha-fetoprotein level (HR:2.492; 95%CI:1.418-4.380; P=0.002) as independent risk factors for HCC recurrence after LT. The predictive model based on these risk factors had a good predictive performance in both the development and validation cohorts (area under the ROC curve=0.800, 0.791, respectively), and the performance of the new model was significantly better than that of single GLR and SII calculations (P<0.001). Survival analysis and competing-risk regression analysis showed that the predictive model could distinguish patients with varying levels of recurrence risk in both the development and validation cohorts.

Conclusions

The GLR and SII are effective indicators for evaluating HCC recurrence after LT. The predictive model based on these indicators can accurately predict HCC recurrence after LT and is expected to guide preoperative patient selection and postoperative follow-up.

Macrotrabecular-massive subtype-based nomogram to predict early recurrence of hepatocellular carcinoma after surgery

OBJECTIVES

To analyze the predictive factors on early postoperative recurrence of hepatocellular carcinoma (HCC) and to establish a new nomogram to predict early postoperative recurrence of HCC.

METHODS

A retrospective analysis of 383 patients who had undergone curative resection between February 2012 and September 2020 in our center was performed. The Kaplan-Meier method was used for survival curve analysis. Univariate and multivariate Cox regression were performed to identify independent risk factors associated with early recurrence, and a nomogram for predicting early recurrence of HCC was established.

RESULTS

A total of 152/383 patients developed recurrence after surgery, of which 83 had recurrence within 1 year. Multivariate Cox regression analysis showed that preoperative alpha-fetoprotein level ≥400 ng/ml (P = 0.001), tumor diameter ≥5 cm (P = 0.009) and MVI (P = 0.007 and macrotrabecular-massive HCC (P = 0.003) were independent risk factors for early postoperative recurrence of HCC. The macrotrabecular-massive-based nomogram obtained a good C-index (0.74) for predicting early recurrence of HCC, and the area under the curve for predicting early recurrence was 0.767, which was better than the single American Joint Committee on Cancer T stage and Barcelona Clinic Liver Cancer stage.

CONCLUSIONS

The nomogram based on macrotrabecular-massive HCC can effectively predict early postoperative recurrence of HCC.

Preoperative systemic inflammatory response index predicts the prognosis of patients with hepatocellular carcinoma after liver transplantation

Background

Preoperative inflammatory status plays an important role in the prognosis of malignancy. We sought to explore the value of preoperative inflammatory biomarkers in predicting long-term outcomes of liver transplantation (LT) in patients with hepatocellular carcinoma (HCC).

Method

Patients who underwent LT for HCC in our hospital between January 2010 and June 2020 were included in this study. Demographic, clinical, laboratory, and outcome data were obtained. The area under the curve (AUC) of the receiver operating characteristic curve was used to evaluate the predictive value of inflammatory biomarkers. The effectiveness of inflammatory biomarkers in predicting outcomes was analyzed by univariate and multivariate Cox proportional hazards analyses.

Results

A total of 218 patients were included in the study, with a mean age of 53.9 ± 8.5 years. The AUC of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune inflammation index (SII), and systemic inflammatory response index (SIRI) for overall survival (OS) were 0.741, 0.731, 0.756, 0.746, and 0.749, respectively. Cox proportional hazards model indicated that SIRI &gt; 1.25 was independently associated with low OS [hazard ratio (HR) = 2.258, P = 0.024]. PLR &gt; 82.15 and SIRI &gt; 0.95 were independently associated with low disease-free survival (HR = 1.492, P = 0.015; and HR = 1.732, P = 0.008, respectively). In the survival analysis, the prognosis of patients with high preoperative SIRI and PLR was significantly worse (P &lt; 0.001).

Conclusion

SIRI and PLR were useful prognostic markers for predicting patients with HCC after LT.

