Xie Gui-Lin, Liang Lei, Ye Tai-Wei, Xu Fei-Qi, Wang Dong-Dong, Xie Ya-Ming, Zhang Kang-Jun, Fu Tian-Wei, Yao Wei-Feng, Liu Jun-Wei, Zhang Cheng-Wu
Department of Hepatobiliary Surgery, Affiliated Hospital of Shaoxing University, Shaoxing, Zhejiang, China.
General Surgery, Cancer Center, Department of Hepatobiliary and Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Front Oncol. 2023 Apr 14;13:1089716. doi: 10.3389/fonc.2023.1089716. eCollection 2023.
An increasing number of studies have confirmed that non-textbook outcomes (non-TO) are a risk factor for the long-term outcome of malignant tumors. It is particularly important to identify the predictive factors of non-TO to improve the quality of surgical treatment. We attempted to construct two nomograms for preoperative and postoperative prediction of non-TO after laparoscopic hepatectomy for hepatocellular carcinoma (HCC).
Patients who underwent curative-intent hepatectomy for HCC between 2014 and 2021 at two Chinese hospitals were analyzed. Using univariate and multivariate analyses, the independent predictors of non-TO were identified. The prediction accuracy is accurately measured by the receiver operating characteristic (ROC) curve and calibration curve. ROC curves for the preoperative and postoperative models, Child-Pugh grade, BCLC staging, and 8th TNM staging were compared relative to predictive accuracy for non-TO.
Among 515 patients, 286 patients (55.5%) did not achieve TO in the entire cohort. Seven and eight independent risk factors were included in the preoperative and postoperative predictive models by multivariate logistic regression analysis, respectively. The areas under the ROC curves for the postoperative and preoperative models, Child-Pugh grade, BCLC staging, and 8th TNM staging in predicting non-TO were 0.762, 0.698, 0.579, 0.569, and 0.567, respectively.
Our proposed preoperative and postoperative nomogram models were able to identify patients at high risk of non-TO following laparoscopic resection of HCC, which may guide clinicians to make individualized surgical decisions, improve postoperative survival, and plan adjuvant therapy against recurrence.
越来越多的研究证实，非教科书式结局（non-TO）是恶性肿瘤长期结局的一个危险因素。识别非教科书式结局的预测因素对于提高外科治疗质量尤为重要。我们试图构建两个列线图，用于术前和术后预测肝细胞癌（HCC）腹腔镜肝切除术后的非教科书式结局。
分析了2014年至2021年期间在中国两家医院接受根治性肝切除术治疗HCC的患者。通过单因素和多因素分析，确定非教科书式结局的独立预测因素。预测准确性通过受试者工作特征（ROC）曲线和校准曲线进行精确测量。比较术前和术后模型、Child-Pugh分级、BCLC分期和第8版TNM分期相对于非教科书式结局预测准确性的ROC曲线。
在515例患者中，整个队列中有286例患者（55.5%）未达到教科书式结局。通过多因素逻辑回归分析，术前和术后预测模型分别纳入了7个和8个独立危险因素。术后和术前模型、Child-Pugh分级、BCLC分期和第8版TNM分期在预测非教科书式结局时的ROC曲线下面积分别为0.762、0.698、0.579、0.569和0.567。
我们提出的术前和术后列线图模型能够识别HCC腹腔镜切除术后非教科书式结局的高危患者，这可能有助于临床医生做出个体化的手术决策，提高术后生存率，并规划针对复发的辅助治疗。
