Dou Xinyu, Xi Jiaona, Zheng Gaozan, Ren Guangming, Tian Ye, Dan Hanjun, Xie Zhenyu, Niu Liaoran, Duan Lili, Li Ruikai, Wu Hongze, Feng Fan, Zheng Jianyong
Xi'an Medical University, Xi'an, China.
Department of Gastrointestinal Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
J Cancer Res Clin Oncol. 2023 Nov;149(15):14045-14056. doi: 10.1007/s00432-023-05168-1. Epub 2023 Aug 7.
The objective of this study is to examine the risk factors that contribute to the development of liver metastasis (LM) in patients who have suffered radical resection for colorectal cancer (CRC), and to establish a nomogram model that can be used to predict the occurrence of the LM.
The present study enrolled 1377 patients diagnosed with CRC between January 2010 and July 2021. The datasets were allocated to training (n = 965) and validation (n = 412) sets in a randomly stratified manner. The study utilized univariate and multivariate logistic regression analyses to establish a nomogram for predicting LM in patients with CRC.
Multivariate analysis revealed that T stage, N stage, number of harvested lymph nodes (LNH), mismatch repair (MMR) status, neutrophil count, monocyte count, postoperative carcinoembryonic antigen (CEA) levels, postoperative cancer antigen 125 (CA125) levels, and postoperative carbohydrate antigen 19-9 (CA19-9) levels were independent predictive factors for LM after radical resection. These factors were then utilized to construct a comprehensive nomogram for predicting LM. The nomogram demonstrated great discrimination, with an area under the curve (AUC) of 0.782 for the training set and 0.768 for the validation set. Additionally, the nomogram exhibited excellent calibration and significant clinical benefit as confirmed by the calibration curves and the decision curve analysis, respectively.
This nomogram has the potential to support clinicians in identifying high-risk patients who may develop LM post-surgery. Clinicians can devise personalized treatment and follow-up plans, ultimately leading to an improved prognosis for patients.
本研究的目的是探讨接受结直肠癌（CRC）根治性切除的患者发生肝转移（LM）的危险因素，并建立一个可用于预测LM发生的列线图模型。
本研究纳入了2010年1月至2021年7月期间诊断为CRC的1377例患者。数据集以随机分层的方式分配到训练集（n = 965）和验证集（n = 412）。本研究采用单因素和多因素逻辑回归分析来建立预测CRC患者LM的列线图。
多因素分析显示，T分期、N分期、收获的淋巴结数量（LNH）、错配修复（MMR）状态、中性粒细胞计数、单核细胞计数、术后癌胚抗原（CEA）水平、术后癌抗原125（CA125）水平和术后糖类抗原19-9（CA19-9）水平是根治性切除后LM的独立预测因素。然后利用这些因素构建了一个预测LM的综合列线图。该列线图显示出良好的区分度，训练集的曲线下面积（AUC）为0.782，验证集为0.768。此外，校准曲线和决策曲线分析分别证实，该列线图具有良好的校准性和显著的临床效益。
该列线图有可能帮助临床医生识别术后可能发生LM的高危患者。临床医生可以制定个性化的治疗和随访计划，最终改善患者的预后。
