State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China.
Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People's Republic of China.
Cancer Med. 2021 Mar;10(5):1535-1544. doi: 10.1002/cam4.3697. Epub 2021 Feb 4.
We aimed to construct a nomogram to predict personalized post-recurrence survival (PRS) among colorectal cancer liver metastasis (CRLM) patients with post-hepatectomy recurrence.
Colorectal cancer liver metastasis patients who received initial hepatectomy and had subsequent recurrence between 2001 and 2019 in Sun Yat-sen University Cancer Center from China were included in the study. Patients were randomly assigned to a training cohort and a validation cohort on a ratio of 2:1. Univariable analysis was first employed to select potential predictive factors for PRS. Then, the multivariable Cox regression model was applied to recognize independent prognostic factors. According to the model, a nomogram to predict PRS was established. The nomogram's predictive capacity was further assessed utilizing concordance index (C-index) values, calibration plots, and Kaplan-Meier curves.
About 376 patients were finally enrolled, with a 3-year PRS rate of 37.3% and a 5-year PRS rate of 24.6%. The following five independent predictors for PRS were determined to construct the nomogram: the largest size of liver metastases at initial hepatectomy, relapse-free survival, CEA level at recurrence, recurrent sites, and treatment for recurrence. The nomogram displayed fairly good discrimination and calibration. The C-index value was 0.742 for the training cohort and 0.773 for the validation cohort. Patients were grouped into three risk groups very well by the nomogram, with 5-year PRS rates of 45.2%, 23.3%, and 9.0%, respectively (p < 0.001) in the training cohort and 36.0%, 9.2%, and 4.6%, respectively (p < 0.001) in the validation cohort.
A novel nomogram was built and validated to enable the prediction of personal PRS in CRLM patients with post-hepatectomy recurrence. The nomogram may help physicians in decision making.
我们旨在构建一个列线图,以预测接受初始肝切除术后发生肝转移(CRLM)复发的结直肠癌患者的个体化复发后生存(PRS)。
本研究纳入了 2001 年至 2019 年在中国中山大学肿瘤防治中心接受初始肝切除术且随后复发的结直肠癌肝转移患者。患者按 2:1 的比例随机分配到训练队列和验证队列。首先采用单变量分析筛选与 PRS 相关的潜在预测因素。然后,应用多变量 Cox 回归模型识别独立的预后因素。根据该模型,建立了一个预测 PRS 的列线图。进一步通过一致性指数(C-index)值、校准图和 Kaplan-Meier 曲线评估列线图的预测能力。
最终共纳入 376 例患者,3 年 PRS 率为 37.3%,5 年 PRS 率为 24.6%。确定了 5 个独立的 PRS 预测因素来构建列线图:初始肝切除时肝转移的最大直径、无复发生存、复发时 CEA 水平、复发部位和复发后的治疗。该列线图具有较好的区分度和校准度。训练队列的 C-index 值为 0.742,验证队列的 C-index 值为 0.773。该列线图可将患者很好地分为 3 个风险组,在训练队列中,5 年 PRS 率分别为 45.2%、23.3%和 9.0%(p<0.001),在验证队列中,5 年 PRS 率分别为 36.0%、9.2%和 4.6%(p<0.001)。
构建并验证了一种新的列线图,以预测接受初始肝切除术后复发的 CRLM 患者的个体化 PRS。该列线图可能有助于医生做出决策。