HbA1c-Based Score Model for Predicting Death Risk in Patients with Hepatocellular Carcinoma and Type 2 Diabetes Mellitus

Aim. To establish a new score model to predict risk of death in patients with hepatocellular carcinoma and type 2 diabetes mellitus. Methods. This was a retrospective study of 147 patients with hepatocellular carcinoma and type 2 diabetes mellitus who came to Beijing Ditan Hospital between October 2...

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Published in:Journal of diabetes research 2017-01, Vol.2017 (2017), p.1-7
Main Authors: Wang, Xianbo, Jiang, Yu-yong, Liu, Xiaoli, Zhang, Shuan, Choo, Hyunwook, Yang, Zhiyun
Format: Article
Language:English
Subjects:
Age
Aged
Carcinoma, Hepatocellular - blood
Carcinoma, Hepatocellular - complications
Carcinoma, Hepatocellular - mortality
Diabetes
Diabetes Mellitus, Type 2 - blood
Diabetes Mellitus, Type 2 - complications
Diabetes Mellitus, Type 2 - mortality
Family medical history
Female
Glucose
Glycated Hemoglobin A - analysis
Health risk assessment
Hemoglobin
Humans
Laboratories
Liver cancer
Liver Neoplasms - blood
Liver Neoplasms - complications
Liver Neoplasms - mortality
Magnetic resonance imaging
Male
Medical prognosis
Middle Aged
Models, Theoretical
NMR
Nuclear magnetic resonance
Prognosis
Regression analysis
Retrospective Studies
Risk
Risk Assessment
Risk factors
Statistical analysis
Survival Rate
Ultrasonic imaging
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container_issue 2017
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creator Wang, Xianbo
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Liu, Xiaoli
Zhang, Shuan
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description Aim. To establish a new score model to predict risk of death in patients with hepatocellular carcinoma and type 2 diabetes mellitus. Methods. This was a retrospective study of 147 patients with hepatocellular carcinoma and type 2 diabetes mellitus who came to Beijing Ditan Hospital between October 2008 and June 2013. Univariate and multivariate logistic regression analysis was performed to obtain the independent factors associated with death risk. A new score model was devised according to these factors. Results. A prediction score model composed of HbA1c, NLR, age, and CTP class was devised, which ranged from 0 to 7. AUROC of the score was 0.853 (P
doi_str_mv 10.1155/2017/3819502
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To establish a new score model to predict risk of death in patients with hepatocellular carcinoma and type 2 diabetes mellitus. Methods. This was a retrospective study of 147 patients with hepatocellular carcinoma and type 2 diabetes mellitus who came to Beijing Ditan Hospital between October 2008 and June 2013. Univariate and multivariate logistic regression analysis was performed to obtain the independent factors associated with death risk. A new score model was devised according to these factors. Results. A prediction score model composed of HbA1c, NLR, age, and CTP class was devised, which ranged from 0 to 7. AUROC of the score was 0.853 (P&lt;0.001, 95% CI: 0.791–0.915). Scores 0–2, 3-4, and 5–7 identified patients as low-, medium-, and high-risk categories. The cumulative survival rate was 93.6%, 83.0%, and 74.5% in the low-risk group in 1, 2, and 3 years, while it was 64.0%, 46.0%, and 26.0% in the medium-risk group, whereas it was 24.0%, 12.0%, and 6.0% in the high-risk group, respectively. The cumulative survival rate was significantly higher in the low-risk group than that in the medium-risk group and high-risk group (P&lt;0.001). Conclusion. The HbA1c-based score model can be used to predict death risk in patients with hepatocellular carcinoma and type 2 diabetes mellitus.