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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
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. The clinical data of patients wi...
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| Published in: | BMC cancer 2020-11, Vol.20 (1), p.1099-1099, Article 1099 |
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| description | 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.
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).
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, |
| doi_str_mv | 10.1186/s12885-020-07551-4 |
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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).
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).
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.</description><identifier>ISSN: 1471-2407</identifier><identifier>EISSN: 1471-2407</identifier><identifier>DOI: 10.1186/s12885-020-07551-4</identifier><identifier>PMID: 33183271</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Asian Continental Ancestry Group - genetics ; Biomarkers ; Biomarkers, Tumor - blood ; Biomarkers, Tumor - genetics ; Biopsy ; Cancer ; Cancer therapies ; Care and treatment ; Colorectal cancer ; Colorectal carcinoma ; Colorectal Neoplasms - blood ; Colorectal Neoplasms - genetics ; Colorectal Neoplasms - pathology ; Development and progression ; Female ; Females ; Follow-Up Studies ; Gene expression ; Gene mutation ; Genetic aspects ; Haematological parameters ; Health aspects ; Hematocrit ; Hematology ; Humans ; K-Ras protein ; KRAS mutation ; Male ; Medical prognosis ; Metastasis ; Middle Aged ; Monoclonal antibodies ; Mortality ; Mutation ; Patients ; Predictive Value of Tests ; Proto-Oncogene Proteins p21(ras) - genetics ; Regression analysis ; Retrospective Studies ; ROC Curve ; Serum tumour markers ; Tumors</subject><ispartof>BMC cancer, 2020-11, Vol.20 (1), p.1099-1099, Article 1099</ispartof><rights>COPYRIGHT 2020 BioMed Central Ltd.</rights><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c628t-b945a0fefc7758e0e7ed925861d7a67e444f6cc34847e8edf2fa02eb0de7c3f23</citedby><cites>FETCH-LOGICAL-c628t-b945a0fefc7758e0e7ed925861d7a67e444f6cc34847e8edf2fa02eb0de7c3f23</cites><orcidid>0000-0002-2572-0907</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7659200/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2462185399?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33183271$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cao, Yinghao</creatorcontrib><creatorcontrib>Gu, Junnan</creatorcontrib><creatorcontrib>Yan, Lizhao</creatorcontrib><creatorcontrib>Deng, Shenghe</creatorcontrib><creatorcontrib>Mao, Fuwei</creatorcontrib><creatorcontrib>Cai, Wentai</creatorcontrib><creatorcontrib>Li, Hang</creatorcontrib><creatorcontrib>Liu, Xinghua</creatorcontrib><creatorcontrib>Wang, Jiliang</creatorcontrib><creatorcontrib>Wu, Ke</creatorcontrib><creatorcontrib>Cai, Kailin</creatorcontrib><title>The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis</title><title>BMC cancer</title><addtitle>BMC Cancer</addtitle><description>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.
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).
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).
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.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Asian Continental Ancestry Group - genetics</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - blood</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biopsy</subject><subject>Cancer</subject><subject>Cancer therapies</subject><subject>Care and treatment</subject><subject>Colorectal cancer</subject><subject>Colorectal carcinoma</subject><subject>Colorectal Neoplasms - blood</subject><subject>Colorectal Neoplasms - genetics</subject><subject>Colorectal Neoplasms - pathology</subject><subject>Development and progression</subject><subject>Female</subject><subject>Females</subject><subject>Follow-Up Studies</subject><subject>Gene expression</subject><subject>Gene mutation</subject><subject>Genetic aspects</subject><subject>Haematological parameters</subject><subject>Health aspects</subject><subject>Hematocrit</subject><subject>Hematology</subject><subject>Humans</subject><subject>K-Ras protein</subject><subject>KRAS mutation</subject><subject>Male</subject><subject>Medical prognosis</subject><subject>Metastasis</subject><subject>Middle Aged</subject><subject>Monoclonal antibodies</subject><subject>Mortality</subject><subject>Mutation</subject><subject>Patients</subject><subject>Predictive Value of Tests</subject><subject>Proto-Oncogene Proteins p21(ras) - genetics</subject><subject>Regression analysis</subject><subject>Retrospective Studies</subject><subject>ROC Curve</subject><subject>Serum tumour