Nomograms for Prediction of Molecular Phenotypes in Colorectal Cancer.

Clicks: 251
ID: 94834
2020
Colorectal cancer (CRC) patients with different molecular phenotypes, including microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and somatic mutations in and gene, vary in treatment response and prognosis. However, molecular phenotyping under adequate quality control in a community-based setting may be difficult. We aimed to build the nomograms based on easily accessible clinicopathological characteristics to predict molecular phenotypes.Three hundred and six patients with pathologically confirmed stage I-IV CRC were included in the cohort. The assays for MSI, CIMP, and mutations in and gene were performed using resected tumor samples. The candidate predictors were identified from clinicopathological variables using multivariate Logistic regression analyses to construct the nomograms that could predict each molecular phenotype.The incidences of MSI, CIMP, mutation and mutation were 25.3% (72/285), 2.5% (7/270), 3.4% (10/293), and 34.8% (96/276) respectively. In the multivariate Logistic analysis, poor differentiation and high neutrophil/lymphocyte ratio (NLR) were independently associated with MSI; poor differentiation, high NLR and high carcinoembryonic antigen/tumor size ratio (CSR) were independently associated with CIMP; poor differentiation, lymphovascular invasion and high CSR were independently associated with mutation; poor differentiation, proximal tumor, mucinous tumor and high NLR were independently associated with mutation. Four nomograms for MSI, CIMP, mutation and mutation were developed based on these independent predictors, the C-indexes of which were 61.22% (95% CI: 60.28-62.16%), 95.57% (95% CI: 95.20-95.94%), 83.56% (95% CI: 81.54-85.58%), and 69.12% (95% CI: 68.30-69.94%) respectively.We established four nomograms using easily accessible variables that could well predict the presence of MSI, CIMP, mutation and mutation in CRC patients.
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Authors Yu, Zhuojun;Yu, Huichuan;Zou, Qi;Huang, Zenghong;Wang, Xiaolin;Tang, Guannan;Bai, Liangliang;Zhou, Chuanhai;Zhuang, Zhuokai;Xie, Yumo;Wang, Heng;Xu, Gaopo;Chen, Zijian;Fu, Xinhui;Huang, Meijin;Luo, Yanxin;
Journal OncoTargets and therapy
Year 2020
DOI 10.2147/OTT.S234495
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