Radiomic signature-based nomogram to predict disease-free survival in stage II and III colon cancer

列线图 医学 结直肠癌 无线电技术 逻辑回归 队列 内科学 肿瘤科 放射科 阶段(地层学) 癌症 T级 回顾性队列研究 生物 古生物学
作者
Xun Yao,Caixia Sun,Fei Xiong,Xinyu Zhang,Cheng Jin,Chao Wang,Yingjiang Ye,Nan Hong,Lihui Wang,Zhenyu Liu,Xiaochun Meng,Yi Wang,Jie Tian
出处
期刊:European Journal of Radiology [Elsevier BV]
卷期号:131: 109205-109205 被引量:13
标识
DOI:10.1016/j.ejrad.2020.109205
摘要

Abstract

Purpose

To develop a radiomic nomogram to predict disease-free survival (DFS) in patients with colon cancer.

Methods

We retrospectively identified 302 patients with stage III colon cancer and 269 patients with stage II colon cancer who had undergone multidetector computed tomography (MDCT) and radical resection between January 2009 and December 2015. Patients were divided into a training cohort (n = 322) and an external validation cohort (n = 249). Radiomic features were extracted from MDCT images, and a radiomic signature was built as to predict DFS. A radiomic nomogram integrating the radiomic signature and clinicopathologic characteristics was developed using multivariable logistic regression. The nomogram was evaluated with regard to calibration, discrimination, and clinical utility.

Results

The radiomic signature was an independent prognostic factor for DFS in the training cohort (HR = 1.102; 95 % CI: 1.052–1.156; P < 0.001) and the external validation cohort (HR = 1.157; 95 % CI: 1.030–1.301; P = 0.014). The radiomic signature-based nomogram was more effective at predicting DFS than either the TNM staging system or a clinicopathologic nomogram. The C-indices of the radiomic nomogram and TNM staging system were 0.780 (95 % CI: 0.734–0.847) and 0.738 (0.687−0.784) respectively. The radiomic signature-based nomogram demonstrated good fitness (shown by calibration curves) and clinical usefulness (shown by decision curve analysis).

Conclusion

A radiomic signature derived from MDCT images can effectively predict DFS in patients with stage II and III colon cancer and could be used as a supplement for risk stratification.
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