Department of Anaesthesia, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Int J Colorectal Dis. 2024 Apr 3;39(1):46. doi: 10.1007/s00384-024-04621-y.
Lymph node metastasis (LNM) is a crucial factor that determines the prognosis of T1 colorectal cancer (CRC) patients. We aimed to develop a practical prediction model for LNM in T1 CRC.
We conducted a retrospective analysis of data from 825 patients with T1 CRC who underwent radical resection at a single center in China. All enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3 using R software. Risk factors for LNM were identified through multivariate logistic regression analyses. Subsequently, a prediction model was developed using the selected variables.
The lymph node metastasis (LNM) rate was 10.1% in the training cohort and 9.3% in the validation cohort. In the training set, risk factors for LNM in T1 CRC were identified, including depressed endoscopic gross appearance, sex, submucosal invasion combined with tumor grade (DSI-TG), lymphovascular invasion (LVI), and tumor budding. LVI emerged as the most potent predictor for LNM. The prediction model based on these factors exhibited good discrimination ability in the validation sets (AUC: 79.3%). Compared to current guidelines, the model could potentially reduce over-surgery by 48.9%. Interestingly, we observed that sex had a differential impact on LNM between early-onset and late-onset CRC patients.
We developed a clinical prediction model for LNM in T1 CRC using five factors that are easily accessible in clinical practice. The model has better predictive performance and practicality than the current guidelines and can assist clinicians in making treatment decisions for T1 CRC patients.
淋巴结转移（LNM）是决定 T1 结直肠癌（CRC）患者预后的关键因素。我们旨在为 T1 CRC 患者建立 LNM 的实用预测模型。
我们对在中国一家中心接受根治性切除术的 825 例 T1 CRC 患者的数据进行了回顾性分析。所有入组患者均使用 R 软件按 7:3 的比例随机分为训练集和验证集。通过多变量逻辑回归分析确定 LNM 的危险因素。随后，使用选定的变量开发预测模型。
训练队列和验证队列的 LNM 率分别为 10.1%和 9.3%。在训练集中，确定了 T1 CRC 发生 LNM 的危险因素，包括内镜下大体外观凹陷、性别、黏膜下浸润合并肿瘤分级（DSI-TG）、淋巴血管侵犯（LVI）和肿瘤芽。LVI 是 LNM 的最强预测因子。基于这些因素的预测模型在验证集中具有良好的判别能力（AUC：79.3%）。与当前指南相比，该模型可潜在减少 48.9%的过度手术。有趣的是，我们观察到性别对早发性和晚发性 CRC 患者的 LNM 有不同的影响。
我们使用五种在临床实践中易于获得的因素为 T1 CRC 患者建立了 LNM 的临床预测模型。该模型具有比当前指南更好的预测性能和实用性，可帮助临床医生为 T1 CRC 患者做出治疗决策。
