The Second General Surgery, The Fourth Hospital of Hebei Medical University, NO.12, JianKang Road, Shijiazhuang, Hebei Province, PR China.
The Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, NO.139, Ziqiang Road, Shijiazhuang, Hebei Province, PR China.
BMC Surg. 2023 Jun 29;23(1):182. doi: 10.1186/s12893-023-02018-2.
Colorectal cancer (CRC) is a frequent cancer worldwide with varied survival outcomes.
We aimed to develop a nomogram model to predict the overall survival (OS) of CRC patients after surgery.
This is a retrospective study.
This study was conducted from 2015 to 2016 in a single tertiary center for CRC.
CRC patients who underwent surgery between 2015 and 2016 were enrolled and randomly assigned into the training (n = 480) and validation (n = 206) groups. The risk score of each subject was calculated based on the nomogram. All participants were categorized into two subgroups according to the median value of the score.
The clinical characteristics of all patients were collected, significant prognostic variables were determined by univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression was applied for variable selection. The tuning parameter (λ) for LASSO regression was determined by cross-validation. Independent prognostic variables determined by multivariable analysis were used to establish the nomogram. The predictive capacity of the model was assessed by risk group stratification.
Infiltration depth, macroscopic classification, BRAF, carbohydrate antigen 19 - 9 (CA-199) levels, N stage, M stage, TNM stage, carcinoembryonic antigen levels, number of positive lymph nodes, vascular tumor thrombus, and lymph node metastasis were independent prognostic factors. The nomogram established based on these factors exhibited good discriminatory capacity. The concordance indices for the training and validation groups were 0.796 and 0.786, respectively. The calibration curve suggested favorable agreement between predictions and observations. Moreover, the OS of different risk subgroups was significantly different.
The limitations of this work included small sample size and single-center design. Also, some prognostic factors could not be included due to the retrospective design.
A prognostic nomogram for predicting the OS of CRC patients after surgery was developed, which might be helpful for evaluating the prognosis of CRC patients.
结直肠癌（CRC）是一种全球范围内常见的癌症，其生存结果存在差异。
旨在建立预测 CRC 患者手术后总体生存（OS）的列线图模型。
这是一项回顾性研究。
这项研究于 2015 年至 2016 年在一家 CRC 三级中心进行。
纳入 2015 年至 2016 年接受手术的 CRC 患者，并将其随机分配到训练组（n=480）和验证组（n=206）。根据列线图计算每位受试者的风险评分。根据评分的中位数将所有参与者分为两个亚组。
收集所有患者的临床特征，通过单因素分析确定显著预后变量。应用最小绝对收缩和选择算子（LASSO）回归进行变量选择。通过交叉验证确定 LASSO 回归的调整参数（λ）。多变量分析确定的独立预后变量用于建立列线图。通过风险分组评估模型的预测能力。
浸润深度、大体分类、BRAF、癌胚抗原 19-9（CA-199）水平、N 分期、M 分期、TNM 分期、癌胚抗原水平、阳性淋巴结数量、血管肿瘤血栓和淋巴结转移是独立的预后因素。基于这些因素建立的列线图具有良好的区分能力。训练组和验证组的一致性指数分别为 0.796 和 0.786。校准曲线表明预测值与观察值之间具有良好的一致性。此外，不同风险亚组的 OS 存在显著差异。
本研究的局限性包括样本量小和单中心设计。此外，由于回顾性设计，一些预后因素无法纳入。
建立了预测 CRC 患者手术后 OS 的预后列线图，可能有助于评估 CRC 患者的预后。