Amino acid profiles in the tissue and serum of patients with liver cancer

Most patients with liver cancer were found late and lost the chance of surgery. Liquid biopsy can monitor the risk of tumor recurrence and metastasis, quickly evaluate the curative effect of tumor treatment, and is conducive to early screening and auxiliary diagnosis of high-risk groups. Amino acid (AA) profiling has been used to the diagnosis and the prognosis for cancers. However, little was known about the profiles of AA of liver cancer. In this study, we used tRNA in Cancer database to analyze the AA levels in liver cancer tissues. Blood samples of patients with liver cancer were collected and analyzed using the automatic AA analyzer. We found that valine, isoleucine, and leucine were decreased significantly both in the plasma and the tumor tissues of patients with liver cancer. However, upregulation of methionine was observed in tissues and plasma of patients with liver cancer. Interestingly, tyrosine, and phenylalanine were decreased in tumor tissue but increased in the plasma of patients with liver cancer. This is the first report provided an overview of AA profile in both plasma and tissue for patients with liver cancer. AA levels can be used as diagnostic and prognostic markers of patients with liver cancer.

Intraoperative low-dose dopamine is associated with worse survival in patients with hepatocellular carcinoma: A propensity score matching analysis

Background

Dopamine is widely used in patients during surgery. We evaluated the association between intraoperative low-dose dopamine administration and recurrence-free survival (RFS) and overall survival (OS) in patients with hepatocellular carcinoma (HCC).

Methods

Consecutive patients with nonmetastatic HCC who underwent radical hepatectomy were enrolled between 2008 and 2010. Univariate and multivariate logistic regression analyses were used to evaluate the prognostic factors for RFS and OS. Survival outcomes were evaluated using Kaplan–Meier analyses with the log-rank test. A one-to-one propensity score matching (PSM) analysis was performed to reduce confounding bias.

Results

A total of 805 HCC patients, including 699 patients who did not receive dopamine consumption and 106 patients who received low-dose dopamine during the operation, were retrospectively analyzed. The patients who were assigned low-dose dopamine had worse RFS (p = 0.009) and OS (p = 0.041) than those who did not receive dopamine. Multivariate regression analysis showed that the intraoperative administration of low-dose dopamine was an independent unfavorable predictor for RFS (p = 0.004) but not for OS (p = 0.059). After PSM, the low-dose dopamine-treated group still had significantly poorer RFS (p = 0.003) and OS (p = 0.002). When stratified by time of recurrence, patients with low-dose dopamine use had a significantly greater chance of recurrence within 2 years (p = 0.007) but not after 2 years (p = 0.186).

Conclusions

Intraoperative low-dose dopamine use has a negative impact on RFS and OS in HCC patients who have undergone radical hepatectomy. Further prospective studies are required to assess the effects of low-dose dopamine on surgical outcomes in HCC patients.

Predictive Value of Preoperative Serum AFP, CEA, and CA19-9 Levels in Patients with Single Small Hepatocellular Carcinoma: Retrospective Study

Purpose

This study aimed to explore the relationship between the tumor marker score (TMS) and the postoperative recurrence of single small hepatocellular carcinoma (HCC).

Patients and Methods

A total of 409 patients with one resectable HCC with a diameter of 3 cm or less who visited Tianjin Medical University Cancer Institute & Hospital from January 2010 to December 2014 were included in this study. Their alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), and carbohydrate antigen 19-9 (CA19-9) levels were classified into low and high groups using X-tile software. Each patients' TMS was calculated as the sum of each tumor marker (low = 0; high = 1).

Results

A total of 142 patients were classified as TMS0, 171 as TMS1, and 96 as TMS2. Kaplan–Meier analysis illustrated that TMS could divide the patients into groups with remarkably different prognoses, and the patients with high TMS had worse recurrence-free survival (RFS) than those with low TMS. Multivariate analysis showed that TMS, age, and HBeAg positive were the independent predictors of RFS rate. Subgroup analysis revealed that high TMS was a stable risk factor relative to TMS0. Receiver operating curves showed that the 1-, 3-, and 5-year area under curve (AUC) values of TMS were 0.698, 0.662, and 0.673, respectively. The AUC of TMS was higher than that of other common prognostic models in time-dependent receiver operating curve.

Conclusion

TMS was an independent prognostic factor for the postoperative recurrence of a single small HCC and can provide a well-discriminated risk stratification, thus contributing to prognostic prediction and adjuvant therapeutic development.

Combining Pre- and Postoperative Lymphocyte–C-Reactive Protein Ratios Can Better Predict Hepatocellular Carcinoma Prognosis After Partial Hepatectomy

Background

Various preoperative inflammatory indicators have been identified as potential predictors of poor prognosis in patients with hepatocellular carcinoma (HCC), but the role of postoperative inflammatory indicators remains unclear. This study aimed to explore the prognostic value of the postoperative lymphocyte–C-reactive protein ratio (PostLCR) on its own and combined with preoperative LCR (PreLCR).

