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A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma
Background and Aim The existed staging systems were limited in the accuracy of prediction for overall survival (OS) of hepatocellular carcinoma (HCC) patients. The aim of this study is to establish a novel inflammation‐based prognostic system with nomogram for HCC patients. Methods A prospective coh...
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| Published in: | Cancer medicine (Malden, MA) MA), 2018-10, Vol.7 (10), p.5027-5035 |
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| creator | Chen, Jinbin Fang, Aiping Chen, Minshan Tuoheti, Yiminjiang Zhou, Zhongguo Xu, Li Chen, Jiancong Pan, Yangxun Wang, Juncheng Zhu, Huilian Zhang, Yaojun |
| description | Background and Aim
The existed staging systems were limited in the accuracy of prediction for overall survival (OS) of hepatocellular carcinoma (HCC) patients. The aim of this study is to establish a novel inflammation‐based prognostic system with nomogram for HCC patients.
Methods
A prospective cohort of patients was recruited and assigned to the training cohort (n = 659) and validation cohort (n = 320) randomly. Different inflammation‐based score systems were evaluated to select the best one predicting overall survival (OS). The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C‐index) and calibration curve and compared with conventional staging systems.
Results
With a highest C‐index and areas under the receiver operating characteristic curve (AUC), C‐reactive protein/albumin ratio (CAR) was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion and extra‐hepatic metastases. The C‐index of the nomogram was 0.813 (95% CI, 0.789‐0.837) in the training cohort and 0.794 (95% CI, 0.756‐0.832) in the validation cohort. The calibration curve for predicting probability of survival showed that the nomogram had a high consistency with follow‐up data. The C‐index of the novel system was higher than other conventional staging systems (P |
| doi_str_mv | 10.1002/cam4.1787 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6198220</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2113263579</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4437-d6381d61bf9a5cf1bc88f7983d563f52280b6cd98279f9f642ccb1a9fa9dfa3f3</originalsourceid><addsrcrecordid>eNp1kc9uEzEQhy0EolXpgRdAlrjAIa3_7NreC1IUUUAq4gJna9ZrN47sdbB3U-XGI_CMfRIcUqqChC_2aD5_mtEPoZeUXFBC2KWB2FxQqeQTdMpI0y6k4M3TR-8TdF7KhtQjCROSPkcnnLC2E0qdos0Sj2lnA_ajCxAjTD6Ndz9-9lDsUFsx3WSIuOzLZCOeEt5mO3gz4TLnnd9BwMnhbf1lx6ngWz-t8drWOhkbwhwgYwPZ-CqCF-iZg1Ds-f19hr5dvf-6-ri4_vLh02p5vTBNw-ViEFzRQdDeddAaR3ujlJOd4kMruGsZU6QXZugUk53rnGiYMT2FzkE3OOCOn6F3R-927qMdTJ0sQ9Db7CPkvU7g9d-d0a_1TdppQauUkSp4cy_I6ftsy6SjL4d9YLRpLppRypngrewq-vofdJPmPNb1KsUa0gohZaXeHimTUynZuodhKNGHEPUhRH0IsbKvHk__QP6JrAKXR-DWB7v_v0mvlp-b38pf0e6p1w</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2124056677</pqid></control><display><type>article</type><title>A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma</title><source>Open Access: PubMed Central</source><source>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</source><source>Wiley Open Access</source><creator>Chen, Jinbin ; Fang, Aiping ; Chen, Minshan ; Tuoheti, Yiminjiang ; Zhou, Zhongguo ; Xu, Li ; Chen, Jiancong ; Pan, Yangxun ; Wang, Juncheng ; Zhu, Huilian ; Zhang, Yaojun</creator><creatorcontrib>Chen, Jinbin ; Fang, Aiping ; Chen, Minshan ; Tuoheti, Yiminjiang ; Zhou, Zhongguo ; Xu, Li ; Chen, Jiancong ; Pan, Yangxun ; Wang, Juncheng ; Zhu, Huilian ; Zhang, Yaojun</creatorcontrib><description>Background and Aim
The existed staging systems were limited in the accuracy of prediction for overall survival (OS) of hepatocellular carcinoma (HCC) patients. The aim of this study is to establish a novel inflammation‐based prognostic system with nomogram for HCC patients.
Methods
A prospective cohort of patients was recruited and assigned to the training cohort (n = 659) and validation cohort (n = 320) randomly. Different inflammation‐based score systems were evaluated to select the best one predicting overall survival (OS). The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C‐index) and calibration curve and compared with conventional staging systems.
