Department of Infectious Diseases and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Front Immunol. 2021 Jan 8;11:613946. doi: 10.3389/fimmu.2020.613946. eCollection 2020.
There is no study accessible now assessing the prognostic aspect of radiomics for anti-PD-1 therapy for patients with HCC.
The aim of this study was to develop and validate a radiomics nomogram by incorporating the pretreatment contrast-enhanced Computed tomography (CT) images and clinical risk factors to estimate the anti-PD-1 treatment efficacy in Hepatocellular Carcinoma (HCC) patients.
A total of 58 patients with advanced HCC who were refractory to the standard first-line of therapy, and received PD-1 inhibitor treatment with Toripalimab, Camrelizumab, or Sintilimab from 1st January 2019 to 31 July 2020 were enrolled and divided into two sets randomly: training set (n = 40) and validation set (n = 18). Radiomics features were extracted from non-enhanced and contrast-enhanced CT scans and selected by using the least absolute shrinkage and selection operator (LASSO) method. Finally, a radiomics nomogram was developed based on by univariate and multivariate logistic regression analysis. The performance of the nomogram was evaluated by discrimination, calibration, and clinical utility.
Eight radiomics features from the whole tumor and peritumoral regions were selected and comprised of the Fusion Radiomics score. Together with two clinical factors (tumor embolus and ALBI grade), a radiomics nomogram was developed with an area under the curve (AUC) of 0.894 (95% CI, 0.797-0.991) and 0.883 (95% CI, 0.716-0.998) in the training and validation cohort, respectively. The calibration curve and decision curve analysis (DCA) confirmed that nomogram had good consistency and clinical usefulness.
This study has developed and validated a radiomics nomogram by incorporating the pretreatment CECT images and clinical factors to predict the anti-PD-1 treatment efficacy in patients with advanced HCC.
目前尚无研究评估放射组学对 HCC 患者抗 PD-1 治疗的预后价值。
本研究旨在通过纳入治疗前增强 CT 图像和临床危险因素，建立并验证一个放射组学列线图，以预测 HCC 患者接受 PD-1 抑制剂治疗的疗效。
本研究共纳入了 2019 年 1 月 1 日至 2020 年 7 月 31 日期间，58 例因标准一线治疗无效而接受特瑞普利单抗、卡瑞利珠单抗或信迪利单抗治疗的晚期 HCC 患者，将其随机分为训练集（n=40）和验证集（n=18）。从平扫和增强 CT 扫描中提取放射组学特征，采用最小绝对收缩和选择算子（LASSO）方法进行选择。最后，通过单因素和多因素逻辑回归分析建立放射组学列线图。通过判别、校准和临床实用性评估列线图的性能。
从全肿瘤和肿瘤周围区域共选择了 8 个放射组学特征，组成融合放射组学评分。联合两个临床因素（肿瘤栓子和 ALBI 分级），建立了一个放射组学列线图，在训练集和验证集中的曲线下面积（AUC）分别为 0.894（95%CI：0.797-0.991）和 0.883（95%CI：0.716-0.998）。校准曲线和决策曲线分析（DCA）证实了该列线图具有良好的一致性和临床实用性。
本研究建立并验证了一个放射组学列线图，该列线图结合了治疗前 CECT 图像和临床因素，可预测晚期 HCC 患者接受抗 PD-1 治疗的疗效。
