CT-based radiomics nomogram for the preoperative prediction of microsatellite instability and clinical outcomes in colorectal cancer: a multicentre study

列线图 医学 接收机工作特性 置信区间 逻辑回归 结直肠癌 危险系数 单变量 无线电技术 回顾性队列研究 肿瘤科 内科学 比例危险模型 队列 多元分析 放射科 多元统计 癌症 统计 数学
作者
Ming Li,Gang Xu,Yang Cui,Sheng Wang,H.B. Wang,Xun Xu,Shiwei Duan,Jiong Shi,Feng Feng
出处
期刊:Clinical Radiology [Elsevier BV]
卷期号:78 (10): e741-e751 被引量:5
标识
DOI:10.1016/j.crad.2023.06.012
摘要

To develop and validate a computed tomography (CT)-based radiomics nomogram for preoperative prediction of microsatellite instability (MSI) status and clinical outcomes in colorectal cancer (CRC) patients.This retrospective study enrolled 497 CRC patients from three centres. Least absolute shrinkage and selection operator regression was utilised for feature selection and constructing the radiomics signature. Univariate and multivariate logistic regression analyses were employed to identify significant clinical variables. The radiomics nomogram was constructed by integrating the radiomics signature and the identified clinical variables. The performance of the nomogram was evaluated through receiver operating characteristic curves, calibration curves, and decision curve analysis. Kaplan-Meier analysis was performed to investigate the prognostic value of the nomogram.The radiomics signature comprised 10 radiomics features associated with MSI status. The nomogram, integrating the radiomics signature and independent predictors (age, location, and thickness), demonstrated favourable calibration and discrimination, achieving areas under the receiver operating characteristic (ROC) curves (AUCs) of 0.89 (95% confidence interval [CI]: 0.83-0.95), 0.87 (95% CI: 0.79-0.95), 0.88 (95% CI: 0.81-0.96), and 0.86 (95% CI: 0.78-0.93) in the training cohort, internal validation cohort, and two external validation cohorts, respectively. The nomogram exhibited superior performance compared to the clinical model (p<0.05). Additionally, survival analysis demonstrated that the nomogram successfully stratified stage II CRC patients based on prognosis (hazard ratio [HR]: 0.357, p=0.022).The radiomics nomogram demonstrated promising performance in predicting MSI status and stratifying the prognosis of patients with CRC.
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