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- Title
Tumor Radiomic Features on Pretreatment MRI to Predict Response to Lenvatinib plus an Anti-PD-1 Antibody in Advanced Hepatocellular Carcinoma: A Multicenter Study.
- Authors
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
- 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.
- Subjects
PROGRESSION-free survival; CONTRAST-enhanced magnetic resonance imaging; FEATURE extraction; MAGNETIC resonance imaging; NEUTROPHIL lymphocyte ratio
- Publication
Liver Cancer (2235-1795), 2023, Vol 12, Issue 3, p262
- ISSN
2235-1795
- Publication type
Article
- DOI
10.1159/000528034