markers</subject><subject>Tumors</subject><issn>1471-2407</issn><issn>1471-2407</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptkt9qFDEUxgdRbK2-gBcSEEQvpiaZTJL1QijFP8WC0NbrcDZzsps6M1mTzGIfxzc13a11VyQXCTm_7wvn5Kuq54weM6bl28S41m1NOa2paltWiwfVIROK1VxQ9XDnfFA9SemaUqY01Y-rg6ZhuuGKHVa_rpZI1tBPSIIjS8ABcujDwlvoyQoiDJgxJgJjRxLGaSB5GsIUyQDx-23BhUhWETtvsx8X5MvFySUZpgzZhzERPxKlBTld-hETElusI9pcvC2MFou0gDjm9I4AiZhjSKtS92ssL0J_k3x6Wj1y0Cd8drcfVd8-frg6_Vyff_10dnpyXlvJda7nM9ECdeisUq1Gigq7GW-1ZJ0CqVAI4aS1jdBCocbOcQeU45x2qGzjeHNUnW19uwDXZhV96fDGBPBmcxHiwkDM3vZoqKaSWyqko53ohNDMUdvOZ5Jp3tAWitf7rddqmg_Y2dJhhH7PdL8y-qVZhLVRsp1xSovB6zuDGH5MmLIZfLLY9zBimJLhQlIlJae6oC__Qa_L_5ThbSjOdNvMZn-pBZQG_OhCedfempoTKTjXjVaqUMf_ocrqcPA2jOh8ud8TvNkTFCbjz7yAKSVzdnmxz77aYZcIfV6m0E-bpOyDfAvaEocU0d0PjlFzm3yzTb4pyTeb5BtRRC92R34v-RP15jdDrv6Q</recordid><startdate>20201112</startdate><enddate>20201112</enddate><creator>Cao, Yinghao</creator><creator>Gu, Junnan</creator><creator>Yan, Lizhao</creator><creator>Deng, Shenghe</creator><creator>Mao, Fuwei</creator><creator>Cai, Wentai</creator><creator>Li, Hang</creator><creator>Liu, Xinghua</creator><creator>Wang, Jiliang</creator><creator>Wu, Ke</creator><creator>Cai, Kailin</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>3V.</scope><scope>7TO</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-2572-0907</orcidid></search><sort><creationdate>20201112</creationdate><title>The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis</title><author>Cao, Yinghao ; Gu, Junnan ; Yan, Lizhao ; Deng, Shenghe ; Mao, Fuwei ; Cai, Wentai ; Li, Hang ; Liu, Xinghua ; Wang, Jiliang ; Wu, Ke ; Cai, Kailin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c628t-b945a0fefc7758e0e7ed925861d7a67e444f6cc34847e8edf2fa02eb0de7c3f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Asian Continental Ancestry Group - genetics</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - blood</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biopsy</topic><topic>Cancer</topic><topic>Cancer therapies</topic><topic>Care and treatment</topic><topic>Colorectal cancer</topic><topic>Colorectal carcinoma</topic><topic>Colorectal Neoplasms - blood</topic><topic>Colorectal Neoplasms - genetics</topic><topic>Colorectal Neoplasms - pathology</topic><topic>Development and progression</topic><topic>Female</topic><topic>Females</topic><topic>Follow-Up Studies</topic><topic>Gene expression</topic><topic>Gene mutation</topic><topic>Genetic aspects</topic><topic>Haematological parameters</topic><topic>Health aspects</topic><topic>Hematocrit</topic><topic>Hematology</topic><topic>Humans</topic><topic>K-Ras protein</topic><topic>KRAS mutation</topic><topic>Male</topic><topic>Medical prognosis</topic><topic>Metastasis</topic><topic>Middle Aged</topic><topic>Monoclonal antibodies</topic><topic>Mortality</topic><topic>Mutation</topic><topic>Patients</topic><topic>Predictive Value of Tests</topic><topic>Proto-Oncogene Proteins p21(ras) - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Yinghao</au><au>Gu, Junnan</au><au>Yan, Lizhao</au><au>Deng, Shenghe</au><au>Mao, Fuwei</au><au>Cai, Wentai</au><au>Li, Hang</au><au>Liu, Xinghua</au><au>Wang, Jiliang</au><au>Wu, Ke</au><au>Cai, Kailin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis</atitle><jtitle>BMC cancer</jtitle><addtitle>BMC Cancer</addtitle><date>2020-11-12</date><risdate>2020</risdate><volume>20</volume><issue>1</issue><spage>1099</spage><epage>1099</epage><pages>1099-1099</pages><artnum>1099</artnum><issn>1471-2407</issn><eissn>1471-2407</eissn><abstract>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.
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).
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).
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.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>33183271</pmid><doi>10.1186/s12885-020-07551-4</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-2572-0907</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Aged Aged, 80 and over Asian Continental Ancestry Group - genetics Biomarkers Biomarkers, Tumor - blood Biomarkers, Tumor - genetics Biopsy Cancer Cancer therapies Care and treatment Colorectal cancer Colorectal carcinoma Colorectal Neoplasms - blood Colorectal Neoplasms - genetics Colorectal Neoplasms - pathology Development and progression Female Females Follow-Up Studies Gene expression Gene mutation Genetic aspects Haematological parameters Health aspects Hematocrit Hematology Humans K-Ras protein KRAS mutation Male Medical prognosis Metastasis Middle Aged Monoclonal antibodies Mortality Mutation Patients Predictive Value of Tests Proto-Oncogene Proteins p21(ras) - genetics Regression analysis Retrospective Studies ROC Curve Serum tumour markers Tumors |
| title | The value of haematological parameters and serum tumour markers for predicting KRAS mutations in 784 Chinese colorectal cancer patients: a retrospective analysis |
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