ArticleBMC cancer2021
Predictive potential of Nomogram based on GMWG for patients with hepatocellular carcinoma after radical resection.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A visualized nomogram to predict intravenous immunoglobulin resistance in Kawasaki disease: a study based on the population in Southern China.Italian journal of pediatrics · 2025Article
- CT Radiomics Combined with Metabolic-Biomarkers Enables Early Recurrence Prediction in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Article
- Construction and evaluation of a liver cancer risk prediction model based on machine learning.World journal of gastrointestinal oncology · 2024Article
- The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.Frontiers in medicine · 2024Article
- Beta2-Microglobulin as Predictive Biomarkers in the Prognosis of Hepatocellular Carcinoma and Development of a New Nomogram.Journal of hepatocellular carcinoma · 2023Article
- The Ratio of Preoperative Serum Biomarkers Predicts Prognosis in Patients With Oral Squamous Cell Carcinoma.Frontiers in oncology · 2021Article
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9 authors.
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Abstract
backgroundSince it's a challenging task to precisely predict the prognosis of patients with hepatocellular carcinoma (HCC). We developed a nomogram based on a novel indicator GMWG [(Geometric Mean of gamma-glutamyltranspeptidase (GGT) and white blood cell (WBC)] and explored its potential in the prognosis for HCC patients.
methodsThe patients enrolled in this study were randomly assigned to training and validation cohorts. And we performed the Least Absolute Shrinkage and Selection Operator proportional hazards model (LASSO Cox) model with clinical characteristics, serum indexes, and novel GMWG. Multivariate analysis was performed to build a nomogram. The performance of the nomogram was evaluated by C-index, the area under the receiver operating characteristic curve (AUC), and the calibration curve. Kaplan-Meier curves showed discrimination of the nomogram. Clinical utility was assessed by decision curve analysis (DCA). The discrimination ability of the nomogram was determined by the net reclassification index (NRI).
resultsThe geometric mean of GGT and white WBC count (GMWG), neutrophil to lymphocyte ratio (NLR), and tumor size were significantly associated with the overall survival (OS). The variables above were used to develop the nomogram. The indexes of nomogram were 0.70 and 071 in the training or validation cohort, respectively. AUC of 1-, 3- and 5-year OS showed satisfactory accuracy as well. The calibration curve showed agreement between the ideal and predicted values. Kaplan-Meier curves based on the overall survival (OS) and disease-free survival (DFS) showed significant differences between nomogram predictive low and high groups. DCA showed clinical utilities while NRI showed discrimination ability in both training or validation cohort.
conclusionsGMWG might be a potential prognostic indicator for patients with HCC. The nomogram containing GMWG also showed satisfaction prediction capacity.
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