The Age, Gamma-Glutamyl Transpeptidase and Platelet Index: A Novel Noninvasive Model for Predicting Hepatocellular Carcinoma in Patients with Hepatitis B Virus-Related Liver Cirrhosis

Li, Kai; Huang, Zeyu; Yang, Suhua; Lin, Lin; Zheng, Shuqin; Zhang, Xiujun; Xue, Yuan; Xie, W.

doi:10.2147/jhc.s386977

Cited by 2 publications

(1 citation statement)

References 29 publications

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“…The gamma-glutamyl transpeptidase to platelet ratio (GPR) has been reported as an accurate non-invasive predictor for HCC development in patients with HBV infection ( 58 ). Combined with the preoperative serum fibrinogen index, GPR could better predict the prognosis of HBV-related HCC underwent hepatectomy as an effective non-invasive predictor ( 59 ).…”

Section: Serological and Hematological Predictorsmentioning

confidence: 99%

Perioperative predictors of outcome of hepatectomy for HBV-related hepatocellular carcinoma

Tang

2023

Front. Oncol.

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Hepatitis B virus (HBV) is identified as a major risk factor for hepatocellular carcinoma (HCC), resulting in so-called hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC). Hepatectomy for HCC is acknowledged as an efficient treatment strategy, especially for early HCC. Furthermore, patients with advanced HCC can still obtain survival benefits through surgical treatment combined with neoadjuvant therapy, adjuvant therapy, transcatheter arterial chemoembolization, and radiofrequency ablation. Therefore, preoperative and postoperative predictors of HBV-related HCC have crucial indicative functions for the follow-up treatment of patients with feasible hepatectomy. This review covers a variety of research results on preoperative and postoperative predictors of hepatectomy for HBV-related HCC over the past decade and in previous landmark studies. The relevant contents of Hepatitis C virus-related HCC, non-HBV non-HCV HCC, and the artificial intelligence application in this field are briefly addressed in the extended content. Through the integration of this review, a large number of preoperative and postoperative factors can predict the prognosis of HBV-related HCC, while most of the predictors have no standardized thresholds. According to the characteristics, detection methods, and application of predictors, the predictors can be divided into the following categories: 1. serological and hematological predictors, 2. genetic, pathological predictors, 3. imaging predictors, 4. other predictors, 5. analysis models and indexes. Similar results appear in HCV-related HCC, non-HBV non-HCV HCC. Predictions based on AI and big biological data are actively being applied. A reasonable prediction model should be established based on the economic, health, and other levels in specific countries and regions.

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Section: Serological and Hematological Predictorsmentioning

confidence: 99%

Perioperative predictors of outcome of hepatectomy for HBV-related hepatocellular carcinoma

Tang

2023

Front. Oncol.

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Performance of multi-regional radiomics features and clinical-radiological variables in the prognostic analysis and risk stratification of single hepatocellular carcinoma

Wang,

Feng,

Liang

et al. 2023

Preprint

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Background To develop multi-regional radiomics models to evaluate the prognosis of single hepatocellular carcinoma (HCC) after hepatectomy and stratify risk by combining radiomics features with clinical-radiological variables. Methods This retrospective study enrolled 207 patients with single HCC after surgery (training set:validation set = 144:63). Different volumes of interest (VOIs) were constructed to extract radiomics features, and the model with the largest area under the receiver operating characteristic curve (AUC) was considered optimal. Prognostic clinical-radiological variables were identified via univariate and multivariate Cox regression analyses. A combined model incorporating radiomics features and clinical-radiological variables was utilized to predict outcomes and stratify recurrence risk. The Kaplan–Meier method and the log–rank tests were applied to estimate recurrence-free survival (RFS). Calibration curves and decision curve analysis were employed to assess performance of the combined model. Results Among the multi-regional radiomics models, the model based on VOItumor + 5mm had the highest AUC of 0.803. Multivariate analysis identified age, cirrhosis, hepatitis, albumin-bilirubin grade, gamma-glutamyl transpeptidase level, microvascular invasion, and mosaic architecture as risk factors of RFS. The combined model achieved C-indexes of 0.820 and 0.694 in the training and validation sets, respectively. The Kaplan–Meier curve, calibration curve, and decision curve analyses suggested that the combined model might be a non-invasive and reliable approach for assessing clinical outcomes and accomplishing relapse risk stratification. Conclusion The VOItumor+5mm-based radiomics model in conjunction with clinical-radiological variables can satisfactorily stratify risk for patients with single HCC ≤ 5 cm.

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The Age, Gamma-Glutamyl Transpeptidase and Platelet Index: A Novel Noninvasive Model for Predicting Hepatocellular Carcinoma in Patients with Hepatitis B Virus-Related Liver Cirrhosis

Cited by 2 publications

References 29 publications

Perioperative predictors of outcome of hepatectomy for HBV-related hepatocellular carcinoma

Perioperative predictors of outcome of hepatectomy for HBV-related hepatocellular carcinoma

Performance of multi-regional radiomics features and clinical-radiological variables in the prognostic analysis and risk stratification of single hepatocellular carcinoma

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