Methods

A total of 290 patients with primary HCC were retrospectively enrolled in the study. Univariate analysis was used to identify factors significantly associated with poor disease-free survival (DFS) and overall survival (OS), then multivariate analysis was performed to identify independent prognostic indicators of poor survival. Prognostic models based on preoperative, postoperative, and both types of indicators were then constructed, and their predictive performance were evaluated using time-dependent receiver operating characteristic curves and the concordance index (C-index).

Results

PreLCR and PostLCR levels correlated with DFS and OS more strongly than other pre- and postoperative inflammatory indicators, respectively. Decreased PreLCR and PostLCR were independent prognostic factors for both DFS and OS, while HCC patients with decreased PreLCR and PostLCR had worse prognosis than patients with increased PreLCR and PostLCR. Patients into three groups based on their cut-off values of PreLCR and PostLCR, Kaplan–Meier survival analysis indicated that HCC patients with low PreLCR and PostLCR had the worst DFS and OS. The combined model showed better predictive performance at 1 and 3 years post-surgery than individual pre- and postoperative models, the American Joint Committee on Cancer/Tumor-Node-Metastasis (8th edition) staging system and the Barcelona Clinic Liver Cancer system. The combine model demonstrated a markedly superior C-index compared with the other models in DFS and OS.

Conclusion

Our study showed PreLCR and PostLCR are independent predictors of DFS and OS in HCC patients after partial hepatectomy. Models that include both PreLCR and PostLCR can predict prognosis better than well-established clinical staging systems.

Prognostic significance of systemic immune-inflammation index and platelet-albumin-bilirubin grade in patients with pancreatic cancer undergoing radical surgery

BACKGROUND

Systemic inflammatory markers are associated with patient survival in pancreatic cancer (PC). The aim of this study was to investigate the prognostic significance of the systemic immune-inflammation index (SII) in PC patients who underwent radical surgery. Platelet-albumin-bilirubin (PALBI) grade is a composite evaluation index based on liver function. Patients with pancreatic head cancer are prone to obstructive jaundice, which leads to abnormal liver function. Based on this, we also explored the prognostic value of PALBI grade in PC patients.

METHODS

Patients with pathologically confirmed PC who had undergone radical surgery (with negative surgical margin) for the first time at the Affiliated Hospital of Qingdao University from January 2013 to December 2019 and followed up by December 2020 were retrospectively analyzed. Peripheral blood cell count is easily affected by infection or hematological diseases, which affects the results, so it is excluded. Clinical data and laboratory examination indexes were collected. The SII and PALBI grade were calculated. The cutoff values were determined using the Youden index. The Cox proportional hazards regression model was used to analyze the prognostic value of the SII and PALBI grade through univariate and multivariate survival analysis.

RESULTS

A total of 214 patients [median age, 60.29 years; 128 (59.8%) men] met the inclusion criteria. There were 140 patients (65.4%) with pancreatic head cancer according to the tumor location. They were divided into high and low SII or PALBI groups by cutoff values of 705 and -5.6, respectively. According to the multivariate analysis, SII (P<0.001) was an independent factor negatively associated with overall survival (OS) and disease-free survival (DFS). In patients with pancreatic head cancer, PALBI grade was associated with shorter OS (P=0.031). The combination of high SII and high PALBI grade had stronger predictive value for poor prognosis (log-rank test, P<0.001), which the OS was 11.3 months less than the combination of low two groups.

CONCLUSIONS

SII was a promising prognostic biomarker in PC. And PALBI grade also showed predictive value for patients with pancreatic head cancer. Therefore, it can help predict the treatment outcomes in these patients.

Prediction Efficacy of Prognostic Nutritional Index and Albumin-Bilirubin Grade in Patients With Intrahepatic Cholangiocarcinoma After Radical Resection: A Multi-Institutional Analysis of 535 Patients

Background

The preoperative nutritional status and the immunological status have been reported to be independent prognostic factors of patients with intrahepatic cholangiocarcinoma (ICC). This study aimed to investigate whether prognostic nutritional index (PNI) + albumin–bilirubin (ALBI) could be a better predictor than PNI and ALBI alone in patients with ICC after radical resection.

