1. Development of a Better Nomogram for Prediction of Preoperative Microvascular Invasion and Postoperative Prognosis in Hepatocellular Carcinoma Patients: A Comparison Study.
- Author
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Pei J, Wang L, and Li H
- Subjects
- Humans, Male, Middle Aged, Aged, Neoplasm Invasiveness diagnosis, Neoplasm Invasiveness pathology, Logistic Models, Predictive Value of Tests, Proportional Hazards Models, Reproducibility of Results, Preoperative Period, Postoperative Period, Precision Medicine methods, alpha-Fetoproteins analysis, Liver Cirrhosis diagnosis, Liver Cirrhosis etiology, Nomograms, Carcinoma, Hepatocellular complications, Carcinoma, Hepatocellular diagnosis, Carcinoma, Hepatocellular surgery, Liver Neoplasms complications, Liver Neoplasms diagnosis, Liver Neoplasms surgery, Microcirculation, Liver blood supply, Liver pathology, Liver surgery, Neoplasm Recurrence, Local diagnosis, Neoplasm Recurrence, Local etiology, Neoplasm Recurrence, Local pathology
- Abstract
Objective: Personalized precision medicine can be facilitated by clinically available preoperative microvascular invasion (MVI) prediction models that are reliable and postoperative MVI pathological grade-related recurrence prediction models that are accurate. In this study, we aimed to compare different mathematical models to derive the best preoperative prediction and postoperative recurrence prediction models for MVI., Methods: A total of 143 patients with hepatocellular carcinoma (HCC) whose clinical, laboratory, imaging, and pathological data were available were included in the analysis. Logistic regression, Cox proportional hazards regression, LASSO regression with 10-fold cross-validation, stepwise regression, and random forest methods were used for variable screening and predictive modeling. The accuracy and validity of seven preoperative MVI prediction models and five postoperative recurrence prediction models were compared in terms of C-index, net reclassification improvement, and integrated discrimination improvement., Results: Multivariate logistic regression analysis revealed that a preoperative nomogram model with the variables cirrhosis diagnosis, alpha-fetoprotein > 400, and diameter, shape, and number of lesions can predict MVI in patients with HCC reliably. Postoperatively, a nomogram model with MVI grade, number of lesions, capsule involvement status, macrovascular invasion, and shape as the variables was selected after LASSO regression and 10-fold cross-validation analysis to accurately predict the prognosis for different MVI grades. The number and shape of the lesions were the most common predictors of MVI preoperatively and recurrence postoperatively., Conclusions: Our study identified the best statistical approach for the prediction of preoperative MVI as well as postoperative recurrence in patients with HCC based on clinical, imaging, and laboratory tests results. This could expedite preoperative treatment decisions and facilitate postoperative management., Competing Interests: The authors declare no conflict of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)
- Published
- 2025
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