Tumor Radiomic Features on Pretreatment MRI to Predict Response to Lenvatinib plus an Anti-PD-1 Antibody in Advanced Hepatocellular Carcinoma: A Multicenter Study

Abstract: Introduction: Lenvatinib plus an anti-PD-1 antibody has shown promising antitumor effects in patients with advanced hepatocellular carcinoma (HCC), but with clinical benefit limited to a subset of patients. We developed and validated a radiomic-based model to predict objective response to this combination therapy in advanced HCC patients. Methods: Patients (N = 170) who received first-line combination therapy with lenvatinib plus an anti-PD-1 antibody were retrospectively enrolled from 9 Chinese centers; 124 and 46 into the training and validation cohorts, respectively. Radiomic features were extracted from pretreatment contrast-enhanced MRI. After feature selection, clinicopathologic, radiomic, and clinicopathologic-radiomic models were built using a neural network. The performance of models, incremental predictive value of radiomic features compared with clinicopathologic features and relationship between radiomic features and survivals were assessed. Results: The clinicopathologic model modestly predicted objective response with an AUC of 0.748 (95% CI: 0.656–0.840) and 0.702 (95% CI: 0.547–0.884) in the training and validation cohorts, respectively. The radiomic model predicted response with an AUC of 0.886 (95% CI: 0.815–0.957) and 0.820 (95% CI: 0.648–0.984), respectively, with good calibration and clinical utility. The incremental predictive value of radiomic features to clinicopathologic features was confirmed with a net reclassification index of 47.9% (p < 0.001) and 41.5% (p = 0.025) in the training and validation cohorts, respectively. Furthermore, radiomic features were associated with overall survival and progression-free survival both in the training and validation cohorts, but modified albumin-bilirubin grade and neutrophil-to-lymphocyte ratio were not. Conclusion: Radiomic features extracted from pretreatment MRI can predict individualized objective response to combination therapy with lenvatinib plus an anti-PD-1 antibody in patients with unresectable or advanced HCC, provide incremental predictive value over clinicopathologic features, and are associated with overall survival and progression-free survival after initiation of this combination regimen.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Tumor Radiomic Features on Pretreatment MRI to Predict Response to Lenvatinib plus an Anti-PD-1 Antibody in Advanced Hepatocellular Carcinoma: A Multicenter Study ; volume:12 ; number:3 ; year:2022 ; pages:262-276 ; extent:15 ; Liver cancer ; 12, Heft 3 (2022), 262-276 (gesamt 15)

Contributors, Places and Time

• Creator: Xu, Bin ; Dong, San-Yuan ; Bai, Xue-Li ; Song, Tian-Qiang ; Zhang, Bo-Heng ; Zhou, Le-Du ; Chen, Yong-Jun ; Zeng, Zhi-Ming ; Wang, Kui ; Zhao, Hai-Tao ; Lu, Na ; Zhang, Wei ; Li, Xu-Bin ; Zheng, Su-Su ; Long, Guo ; Yang, Yu-Chen ; Huang, Hua-Sheng ; Huang, Lan-Qing ; Wang, Yun-Chao ; Liang, Fei ; Zhu, Xiao-Dong ; Huang, Cheng ; Shen, Ying-Hao ; Zhou, Jian ; Zeng, Meng-Su ; Fan, Jia ; Rao, Sheng-Xiang ; Sun, Hui-Chuan

Further information

• DOI: 10.1159/000528034
• URN: urn:nbn:de:101:1-2502171750219.291293335360
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:21 AM CEST