Department of Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Int J Colorectal Dis. 2023 Apr 17;38(1):99. doi: 10.1007/s00384-023-04369-x.
Metastatic early-onset colorectal cancer (EO-CRC) is on the rise, yet there is a dearth of predictive models for this disease. Therefore, it is crucial to develop a nomogram to aid in the early detection and management of metastatic colorectal cancer in young patients.
We retrieved data from the SEER database on patients with metastatic colorectal cancer aged 50 or younger between 2010 and 2017. The data were randomly allocated in a 7:3 ratio to training and validation cohorts, and univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS) at 1, 3, and 5 years. The nomograms were developed based on these factors, and their discriminatory and calibration capabilities were validated. Using the nomogram risk scores, patients were stratified into low-risk and high-risk groups.
The study included 2470 patients with metastatic EO-CRC. Univariate and multivariate Cox regression analysis identified 12 independent risk factors that were included in the nomogram. The training cohort had a consistency index (C-index) of 0.71, while the validation cohort had a C-index of 0.70, demonstrating good predictive accuracy. Calibration plots showed a high level of consistency between the observed and predicted values, with overlapping plots along the diagonal. The decision curve analysis (DCA) revealed that the nomogram had a high clinical application value.
The novel nomograms were created to predict the prognosis of patients with metastatic EO-CRC, which can aid clinicians in developing more effective treatment strategies and contribute to more accurate prognostic assessments.
早期转移性结直肠癌（EO-CRC）的发病率正在上升，但针对这种疾病的预测模型却很少。因此，开发一种列线图来帮助早期发现和管理年轻患者的转移性结直肠癌至关重要。
我们从 SEER 数据库中检索了 2010 年至 2017 年间年龄在 50 岁或以下的转移性结直肠癌患者的数据。将数据随机分为 7:3 的训练和验证队列，并进行单因素和多因素 Cox 回归分析，以确定总生存（OS）和癌症特异性生存（CSS）的独立预后因素，分别在 1、3 和 5 年。根据这些因素开发了列线图，并验证了其区分度和校准能力。使用列线图风险评分，将患者分为低风险和高风险组。
该研究纳入了 2470 例转移性 EO-CRC 患者。单因素和多因素 Cox 回归分析确定了 12 个独立的风险因素，这些因素被纳入了列线图。训练队列的一致性指数（C-index）为 0.71，验证队列的 C-index 为 0.70，表明预测准确性良好。校准图显示观察值和预测值之间具有高度一致性，对角线沿线存在重叠图。决策曲线分析（DCA）显示该列线图具有较高的临床应用价值。
本研究构建了预测转移性 EO-CRC 患者预后的新型列线图，有助于临床医生制定更有效的治疗策略，并有助于更准确的预后评估。