Methods

The prognostic prediction evaluation of the PNI, ALBI, and the PNI+ALBI grade was performed in 373 patients with ICC who underwent radical resection between 2010 and 2018 at six Chinese tertiary hospitals, and external validation was conducted in 162 patients at four other Chinese tertiary hospitals. Overall survival (OS) and relapse-free survival (RFS) were estimated using the Kaplan–Meier method. Multivariate analysis was conducted to identify independent prognostic factors. A time-dependent receiver operating characteristic (ROC) curve and a nomogram prediction model were further constructed to assess the predictive ability of PNI, ALBI, and the PNI+ALBI grade. The C-index and a calibration plot were used to assess the performance of the nomogram models.

Results

Univariate analysis showed that PNI, ALBI, and the PNI+ALBI grade were prognostic factors for the OS and RFS of patients with ICC after radical resection in the training and testing sets (p < 0.001). Multivariate analysis showed that the PNI+ALBI grade was an independent risk factor for OS and RFS in the training and testing sets (p < 0.001). Analysis of the relationship between the PNI+ALBI grade and clinicopathological characteristics showed that the PNI+ALBI grade correlated with obstructive jaundice, alpha-fetoprotein (AFP), cancer antigen 19-9 (CA19-9), cancer antigen 125 (CA125), PNI, ALBI, Child–Pugh grade, type of resection, tumor size, major vascular invasion, microvascular invasion, T stage, and N stage (p < 0.05). The time-dependent ROC curves showed that the PNI+ALBI grade had better prognostic predictive ability than the PNI, ALBI, and the Child–Pugh grade in the training and testing sets.

Conclusion

Preoperative PNI+ALBI grade is an effective and practical predictor for the OS and RFS of patients with ICC after radical resection.

Artificial Intelligent Multi-Modal Point-of-Care System for Predicting Response of Transarterial Chemoembolization in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) ranks the second most lethal tumor globally and is the fourth leading cause of cancer-related death worldwide. Unfortunately, HCC is commonly at intermediate tumor stage or advanced tumor stage, in which only some palliative treatment can be used to offer a limited overall survival. Due to the high heterogeneity of the genetic, molecular, and histological levels, HCC makes the prediction of preoperative transarterial chemoembolization (TACE) efficacy and the development of personalized regimens challenging. In this study, a new multi-modal point-of-care system is employed to predict the response of TACE in HCC by a concept of integrating multi-modal large-scale data of clinical index and computed tomography (CT) images. This multi-modal point-of-care predicting system opens new possibilities for predicting the response of TACE treatment and can help clinicians select the optimal patients with HCC who can benefit from the interventional therapy.

The Significance of the Rapid Turnover Protein Score as a Predictor of the Long-Term Outcomes in Hepatocellular Carcinoma After Hepatic Resection

BACKGROUND

Nutritional status assessment is essential in cancer patients because a poor nutritional status has been associated with poor outcomes; however, the impact of rapid turnover proteins (RTPs), such as prealbumin, transferrin, and retinol-binding protein, on the outcomes of hepatocellular carcinoma (HCC) has not been well-investigated. We therefore examined the prognostic significance of RTPs in patients with HCC after curative resection.

METHODS

This study included 150 patients who underwent elective hepatic resection for HCC between January 2011 and December 2018. The prealbumin, transferrin, and retinol-binding protein levels were classified into two groups (high vs. low); the RTP score (0-3) was calculated as the sum of each RTP measurement (high = 0; low = 1). We retrospectively investigated the relationship between the RTP score and disease-free and overall survival.

RESULTS

Multivariate analysis showed that a high RTP score (P = 0.022), presence of sarcopenia (P = 0.001), and stage III or higher (P = 0.005) were independent predictors of disease-free survival, while a high RTP score (P < 0.001), presence of sarcopenia (P = 0.017), and stage III or higher (P = 0.012) were independent predictors of overall survival. In patients with high RTP scores, positive hepatitis B and C viral infection, high indocyanine green (ICG) at 15 min (ICG_R15), Child-Pugh grade B, poorly differentiated carcinoma, and postoperative ascites were more common than in patients with low RTP scores.

CONCLUSION

The preoperative RTP score may be a prognostic factor in patients with hepatocellular carcinoma after hepatic resection, suggesting an important role of RTP in the assessment of nutritional status in cancer patients.