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

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 clinica...

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Autores principales: Cao, Yinghao, Gu, Junnan, Yan, Lizhao, Deng, Shenghe, Mao, Fuwei, Cai, Wentai, Li, Hang, Liu, Xinghua, Wang, Jiliang, Wu, Ke, Cai, Kailin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659200/
https://www.ncbi.nlm.nih.gov/pubmed/33183271
http://dx.doi.org/10.1186/s12885-020-07551-4
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author Cao, Yinghao
Gu, Junnan
Yan, Lizhao
Deng, Shenghe
Mao, Fuwei
Cai, Wentai
Li, Hang
Liu, Xinghua
Wang, Jiliang
Wu, Ke
Cai, Kailin
author_facet Cao, Yinghao
Gu, Junnan
Yan, Lizhao
Deng, Shenghe
Mao, Fuwei
Cai, Wentai
Li, Hang
Liu, Xinghua
Wang, Jiliang
Wu, Ke
Cai, Kailin
author_sort Cao, Yinghao
collection PubMed
description 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 independent predictor of KRAS positivity (P = 0.016). CONCLUSIONS: Haematological parameters and STMs were related to KRAS mutation status, and CA19–9 was an independent predictive factor for KRAS gene mutations. The combination of these clinical factors can improve the ability to identify KRAS mutations in CRC patients.
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spelling pubmed-76592002020-11-13 The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis Cao, Yinghao Gu, Junnan Yan, Lizhao Deng, Shenghe Mao, Fuwei Cai, Wentai Li, Hang Liu, Xinghua Wang, Jiliang Wu, Ke Cai, Kailin BMC Cancer Research Article 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 independent predictor of KRAS positivity (P = 0.016). CONCLUSIONS: Haematological parameters and STMs were related to KRAS mutation status, and CA19–9 was an independent predictive factor for KRAS gene mutations. The combination of these clinical factors can improve the ability to identify KRAS mutations in CRC patients. BioMed Central 2020-11-12 /pmc/articles/PMC7659200/ /pubmed/33183271 http://dx.doi.org/10.1186/s12885-020-07551-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Cao, Yinghao
Gu, Junnan
Yan, Lizhao
Deng, Shenghe
Mao, Fuwei
Cai, Wentai
Li, Hang
Liu, Xinghua
Wang, Jiliang
Wu, Ke
Cai, Kailin
The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis
title The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis
title_full The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis
title_fullStr The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis
title_full_unstemmed The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis
title_short The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis
title_sort value of haematological parameters and serum tumour markers for predicting kras mutations in 784 chinese colorectal cancer patients: a retrospective analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659200/
https://www.ncbi.nlm.nih.gov/pubmed/33183271
http://dx.doi.org/10.1186/s12885-020-07551-4
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