Results
With a highest C‐index and areas under the receiver operating characteristic curve (AUC), C‐reactive protein/albumin ratio (CAR) was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion and extra‐hepatic metastases. The C‐index of the nomogram was 0.813 (95% CI, 0.789‐0.837) in the training cohort and 0.794 (95% CI, 0.756‐0.832) in the validation cohort. The calibration curve for predicting probability of survival showed that the nomogram had a high consistency with follow‐up data. The C‐index of the novel system was higher than other conventional staging systems (P < 0.001).
Conclusions
The novel inflammation‐based nomogram, developed from prospectively collected data in the present study, predicted the OS of HCC patients.
The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. C‐reactive protein albumin ratio was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion, and extra‐hepatic metastases. The novel inflammation‐based nomogram, developed from prospectively collected data, predicted the overall survival of hepatocellular carcinoma patients.</description><identifier>ISSN: 2045-7634</identifier><identifier>EISSN: 2045-7634</identifier><identifier>DOI: 10.1002/cam4.1787</identifier><identifier>PMID: 30259688</identifier><language>eng</language><publisher>United States: John Wiley & Sons, Inc</publisher><subject>Albumins - metabolism ; Biomarkers, Tumor - immunology ; C-Reactive Protein - metabolism ; Carcinoma, Hepatocellular - immunology ; Carcinoma, Hepatocellular - pathology ; Clinical Cancer Research ; Female ; Hepatocellular carcinoma ; Humans ; Inflammation ; inflammation‐based score system ; Liver cancer ; Liver Neoplasms - immunology ; Liver Neoplasms - pathology ; Male ; Metastases ; Multivariate analysis ; nomogram ; Nomograms ; Original Research ; Prognosis ; prognostic value ; Prospective Studies ; Random Allocation ; Survival ; Tumor Burden</subject><ispartof>Cancer medicine (Malden, MA), 2018-10, Vol.7 (10), p.5027-5035</ispartof><rights>2018 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.</rights><rights>2018. This work is published 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><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4437-d6381d61bf9a5cf1bc88f7983d563f52280b6cd98279f9f642ccb1a9fa9dfa3f3</citedby><cites>FETCH-LOGICAL-c4437-d6381d61bf9a5cf1bc88f7983d563f52280b6cd98279f9f642ccb1a9fa9dfa3f3</cites><orcidid>0000-0002-6619-1247 ; 0000-0002-1929-4278 ; 0000-0002-9752-4729</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2124056677/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2124056677?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,11562,25753,27924,27925,37012,37013,44590,46052,46476,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30259688$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Jinbin</creatorcontrib><creatorcontrib>Fang, Aiping</creatorcontrib><creatorcontrib>Chen, Minshan</creatorcontrib><creatorcontrib>Tuoheti, Yiminjiang</creatorcontrib><creatorcontrib>Zhou, Zhongguo</creatorcontrib><creatorcontrib>Xu, Li</creatorcontrib><creatorcontrib>Chen, Jiancong</creatorcontrib><creatorcontrib>Pan, Yangxun</creatorcontrib><creatorcontrib>Wang, Juncheng</creatorcontrib><creatorcontrib>Zhu, Huilian</creatorcontrib><creatorcontrib>Zhang, Yaojun</creatorcontrib><title>A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma</title><title>Cancer medicine (Malden, MA)</title><addtitle>Cancer Med</addtitle><description>Background and Aim
The existed staging systems were limited in the accuracy of prediction for overall survival (OS) of hepatocellular carcinoma (HCC) patients. The aim of this study is to establish a novel inflammation‐based prognostic system with nomogram for HCC patients.
Methods
A prospective cohort of patients was recruited and assigned to the training cohort (n = 659) and validation cohort (n = 320) randomly. Different inflammation‐based score systems were evaluated to select the best one predicting overall survival (OS). The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C‐index) and calibration curve and compared with conventional staging systems.
Results
With a highest C‐index and areas under the receiver operating characteristic curve (AUC), C‐reactive protein/albumin ratio (CAR) was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion and extra‐hepatic metastases. The C‐index of the nomogram was 0.813 (95% CI, 0.789‐0.837) in the training cohort and 0.794 (95% CI, 0.756‐0.832) in the validation cohort. The calibration curve for predicting probability of survival showed that the nomogram had a high consistency with follow‐up data. The C‐index of the novel system was higher than other conventional staging systems (P < 0.001).
