Frontiers in Endocrinology (Sep 2024)

A nomogram model for early recurrence of HBV-related hepatocellular carcinomas after radical hepatectomy

  • Yu Zhu,
  • Yu Zhu,
  • Yu Zhu,
  • Ai-Dong Wang,
  • Ling-Ling Gu,
  • Qi-Qiang Dai,
  • Guo-Qun Zheng,
  • Ting Chen,
  • Chun-Long Wu,
  • Wei-Dong Jia,
  • Fa-Biao Zhang

DOI
https://doi.org/10.3389/fendo.2024.1374245
Journal volume & issue
Vol. 15

Abstract

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BackgroundTo identify the risk factors and construct a predictive model for early recurrence of hepatitis B virus(HBV-)- related hepatocellular carcinomas(HCCs) after radical resection.Data and methodsA total of 465 HBV-related HCC patients underwent radical resections between January 1, 2012 and August 31, 2018.Their data were collected through the inpatient information management system of the First Affiliated Hospital of University of Science and Technology of China. Survival and subgroup analyses of early recurrence among male and female patients were performed using Kaplan-Meier curves. The independent risk factors associated with early postoperative tumor recurrence were analyzed using multivariate Cox proportional hazards regression model. Based on these independent risk factors, a risk function model for early recurrence was fitted, and a column chart for the prediction model was drawn for internal and external validation.ResultsA total of 181 patients developed early recurrences, including 156 males and 25 females. There was no difference in the early recurrence rates between males and females. Tumor diameters>5cm, microvascular invasion and albumin level<35 g/L were independent risk factors for early recurrence. A nomogram for the early recurrence prediction model was drawn; the areas under the curve for the model and for external verification were 0.638 and 0.655, respectively.ConclusionTumor diameter>5 cm, microvascular invasion, and albumin level<35 g/L were independent risk factors for early recurrence. The prediction model based on three clinical indicators could predict early recurrence, with good discrimination, calibration, and extrapolation.

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