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个性化早发性结直肠癌的预后预测

Personalizing prognostic prediction in early-onset Colorectal Cancer.

作者信息

Liu Jian, Liu Zhengru, Li Jiao, Tian Shan, Dong Weiguo

机构信息

Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, 430060, China.

出版信息

J Cancer. 2020 Sep 25;11(22):6727-6736. doi: 10.7150/jca.46871. eCollection 2020.

Abstract

Accurately estimating prognosis based on clinicopathologic variables could improve risk stratification for patients with early-onset colorectal cancer (EOCRC). Our primary goal was to create and validate a survival nomogram with adequate performance for predicting overall survival (OS) in patients with EOCRC. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to identify clinical features statistically related to OS. Then we established and internally validated a survival nomogram based on surveillance, epidemiology and end results (SEER) database (N=23813). A cohort of 77 patients with EOCRC from Renmin Hospital of Wuhan University (RHWU) was employed to detect the external validity of the survival nomogram. Moreover, we compared the predictive accuracy of survival nomogram with TNM stage, and also compared the OS between endoscopy and surgery groups before and after propensity score matching (PSM) among EOCRC patients with early stage (Tis-T1N0M0). We selected seven informative indexes (N stage, M stage, perineural invasion, chemotherapy, surgery primary site, summary stage and tumor grade) for the construction of the survival nomogram. Then the survival nomogram exhibited good discrimination with C-index of 0.829, 0.841 and 0.796 in the SEER training, SEER validation and RHWU validation sets, respectively. Calibration curves showed good concordance between the survival nomogram predictions and actual outcomes for 1-year, 3-year and 5-year OS. Furthermore, the survival nomogram was superior to risk stratification by TNM stage in predicting OS among patients with EOCRC. Early-stage patients treated with endoscopy showed similar survival to those with surgery before and after PSM. We proposed a survival nomogram based on the extensively used parameters to precisely predict OS in EOCRC patients. This survival nomogram will contribute to aid oncologists better risk stratification and prognostication for patients with EOCRC.

摘要

基于临床病理变量准确估计预后可改善早发性结直肠癌(EOCRC)患者的风险分层。我们的主要目标是创建并验证一个具有良好性能的生存列线图,用于预测EOCRC患者的总生存期(OS)。应用最小绝对收缩和选择算子(LASSO)Cox回归分析来识别与OS有统计学关联的临床特征。然后我们基于监测、流行病学和最终结果(SEER)数据库(N = 23813)建立并进行了内部验证一个生存列线图。采用武汉大学人民医院(RHWU)的77例EOCRC患者队列来检测生存列线图的外部有效性。此外,我们比较了生存列线图与TNM分期的预测准确性,还比较了早期(Tis-T1N0M0)EOCRC患者在倾向得分匹配(PSM)前后内镜组和手术组之间的OS。我们选择了七个信息性指标(N分期、M分期、神经周围侵犯、化疗、手术原发部位、总结分期和肿瘤分级)来构建生存列线图。然后生存列线图在SEER训练集、SEER验证集和RHWU验证集中分别表现出良好的区分度,C指数分别为0.829、0.841和0.796。校准曲线显示生存列线图预测与1年、3年和5年OS的实际结果之间具有良好的一致性。此外,在预测EOCRC患者的OS方面,生存列线图优于TNM分期的风险分层。PSM前后,接受内镜治疗的早期患者与接受手术治疗的患者生存率相似。我们提出了一个基于广泛使用参数的生存列线图,以精确预测EOCRC患者的OS。这个生存列线图将有助于肿瘤学家更好地对EOCRC患者进行风险分层和预后评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0325/7545680/748714277b6f/jcav11p6727g001.jpg

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