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系统评价:肝移植后肝细胞癌复发的风险预测模型。

Systematic review: risk prediction models for recurrence of hepatocellular carcinoma after liver transplantation.

机构信息

Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Institution of Organ Transplantation, Zhejiang University, Hangzhou, China.

出版信息

Transpl Int. 2020 Jul;33(7):697-712. doi: 10.1111/tri.13585. Epub 2020 Feb 25.

DOI:10.1111/tri.13585
PMID:31985857
Abstract

Recurrence of hepatocellular carcinoma (HCC) after liver transplantation (LT) is a significant clinical problem associated with poor surgical outcomes. This study aims to summarize the current evidence on risk prediction models of HCC recurrence after LT. PubMed and EMBASE were searched to May 25, 2019, for relevant articles. Studies originally designed to develop or validate a risk prediction model for HCC recurrence after LT were included. Two independent authors summarized the study characteristics and evaluated the risk of bias and applicability concerns in the included studies. From 26 included studies, 18 original risk prediction models were determined, but only five models were externally validated. The average number of predictors involved in the construction of risk models was three. The most frequently employed predictors were alpha-fetoprotein, tumor size, vascular invasion, tumor number, tumor differentiation, and neutrophil-lymphocyte ratio. Most studies showed good discriminatory performance (AUC >0.75). The overall quality of the included studies was generally low. Most of the original models lacked the highly recommended external and prospective validation in diverse populations. The AFP model was the well-validated preoperative risk model that can stratify patients into high- and low-risk groups.

摘要

肝移植(LT)后肝细胞癌(HCC)的复发是一个重大的临床问题,与手术结果不佳有关。本研究旨在总结 LT 后 HCC 复发风险预测模型的现有证据。检索了 PubMed 和 EMBASE 数据库,以获取 2019 年 5 月 25 日之前的相关文章。纳入了最初设计用于开发或验证 LT 后 HCC 复发风险预测模型的研究。两名独立作者总结了研究特征,并评估了纳入研究的偏倚风险和适用性问题。从 26 项纳入的研究中,确定了 18 个原始风险预测模型,但只有 5 个模型进行了外部验证。构建风险模型所涉及的预测因子的平均数量为 3 个。最常使用的预测因子是甲胎蛋白、肿瘤大小、血管侵犯、肿瘤数量、肿瘤分化和中性粒细胞-淋巴细胞比值。大多数研究显示出良好的区分性能(AUC>0.75)。纳入研究的总体质量普遍较低。大多数原始模型缺乏在不同人群中进行的高度推荐的外部和前瞻性验证。AFP 模型是一种经过充分验证的术前风险模型,可以将患者分为高风险和低风险组。

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