Xie Weishun, Liu Jungang, Huang Xiaoliang, Wu Guo, Jeen Franco, Chen Shaomei, Zhang Chuqiao, Yang Wenkang, Li Chan, Li Zhengtian, Ge Lianying, Tang Weizhong
Department of Gastrointestinal Surgery, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China.
Guangxi Clinical Research Center for Colorectal Cancer, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China.
Oncol Lett. 2019 Dec;18(6):5785-5792. doi: 10.3892/ol.2019.10937. Epub 2019 Sep 30.
Vascular invasion (VI) is an important feature for systemic recurrence and an indicator for the application of adjuvant therapy in colorectal cancer (CRC). Preoperative knowledge of VI is important in determining whether adjuvant therapy is necessary, as well as the adequacy of surgical resection. In the present study, a predictive nomogram for VI in patients with CRC was constructed. The prediction model consisted of 664 eligible patients with CRC, who were divided into a training set (n=468) and a validation set (n=196). Data were collected between August 2013 and April 2018. The feature selection model was established using the least absolute shrinkage and selection operator regression model. Multivariable logistic regression analysis was used to construct the predictive nomogram. The performance of the nomogram was evaluated by calibration, discrimination and clinical usefulness. Differentiation, computed tomography (CT)-based on N stage (CT N stage), hemameba and tumor distance from the anus (cm) were integrated into the nomogram. The nomogram exhibited good discrimination, with an area under the curve (AUC) of 0.731 and good calibration. Application of the nomogram in the validation cohort showed acceptable discrimination, with an AUC of 0.710 and good calibration. Decision curve analysis revealed that the nomogram was clinically useful. These findings suggests, to the best of our knowledge, that this may be the first nomogram for individual preoperative prediction of VI in patients with CRC, which may promote preoperative optimization strategies for this selected group of patients.
血管侵犯(VI)是全身复发的重要特征,也是结直肠癌(CRC)辅助治疗应用的指标。术前了解VI对于确定是否需要辅助治疗以及手术切除的充分性至关重要。在本研究中,构建了CRC患者VI的预测列线图。该预测模型由664例符合条件的CRC患者组成,这些患者被分为训练集(n = 468)和验证集(n = 196)。数据收集于2013年8月至2018年4月之间。使用最小绝对收缩和选择算子回归模型建立特征选择模型。采用多变量逻辑回归分析构建预测列线图。通过校准、区分度和临床实用性评估列线图的性能。分化程度、基于CT的N分期(CT N分期)、血红蛋白和肿瘤距肛门的距离(cm)被纳入列线图。该列线图表现出良好的区分度,曲线下面积(AUC)为0.731,校准良好。在验证队列中应用列线图显示出可接受的区分度,AUC为0.710,校准良好。决策曲线分析表明该列线图具有临床实用性。据我们所知,这些发现表明,这可能是首个用于CRC患者术前个体VI预测的列线图,这可能会促进针对这一特定患者群体的术前优化策略。