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结合临床和实验室指标的影像衍生生物标志物可预测肝移植术后肝细胞癌的复发

Imaging-Derived Biomarkers Integrated with Clinical and Laboratory Values Predict Recurrence of Hepatocellular Carcinoma After Liver Transplantation.

作者信息

Hoang Thi Phuong Thao, Schindler Philipp, Börner Nikolaus, Masthoff Max, Gerwing Mirjam, von Beauvais Philippa, De Toni Enrico N, Lange Christian M, Trebicka Jonel, Morgül Haluk, Seidensticker Max, Ricke Jens, Pascher Andreas, Guba Markus, Ingrisch Michael, Wildgruber Moritz, Öcal Osman

机构信息

Department of Radiology, University Hospital, LMU Munich, Munich, Germany.

Clinic for Radiology, University Hospital Muenster, Muenster, Germany.

出版信息

J Hepatocell Carcinoma. 2023 Dec 18;10:2277-2289. doi: 10.2147/JHC.S431503. eCollection 2023.

DOI:10.2147/JHC.S431503
PMID:38143909
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10740736/
Abstract

PURPOSE

To investigate the prognostic value of computed tomography (CT) derived imaging biomarkers in hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) and develop a predictive nomogram model.

PATIENTS AND METHODS

This retrospective study included 178 patients with histopathologically confirmed HCC who underwent liver transplantation between 2007 and 2021 at the two academic liver centers. We evaluated dedicated imaging features from baseline multiphase contrast-enhanced CT supplemented by several clinical findings and laboratory parameters. Time-to-recurrence was estimated by Kaplan-Meier analysis. Univariable Cox proportional hazard regression and multivariable Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to assess independent prognostic factors for recurrence. A nomogram model was then built based on the independent factors selected through LASSO regression, to predict the probabilities of HCC recurrence at one, three, and five years.

RESULTS

The rate of HCC recurrence after LT was 17.4% (31 of 178). The LASSO analysis revealed six independent predictors associated with an elevated risk of tumor recurrence. These predictors included the presence of peritumoral enhancement, the presence of over three tumor lesions, the largest tumor diameter greater than 3 cm, serum alpha-fetoprotein (AFP) levels exceeding 400 ng/mL, and the presence of a tumor capsule. Conversely, a history of bridging therapies was found to be correlated with a reduced risk of HCC recurrence. In addition, Kaplan-Meier curves showed patients with irregular margin, satellite nodules, or small lesions displayed shorter time-to-recurrence. Our nomogram demonstrated good performance, yielding a C-index of 0.835 and AUC values of 0.86, 0.88, and 0.85 for the predictions of 1-year, 3-year, and 5-year TTR, respectively.

CONCLUSION

Imaging parameters derived from baseline contrast-enhanced CT showing malignant behavior and aggressive growth patterns, along with serum AFP and history of bridging therapies, show potential as biomarkers for predicting HCC recurrence after transplantation.

摘要

目的

探讨计算机断层扫描(CT)衍生的影像生物标志物在肝移植(LT)后肝细胞癌(HCC)复发中的预后价值,并建立预测列线图模型。

患者与方法

这项回顾性研究纳入了2007年至2021年期间在两个学术性肝脏中心接受肝移植的178例经组织病理学确诊为HCC的患者。我们评估了基线多期对比增强CT的专用影像特征,并辅以多项临床发现和实验室参数。采用Kaplan-Meier分析估计复发时间。单变量Cox比例风险回归和多变量最小绝对收缩和选择算子(LASSO)回归用于评估复发的独立预后因素。然后基于通过LASSO回归选择的独立因素建立列线图模型,以预测HCC在1年、3年和5年复发的概率。

结果

LT后HCC复发率为17.4%(178例中的31例)。LASSO分析揭示了六个与肿瘤复发风险升高相关的独立预测因素。这些预测因素包括瘤周强化的存在、三个以上肿瘤病灶的存在、最大肿瘤直径大于3 cm、血清甲胎蛋白(AFP)水平超过400 ng/mL以及肿瘤包膜的存在。相反,发现桥接治疗史与HCC复发风险降低相关。此外,Kaplan-Meier曲线显示边缘不规则、有卫星结节或小病灶的患者复发时间较短。我们的列线图表现良好,1年、3年和5年复发时间(TTR)预测的C指数为0.835,AUC值分别为0.86、0.88和0.85。

结论

来自基线对比增强CT的显示恶性行为和侵袭性生长模式的影像参数,以及血清AFP和桥接治疗史,显示出作为预测移植后HCC复发生物标志物的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/a9630f328973/JHC-10-2277-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/0fd35dd3b7df/JHC-10-2277-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/c3d1ebbda343/JHC-10-2277-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/4be59820e0e7/JHC-10-2277-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/ebcba8b28a76/JHC-10-2277-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/80d8c605f967/JHC-10-2277-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/a9630f328973/JHC-10-2277-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/0fd35dd3b7df/JHC-10-2277-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/c3d1ebbda343/JHC-10-2277-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/4be59820e0e7/JHC-10-2277-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/ebcba8b28a76/JHC-10-2277-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/80d8c605f967/JHC-10-2277-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd54/10740736/a9630f328973/JHC-10-2277-g0006.jpg

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