基于mri的肥胖代谢表型预测hbv相关肝细胞癌术后生存的模型

IF 3.2 3区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

European Journal of Radiology Pub Date : 2025-05-28 DOI:10.1016/j.ejrad.2025.112201

Beixuan Zheng , Bin Wang , Wei Sun , Heqing Wang , Chun Yang , Mengsu Zeng , Ruofan Sheng

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引用次数: 0

摘要

目的：肥胖代谢表型可能影响肝细胞癌（HCC）患者的生存结局。本研究旨在建立一种基于mri的hbv相关HCC患者术后生存预测模型，重点关注肥胖代谢表型。方法对381例hbv相关HCC患者(男性312例；平均年龄55.9±10.7岁)，术前行MRI和根治性手术。患者被分为三种表型：正常体重（NW）、代谢健康超重/肥胖（MHOO）和代谢不健康超重/肥胖（MUOO）。单因素和多因素Cox回归分析确定了总生存（OS）的独立预测因子。建立预测模型，并进行交叉验证。结果smhoo患者的总生存期（OS）明显优于NW患者（调整HR = 0.42, P = 0.030），而MUOO对OS无显著影响（调整HR = 0.92, P = 0.779）。独立预测因子包括MHOO （HR = 0.44, P = 0.036）、AST/ALT比值>；1 (HR = 2.61, P = 0.001),肿瘤负担得分比;5.0 (HR = 3.02, P <；0.001)和动脉边缘增强(HR = 3.61, P <；0.001)。组合模型在训练集（C-index = 0.737）和验证集（C-index = 0.715）上均取得了较好的性能。在整个队列中，预测的高危患者的OS比低危患者差(P <；0.001)和BCLC A期患者(P <；0.001)。该模型在预测疗效方面优于BCLC和CNLC分期系统(所有P <；0.001)和临床净收益。结论smhoo对hbv相关HCC的OS有保护作用。基于mri的模型整合了肥胖代谢表型、AST/ALT比率、肿瘤负荷评分和动脉边缘增强，在生存预测中有价值，与目前的分期系统相比，提供了更好的预后分层。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

MRI-based predictive model with obesity metabolic phenotype for postoperative survival in HBV-related hepatocellular carcinoma

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MRI-based predictive model with obesity metabolic phenotype for postoperative survival in HBV-related hepatocellular carcinoma

Purpose

Obesity metabolic phenotypes may influence survival outcomes in hepatocellular carcinoma (HCC) patients. This study aimed to develop an MRI-based model for postoperative survival prediction in HBV-related HCC patients, focusing on obesity metabolic phenotypes.

Methods

A retrospective cohort of 381 HBV-related HCC patients (312 males; mean age 55.9 ± 10.7 years) who underwent preoperative MRI and curative surgery was studied. Patients were categorized into three phenotypes: normal weight (NW), metabolically healthy overweight/obesity (MHOO) and metabolically unhealthy overweight/obesity (MUOO). Univariate and multivariate Cox regression analyses identified independent predictors of overall survival (OS). A predictive model was established and validated with cross-validation.

Results

MHOO patients showed significantly better overall survival (OS) than NW patients (adjusted HR = 0.42, P = 0.030), while MUOO had no significant effect on OS (adjusted HR = 0.92, P = 0.779). Independent predictors included MHOO (HR = 0.44, P = 0.036), AST/ALT ratio > 1 (HR = 2.61, P = 0.001), tumor burden score > 5.0 (HR = 3.02, P < 0.001) and arterial rim enhancement (HR = 3.61, P < 0.001). The combined model achieved good performance in both training (C-index = 0.737) and validation (C-index = 0.715) sets. The predicted high-risk patients had worse OS than low-risk patients in the whole cohort (P < 0.001) and in patients at BCLC stage A (P < 0.001). The model outperformed the BCLC and CNLC staging systems in predictive efficacy (all P < 0.001) and clinical net benefit.

Conclusions

MHOO is protective for OS in HBV-related HCC. The MRI-based model integrating obesity metabolic phenotype, AST/ALT ratio, tumor burden score and arterial rim enhancement is valuable in survival prediction, offering superior prognostic stratification compared to current staging systems.

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来源期刊

European Journal of Radiology 医学-核医学

CiteScore

6.70

自引率

3.00%

发文量

398

审稿时长

42 days

期刊介绍： European Journal of Radiology is an international journal which aims to communicate to its readers, state-of-the-art information on imaging developments in the form of high quality original research articles and timely reviews on current developments in the field. Its audience includes clinicians at all levels of training including radiology trainees, newly qualified imaging specialists and the experienced radiologist. Its aim is to inform efficient, appropriate and evidence-based imaging practice to the benefit of patients worldwide.