Background: Hepatocellular carcinoma (HCC) is a highly aggressive and heterogeneous malignancy which predominantly arises in the setting of cirrhosis, and there is lack of models to predict prognosis in cirrhotic HCC. This study aims to develop and validate a prediction model based on the pathomics signature and clinicopathological characteristics to predict the prognosis of HCC with cirrhosis. Methods: In this multicenter, retrospective study, 389 patients were enrolled (training cohort: 268; independent validation cohort: 121). A total of 351 pathomics features were extracted from digital H-E–stained images, and a pathomics signature (PSHCC) was constructed using a least absolute shrinkage and selection operator Cox regression model. Then two nomograms were established by combining the PSHCCand clinicopathological characteristics. Further validation was performed in the validation cohort. Results: This study included 389 patients. A 24 feature-based PSHCCwas constructed. A higher PSHCCwas significantly associated with worse OS and DFS in both the training (OS: hazard ratio [HR], 4.341 [95% CI, 3.109–6.062]; DFS: HR, 3.058 [95% CI, 2.223–4.207]) and validation (OS: HR, 4.145 [95% CI, 2.357–7.291]; DFS: HR, 3.395 [95% CI, 2.104–5.479]) cohorts (p< 0.001 for all comparisons). Multivariable analysis revealed that the PSHCCwas an independent factor associated with OS and DFS. Integrating the PSHCCinto pathomics nomograms resulted in better performance for prognosis prediction than the traditional model in both cohorts. Conclusions: The PSHCCmay serve as a reliable surrogate for prognosis, and the nomograms offer promising tools to predict individual outcomes, facilitating personalized management of HCC with cirrhosis.
背景：肝细胞癌（HCC）是一种高度侵袭性且异质性强的恶性肿瘤，主要发生于肝硬化背景下，目前缺乏预测肝硬化相关HCC预后的模型。本研究旨在开发并验证一个基于病理组学特征和临床病理学特征的预测模型，以预测肝硬化相关HCC的预后。方法：在这项多中心回顾性研究中，共纳入389例患者（训练队列：268例；独立验证队列：121例）。从数字化H-E染色图像中提取了351个病理组学特征，并采用最小绝对收缩与选择算子Cox回归模型构建了病理组学特征（PSHCC）。随后，结合PSHCC与临床病理学特征建立了两个列线图模型，并在验证队列中进行了进一步验证。结果：本研究共纳入389例患者。构建了一个基于24个特征的PSHCC。在训练队列（总生存期[OS]：风险比[HR]为4.341 [95% CI, 3.109–6.062]；无病生存期[DFS]：HR为3.058 [95% CI, 2.223–4.207]）和验证队列（OS：HR为4.145 [95% CI, 2.357–7.291]；DFS：HR为3.395 [95% CI, 2.104–5.479]）中，较高的PSHCC均与较差的OS和DFS显著相关（所有比较p<0.001）。多变量分析显示，PSHCC是与OS和DFS相关的独立因素。在两个队列中，将PSHCC整合到病理组学列线图中，其预后预测性能均优于传统模型。结论：PSHCC可作为可靠的预后替代指标，而列线图为预测个体结局提供了有前景的工具，有助于实现肝硬化相关HCC的个体化管理。
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