The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis

作者：Yinghao Cao, Junnan Gu, Lizhao Yan, Shenghe Deng, Fuwei Mao, Wentai Cai, Hang Li, Xinghua Liu, Jiliang Wang, Ke Wu, Kailin Cai · 发表于：BMC Cancer · 年份：2020 · DOI：10.1186/s12885-020-07551-4 · 被引用次数：8 · 研究领域：Colorectal Cancer Treatments and Studies、HER2/EGFR in Cancer Research、Colorectal Cancer Surgical Treatments

BACKGROUND: Identifying the mutation status of KRAS is important for optimizing treatment in patients with colorectal cancer (CRC). The aim of this study was to investigate the predictive value of haematological parameters and serum tumour markers (STMs) for KRAS gene mutations. METHODS: The clinical data of patients with colorectal cancer from January 2014 to December 2018 were retrospectively collected, and the associations between KRAS mutations and other indicators were analysed. Receiver operating characteristic (ROC) curve analysis was performed to quantify the predictive value of these factors. Univariate and multivariate logistic regression models were applied to identify predictors of KRAS mutations by calculating the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). RESULTS: KRAS mutations were identified in 276 patients (35.2%). ROC analysis revealed that age, CA12-5, AFP, SCC, CA72-4, CA15-3, FERR, CYFRA21-1, MCHC, and tumor location could not predict KRAS mutations (P = 0.154, 0.177, 0.277, 0.350, 0.864, 0.941, 0.066, 0.279, 0.293, and 0.053 respectively), although CEA, CA19-9, NSE and haematological parameter values showed significant predictive value (P = 0.001, < 0.001, 0.043 and P = 0.003, < 0.001, 0.001, 0.031, 0.030, 0.016, 0.015, 0.019, and 0.006, respectively) but without large areas under the curve. Multivariate logistic regression analysis showed that CA19-9 was significantly associated with KRAS mutations and was the only indepe...