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基于术前循环肿瘤细胞状态和临床病理因素的肝癌术后肝外复发预测的列线图。

Nomograms for postsurgical extrahepatic recurrence prediction of hepatocellular carcinoma based on presurgical circulating tumor cell status and clinicopathological factors.

机构信息

Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, China.

Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, Nanning, China.

出版信息

Cancer Med. 2023 Jul;12(14):15065-15078. doi: 10.1002/cam4.6178. Epub 2023 Jun 20.

Abstract

BACKGROUND AND AIMS

Extrahepatic recurrence (EHR) is one of the major reasons for the poor prognosis of hepatocellular carcinoma (HCC). The present study aimed to develop and assess the performance of predictive models by using a combination of presurgical circulating tumor cell (CTCs) data and clinicopathological features to screen patients at high risk of EHR to achieve precise decision-making.

PATIENTS AND METHODS

A total of 227 patients with recurrent HCC and preoperative CTC data from January 2014 to August 2019 were enrolled. All patients were randomly assigned to one of two cohorts: development or validation. Two preoperative and postoperative nomogram models for EHR prediction were developed and multi-dimensionally validated.

RESULTS

Patients with EHR had generally lower recurrence-free survival (p < 0.001), and overall survival (p < 0.001), and significantly higher CTC counts (epithelial CTCs, epithelial/mesenchymal hybrid CTCs, and mesenchymal CTCs count, all p < 0.05) than those without EHR. Univariate and multivariate analyses revealed that EHR was associated with four risk factors in the development cohort: total CTC count (p = 0.014), tumor size (p = 0.028), node number (p = 0.045), and microvascular invasion (p = 0.035). These factors were incorporated into two nomogram models (preoperative and postoperative), which reliably predicted EHR through multidimensional verification (e.g., calibration plot, receiver operating characteristic analysis, decision curve analysis, and clinical impact curve analysis) in the development and validation cohorts, respectively. With threshold of scores of 100.3 and 176.8 before and after surgery respectively, both nomograms were able to stratify patients into two distinct prognostic subgroups (all p < 0.05).

CONCLUSION

The present study proposed two nomogram models integrating presurgical CTC counts and clinicopathological risks and showed relatively good predictive performance of EHR, which may be beneficial to the clinical practice of HCC recurrence. Further multicenter studies are needed to assess its general applicability.

摘要

背景与目的

肝癌(HCC)患者肝外复发(EHR)是预后不良的主要原因之一。本研究旨在通过结合术前循环肿瘤细胞(CTC)数据和临床病理特征,建立并评估预测模型,以筛选出 EHR 风险较高的患者,从而实现精准决策。

患者与方法

本研究纳入了 2014 年 1 月至 2019 年 8 月期间 227 例复发 HCC 患者的术前 CTC 数据。所有患者被随机分配到开发或验证队列之一。建立并多维验证了两个用于 EHR 预测的术前和术后列线图模型。

结果

EHR 患者的无复发生存率(p<0.001)和总生存率(p<0.001)普遍较低,CTC 计数明显较高(上皮 CTCs、上皮/间充质杂交 CTCs 和间充质 CTCs 计数,均 p<0.05)。单因素和多因素分析显示,EHR 与发展队列中的四个风险因素相关:总 CTC 计数(p=0.014)、肿瘤大小(p=0.028)、淋巴结数量(p=0.045)和微血管侵犯(p=0.035)。这些因素被纳入到两个列线图模型(术前和术后)中,通过开发和验证队列的多维验证(如校准图、接受者操作特征分析、决策曲线分析和临床影响曲线分析),可以可靠地预测 EHR。术前和术后的评分阈值分别为 100.3 和 176.8,两个列线图均能够将患者分为两个不同的预后亚组(均 p<0.05)。

结论

本研究提出了两个整合术前 CTC 计数和临床病理风险的列线图模型,显示了对 EHR 相对较好的预测性能,这可能有助于 HCC 复发的临床实践。需要进一步的多中心研究来评估其普遍适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4775/10417085/9ba1dc89d18e/CAM4-12-15065-g004.jpg

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