Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Department of Ultrasound, Nanjing Drum Tower Hospital, Nanjing, 210008, China.
Technol Cancer Res Treat. 2024 Jan-Dec;23:15330338241281327. doi: 10.1177/15330338241281327.
To investigate risk factors for the early recurrence (ER) of hepatocellular carcinoma (HCC) after radical resection based on preoperative contrast-enhanced ultrasound (CEUS) and clinical features to provide guidance for clinical treatment.
The retrospective analysis selected 130 HCC patients who underwent radical tumor resection from October 2019 to November 2021. All patients underwent preoperative routine ultrasound examination and CEUS, and the pathology was confirmed as HCC after surgery. The patients were divided into two groups based on whether there is an ER, namely the ER group and the non-ER group. The general clinical, routine and CEUS data of patients were collected, and the factors were selected by using the least absolute shrinkage and selection operator (LASSO) regression. Multivariate logistic regression was used to screen the independent influencing factors of ER. Then a nomogram model was established to predict the risk of ER, and the application value of nomogram through internal validation was evaluated.
Multivariate logistic regression identified several independent factors influencing ER after radical HCC resection. Significant factors included early wash-out phase (95%CI = 0.003-0.206, P = 0.001), liver cirrhosis (95%CI = 2.835-221.224, P = 0.004), incomplete envelope (95%CI = 5.247-1056.130,P = 0.001), multiple lesions (95%CI = 1.110-135.424,P = 0.041), Albumin <40 g/L (95%CI = 2.496-127.223,P = 0.004), and Golgi Protein 73 (GP73) ≥ 85 ng/mL (95%CI = 1.594-30.002, P = 0.010), with all P-values <0.05. The nomogram prediction model constructed based on the results of multivariate logistic regression, demonstrated a ROC curve AUC of 0.879, a sensitivity of 93.5%, a specificity of 66.7%, and a C-index of 0.602, indicating superior diagnostic efficiency compared to independent influencing factors. The ER nomogram prediction model confirmed good discrimination and calibration in internal validation.
The CEUS-Clinical combined model effectively monitors the risk of ER in high-risk populations following radical resection of HCC, timely interventions to improve patient prognosis.
基于术前超声造影（CEUS）和临床特征，探讨肝癌（HCC）根治性切除术后早期复发（ER）的危险因素，为临床治疗提供指导。
回顾性分析 2019 年 10 月至 2021 年 11 月期间 130 例 HCC 患者行根治性肿瘤切除术，所有患者均行术前常规超声检查和 CEUS，术后病理证实为 HCC。根据是否有 ER 将患者分为 ER 组和非 ER 组。收集患者的一般临床、常规和 CEUS 数据，采用最小绝对收缩和选择算子（LASSO）回归选择因素。多因素 logistic 回归筛选 ER 的独立影响因素。然后建立预测 ER 风险的列线图模型，并通过内部验证评估列线图的应用价值。
多因素 logistic 回归确定了影响 HCC 根治性切除术后 ER 的几个独立因素。显著因素包括早期洗脱期（95%CI=0.003-0.206，P=0.001）、肝硬化（95%CI=2.835-221.224，P=0.004）、不完全包膜（95%CI=5.247-1056.130，P=0.001）、多发病灶（95%CI=1.110-135.424，P=0.041）、白蛋白<40g/L（95%CI=2.496-127.223，P=0.004）和高尔基体蛋白 73（GP73）≥85ng/ml（95%CI=1.594-30.002，P=0.010），所有 P 值均<0.05。基于多因素 logistic 回归结果构建的列线图预测模型，ROC 曲线 AUC 为 0.879，灵敏度为 93.5%，特异性为 66.7%，C 指数为 0.602，表明与独立影响因素相比，该模型具有较高的诊断效率。内部验证证实 ER 列线图预测模型具有良好的区分度和校准度。
CEUS-临床联合模型可有效监测 HCC 根治性切除术后高危人群 ER 的风险，及时干预以改善患者预后。
