State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, P.R. China.
Department of Pathology, Sun Yat-Sen University Cancer Center, 651# Dong Feng Road East, Guangzhou, 510060, Guangdong, China.
J Transl Med. 2024 May 18;22(1):472. doi: 10.1186/s12967-024-05296-3.
Vessels encapsulating tumor clusters (VETC) is a newly described vascular pattern that is distinct from microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Despite its importance, the current pathological diagnosis report does not include information on VETC and hepatic plates (HP). We aimed to evaluate the prognostic value of integrating VETC and HP (VETC-HP model) in the assessment of HCC.
A total of 1255 HCC patients who underwent radical surgery were classified into training (879 patients) and validation (376 patients) cohorts. Additionally, 37 patients treated with lenvatinib were studied, included 31 patients in high-risk group and 6 patients in low-risk group. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to establish a prognostic model for the training set. Harrell's concordance index (C-index), time-dependent receiver operating characteristics curve (tdROC), and decision curve analysis were utilized to evaluate our model's performance by comparing it to traditional tumor node metastasis (TNM) staging for individualized prognosis.
A prognostic model, VETC-HP model, based on risk scores for overall survival (OS) was established. The VETC-HP model demonstrated robust performance, with area under the curve (AUC) values of 0.832 and 0.780 for predicting 3- and 5-year OS in the training cohort, and 0.805 and 0.750 in the validation cohort, respectively. The model showed superior prediction accuracy and discrimination power compared to TNM staging, with C-index values of 0.753 and 0.672 for OS and disease-free survival (DFS) in the training cohort, and 0.728 and 0.615 in the validation cohort, respectively, compared to 0.626 and 0.573 for TNM staging in the training cohort, and 0.629 and 0.511 in the validation cohort. Thus, VETC-HP model had higher C-index than TNM stage system(p < 0.01).Furthermore, in the high-risk group, lenvatinib alone appeared to offer less clinical benefit but better disease-free survival time.
The VETC-HP model enhances DFS and OS prediction in HCC compared to traditional TNM staging systems. This model enables personalized temporal survival estimation, potentially improving clinical decision-making in surveillance management and treatment strategies.
包裹肿瘤簇的血管（VETC）是一种新描述的血管模式，与肝细胞癌（HCC）患者的微血管侵犯（MVI）不同。尽管它很重要，但目前的病理诊断报告并未包含关于 VETC 和肝板（HP）的信息。我们旨在评估整合 VETC 和 HP（VETC-HP 模型）在 HCC 评估中的预后价值。
共对 1255 例接受根治性手术的 HCC 患者进行了研究，分为训练队列（879 例）和验证队列（376 例）。此外，还研究了 37 例接受仑伐替尼治疗的患者，其中高危组 31 例，低危组 6 例。采用最小绝对收缩和选择算子（LASSO）回归分析建立了训练组的预后模型。采用 Harrell 一致性指数（C 指数）、时间依赖性接受者操作特征曲线（tdROC）和决策曲线分析将我们的模型与传统的肿瘤淋巴结转移（TNM）分期进行比较，对个体化预后进行了比较。
建立了一种基于总生存（OS）风险评分的预后模型，即 VETC-HP 模型。VETC-HP 模型表现出良好的性能，在训练队列中预测 3 年和 5 年 OS 的曲线下面积（AUC）值分别为 0.832 和 0.780，在验证队列中分别为 0.805 和 0.750。与 TNM 分期相比，该模型具有更高的预测准确性和区分能力，在训练队列中，OS 和无病生存（DFS）的 C 指数分别为 0.753 和 0.672，在验证队列中，OS 和 DFS 的 C 指数分别为 0.728 和 0.615，而 TNM 分期的 C 指数分别为 0.626 和 0.573。在训练队列中，DFS 的 C 指数比 TNM 分期系统高（p<0.01）。此外，在高危组中，仑伐替尼单独治疗似乎提供的临床获益较少，但无病生存时间更长。
与传统的 TNM 分期系统相比，VETC-HP 模型可提高 HCC 的 DFS 和 OS 预测能力。该模型能够进行个性化的时间生存估计，有可能改善监测管理和治疗策略中的临床决策。
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