Conclusions
The novel inflammation‐based nomogram, developed from prospectively collected data in the present study, predicted the OS of HCC patients.
The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. C‐reactive protein albumin ratio was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion, and extra‐hepatic metastases. The novel inflammation‐based nomogram, developed from prospectively collected data, predicted the overall survival of hepatocellular carcinoma patients.</description><subject>Albumins - metabolism</subject><subject>Biomarkers, Tumor - immunology</subject><subject>C-Reactive Protein - metabolism</subject><subject>Carcinoma, Hepatocellular - immunology</subject><subject>Carcinoma, Hepatocellular - pathology</subject><subject>Clinical Cancer Research</subject><subject>Female</subject><subject>Hepatocellular carcinoma</subject><subject>Humans</subject><subject>Inflammation</subject><subject>inflammation‐based score system</subject><subject>Liver cancer</subject><subject>Liver Neoplasms - immunology</subject><subject>Liver Neoplasms - pathology</subject><subject>Male</subject><subject>Metastases</subject><subject>Multivariate analysis</subject><subject>nomogram</subject><subject>Nomograms</subject><subject>Original Research</subject><subject>Prognosis</subject><subject>prognostic value</subject><subject>Prospective Studies</subject><subject>Random Allocation</subject><subject>Survival</subject><subject>Tumor Burden</subject><issn>2045-7634</issn><issn>2045-7634</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>PIMPY</sourceid><recordid>eNp1kc9uEzEQhy0EolXpgRdAlrjAIa3_7NreC1IUUUAq4gJna9ZrN47sdbB3U-XGI_CMfRIcUqqChC_2aD5_mtEPoZeUXFBC2KWB2FxQqeQTdMpI0y6k4M3TR-8TdF7KhtQjCROSPkcnnLC2E0qdos0Sj2lnA_ajCxAjTD6Ndz9-9lDsUFsx3WSIuOzLZCOeEt5mO3gz4TLnnd9BwMnhbf1lx6ngWz-t8drWOhkbwhwgYwPZ-CqCF-iZg1Ds-f19hr5dvf-6-ri4_vLh02p5vTBNw-ViEFzRQdDeddAaR3ujlJOd4kMruGsZU6QXZugUk53rnGiYMT2FzkE3OOCOn6F3R-927qMdTJ0sQ9Db7CPkvU7g9d-d0a_1TdppQauUkSp4cy_I6ftsy6SjL4d9YLRpLppRypngrewq-vofdJPmPNb1KsUa0gohZaXeHimTUynZuodhKNGHEPUhRH0IsbKvHk__QP6JrAKXR-DWB7v_v0mvlp-b38pf0e6p1w</recordid><startdate>201810</startdate><enddate>201810</enddate><creator>Chen, Jinbin</creator><creator>Fang, Aiping</creator><creator>Chen, Minshan</creator><creator>Tuoheti, Yiminjiang</creator><creator>Zhou, Zhongguo</creator><creator>Xu, Li</creator><creator>Chen, Jiancong</creator><creator>Pan, Yangxun</creator><creator>Wang, Juncheng</creator><creator>Zhu, Huilian</creator><creator>Zhang, Yaojun</creator><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>WIN</scope><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>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-6619-1247</orcidid><orcidid>https://orcid.org/0000-0002-1929-4278</orcidid><orcidid>https://orcid.org/0000-0002-9752-4729</orcidid></search><sort><creationdate>201810</creationdate><title>A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma</title><author>Chen, Jinbin ; Fang, Aiping ; Chen, Minshan ; Tuoheti, Yiminjiang ; Zhou, Zhongguo ; Xu, Li ; Chen, Jiancong ; Pan, Yangxun ; Wang, Juncheng ; Zhu, Huilian ; Zhang, Yaojun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4437-d6381d61bf9a5cf1bc88f7983d563f52280b6cd98279f9f642ccb1a9fa9dfa3f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Albumins - metabolism</topic><topic>Biomarkers, Tumor - immunology</topic><topic>C-Reactive Protein - metabolism</topic><topic>Carcinoma, Hepatocellular - immunology</topic><topic>Carcinoma, Hepatocellular - pathology</topic><topic>Clinical Cancer Research</topic><topic>Female</topic><topic>Hepatocellular carcinoma</topic><topic>Humans</topic><topic>Inflammation</topic><topic>inflammation‐based score system</topic><topic>Liver cancer</topic><topic>Liver Neoplasms - immunology</topic><topic>Liver Neoplasms - pathology</topic><topic>Male</topic><topic>Metastases</topic><topic>Multivariate analysis</topic><topic>nomogram</topic><topic>Nomograms</topic><topic>Original Research</topic><topic>Prognosis</topic><topic>prognostic value</topic><topic>Prospective Studies</topic><topic>Random Allocation</topic><topic>Survival</topic><topic>Tumor