Data Sheet 1_Myeloid response evaluated by noninvasive CT imaging predicts post-surgical survival and immune checkpoint therapy benefits in patients with hepatocellular carcinoma.pdf

BackgroundThe potential of preoperative CT in the assessment of myeloid immune response and its application in predicting prognosis and immune-checkpoint therapy outcomes in hepatocellular carcinoma (HCC) has not been explored.
MethodsA total of 165 patients with pathological slides and multi-phase CT images were included to develop a radiomics signature for predicting the imaging-based myeloid response score (iMRS). Overall survival (OS) and recurrence-free survival (RFS) were assessed according to the iMRS risk group and validated in a surgical resection cohort (n = 98). The complementary advantage of iMRS incorporating significant clinicopathologic factors was investigated by the Cox proportional hazards analysis. Additionally, the iMRS in inferring the benefits of immune checkpoint therapy was explored in an immunotherapy cohort (n = 36).
ResultsWe showed that AUCs of the optimal radiomics signature for iMRS were 0.941 [95% confidence interval (CI), 0.909–0.973] and 0.833 (0.798–0.868) in the training and test cohorts, respectively. High iMRS was associated with poor RFS and OS. The prognostic performance of the Clinical-iMRS nomogram was better than that of a single parameter (p < 0.05), with a 1-, 3-, and 5-year C-index for RFS of 0.729, 0.709, and 0.713 in the training, test, and surgical resection cohorts, respectively. A high iMRS score predicted a higher proportion of objective response (vs. progressive disease or stable disease; odds ratio, 2.311; 95% CI, 1.144–4.672; p = 0.020; AUC, 0.718) in patients treated with anti-PD-1 and PD-L1.
ConclusionsiMRS may provide a promising method for predicting local myeloid immune responses in HCC patients, inferring postsurgical prognosis, and evaluating benefits of immune checkpoint therapy.

背景：目前针对术前CT在肝细胞癌（hepatocellular carcinoma, HCC）骨髓免疫应答评估中的应用价值，以及其在预测患者预后与免疫检查点治疗疗效方面的潜力，尚未有相关研究探索。
方法：本研究共纳入165例具备病理切片与多期CT影像的患者，用于构建放射组学特征模型以预测基于影像的骨髓应答评分（imaging-based myeloid response score, iMRS）。根据iMRS风险分组对患者的总生存期（overall survival, OS）与无复发生存期（recurrence-free survival, RFS）进行评估，并在98例手术切除队列中进行验证。通过Cox比例风险回归分析，探究整合了显著临床病理因素的iMRS的补充预后价值。此外，在36例免疫治疗队列中，探索了iMRS对免疫检查点治疗获益的预测效能。
结果：本研究构建的最优放射组学特征模型用于预测iMRS时，训练队列与测试队列的曲线下面积（area under the curve, AUC）分别为0.941[95%置信区间（confidence interval, CI）：0.909~0.973]与0.833（0.798~0.868）。高iMRS评分与较差的RFS和OS显著相关。整合临床病理因素的Clinical-iMRS列线图的预后效能优于单一参数（p<0.05）；在训练、测试与手术切除队列中，该列线图对应1年、3年、5年RFS的C指数分别为0.729、0.709与0.713。在接受抗PD-1与PD-L1治疗的患者中，高iMRS评分可预测更高的客观缓解率（相较于疾病进展或病情稳定；优势比：2.311；95%CI：1.144~4.672；p=0.020；AUC=0.718）。
结论：iMRS有望成为预测肝细胞癌患者局部骨髓免疫应答、评估术后预后以及判断免疫检查点治疗获益的潜在工具。