Burden</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Jinbin</creatorcontrib><creatorcontrib>Fang, Aiping</creatorcontrib><creatorcontrib>Chen, Minshan</creatorcontrib><creatorcontrib>Tuoheti, Yiminjiang</creatorcontrib><creatorcontrib>Zhou, Zhongguo</creatorcontrib><creatorcontrib>Xu, Li</creatorcontrib><creatorcontrib>Chen, Jiancong</creatorcontrib><creatorcontrib>Pan, Yangxun</creatorcontrib><creatorcontrib>Wang, Juncheng</creatorcontrib><creatorcontrib>Zhu, Huilian</creatorcontrib><creatorcontrib>Zhang, Yaojun</creatorcontrib><collection>Wiley Open Access</collection><collection>Wiley Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Cancer medicine (Malden, MA)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Jinbin</au><au>Fang, Aiping</au><au>Chen, Minshan</au><au>Tuoheti, Yiminjiang</au><au>Zhou, Zhongguo</au><au>Xu, Li</au><au>Chen, Jiancong</au><au>Pan, Yangxun</au><au>Wang, Juncheng</au><au>Zhu, Huilian</au><au>Zhang, Yaojun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma</atitle><jtitle>Cancer medicine (Malden, MA)</jtitle><addtitle>Cancer Med</addtitle><date>2018-10</date><risdate>2018</risdate><volume>7</volume><issue>10</issue><spage>5027</spage><epage>5035</epage><pages>5027-5035</pages><issn>2045-7634</issn><eissn>2045-7634</eissn><abstract>Background and Aim
The existed staging systems were limited in the accuracy of prediction for overall survival (OS) of hepatocellular carcinoma (HCC) patients. The aim of this study is to establish a novel inflammation‐based prognostic system with nomogram for HCC patients.
Methods
A prospective cohort of patients was recruited and assigned to the training cohort (n = 659) and validation cohort (n = 320) randomly. Different inflammation‐based score systems were evaluated to select the best one predicting overall survival (OS). The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C‐index) and calibration curve and compared with conventional staging systems.
Results
With a highest C‐index and areas under the receiver operating characteristic curve (AUC), C‐reactive protein/albumin ratio (CAR) was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion and extra‐hepatic metastases. The C‐index of the nomogram was 0.813 (95% CI, 0.789‐0.837) in the training cohort and 0.794 (95% CI, 0.756‐0.832) in the validation cohort. The calibration curve for predicting probability of survival showed that the nomogram had a high consistency with follow‐up data. The C‐index of the novel system was higher than other conventional staging systems (P < 0.001).
Conclusions
The novel inflammation‐based nomogram, developed from prospectively collected data in the present study, predicted the OS of HCC patients.
The inflammation‐based score system with the highest predicting value and the parameters best reflecting tumor burden identified by multivariate analysis were selected to construct a novel predicting nomogram system. C‐reactive protein albumin ratio was selected to construct the novel system, along with tumor number, tumor size, macrovascular invasion, and extra‐hepatic metastases. The novel inflammation‐based nomogram, developed from prospectively collected data, predicted the overall survival of hepatocellular carcinoma patients.</abstract><cop>United States</cop><pub>John Wiley & Sons, Inc</pub><pmid>30259688</pmid><doi>10.1002/cam4.1787</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-6619-1247</orcidid><orcidid>https://orcid.org/0000-0002-1929-4278</orcidid><orcidid>https://orcid.org/0000-0002-9752-4729</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Albumins - metabolism Biomarkers, Tumor - immunology C-Reactive Protein - metabolism Carcinoma, Hepatocellular - immunology Carcinoma, Hepatocellular - pathology Clinical Cancer Research Female Hepatocellular carcinoma Humans Inflammation inflammation‐based score system Liver cancer Liver Neoplasms - immunology Liver Neoplasms - pathology Male Metastases Multivariate analysis nomogram Nomograms Original Research Prognosis prognostic value Prospective Studies Random Allocation Survival Tumor Burden |
| title | A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma |
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