</description><identifier>ISSN: 2314-6745</identifier><identifier>EISSN: 2314-6753</identifier><identifier>DOI: 10.1155/2017/3819502</identifier><identifier>PMID: 28154829</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Age ; Aged ; Carcinoma, Hepatocellular - blood ; Carcinoma, Hepatocellular - complications ; Carcinoma, Hepatocellular - mortality ; Diabetes ; Diabetes Mellitus, Type 2 - blood ; Diabetes Mellitus, Type 2 - complications ; Diabetes Mellitus, Type 2 - mortality ; Family medical history ; Female ; Glucose ; Glycated Hemoglobin A - analysis ; Health risk assessment ; Hemoglobin ; Humans ; Laboratories ; Liver cancer ; Liver Neoplasms - blood ; Liver Neoplasms - complications ; Liver Neoplasms - mortality ; Magnetic resonance imaging ; Male ; Medical prognosis ; Middle Aged ; Models, Theoretical ; NMR ; Nuclear magnetic resonance ; Prognosis ; Regression analysis ; Retrospective Studies ; Risk ; Risk Assessment ; Risk factors ; Statistical analysis ; Survival Rate ; Ultrasonic imaging</subject><ispartof>Journal of diabetes research, 2017-01, Vol.2017 (2017), p.1-7</ispartof><rights>Copyright © 2017 Lingling He et al.</rights><rights>Copyright © 2017 Lingling He et al. 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>Copyright © 2017 Lingling He et al. 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c537t-f1a5e9c678b6fe561f7891e59ddf1a1b65fb3fb7c0314fbd1825623232863e63</citedby><cites>FETCH-LOGICAL-c537t-f1a5e9c678b6fe561f7891e59ddf1a1b65fb3fb7c0314fbd1825623232863e63</cites><orcidid>0000-0001-7218-0846</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2407644934/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2407644934?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,883,25736,27907,27908,36995,36996,44573,53774,53776,74877</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28154829$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Gao, Chun</contributor><contributor>Chun Gao</contributor><creatorcontrib>Wang, Xianbo</creatorcontrib><creatorcontrib>Jiang, Yu-yong</creatorcontrib><creatorcontrib>Liu, Xiaoli</creatorcontrib><creatorcontrib>Zhang, Shuan</creatorcontrib><creatorcontrib>Choo, Hyunwook</creatorcontrib><creatorcontrib>Yang, Zhiyun</creatorcontrib><title>HbA1c-Based Score Model for Predicting Death Risk in Patients with Hepatocellular Carcinoma and Type 2 Diabetes Mellitus</title><title>Journal of diabetes research</title><addtitle>J Diabetes Res</addtitle><description>Aim. To establish a new score model to predict risk of death in patients with hepatocellular carcinoma and type 2 diabetes mellitus. Methods. This was a retrospective study of 147 patients with hepatocellular carcinoma and type 2 diabetes mellitus who came to Beijing Ditan Hospital between October 2008 and June 2013. Univariate and multivariate logistic regression analysis was performed to obtain the independent factors associated with death risk. A new score model was devised according to these factors. Results. A prediction score model composed of HbA1c, NLR, age, and CTP class was devised, which ranged from 0 to 7. AUROC of the score was 0.853 (P&lt;0.001, 95% CI: 0.791–0.915). Scores 0–2, 3-4, and 5–7 identified patients as low-, medium-, and high-risk categories. The cumulative survival rate was 93.6%, 83.0%, and 74.5% in the low-risk group in 1, 2, and 3 years, while it was 64.0%, 46.0%, and 26.0% in the medium-risk group, whereas it was 24.0%, 12.0%, and 6.0% in the high-risk group, respectively. The cumulative survival rate was significantly higher in the low-risk group than that in the medium-risk group and high-risk group (P&lt;0.001). Conclusion. 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To establish a new score model to predict risk of death in patients with hepatocellular carcinoma and type 2 diabetes mellitus. Methods. This was a retrospective study of 147 patients with hepatocellular carcinoma and type 2 diabetes mellitus who came to Beijing Ditan Hospital between October 2008 and June 2013. Univariate and multivariate logistic regression analysis was performed to obtain the independent factors associated with death risk. A new score model was devised according to these factors. Results. A prediction score model composed of HbA1c, NLR, age, and CTP class was devised, which ranged from 0 to 7. AUROC of the score was 0.853 (P&lt;0.001, 95% CI: 0.791–0.915). Scores 0–2, 3-4, and 5–7 identified patients as low-, medium-, and high-risk categories. The cumulative survival rate was 93.6%, 83.0%, and 74.5% in the low-risk group in 1, 2, and 3 years, while it was 64.0%, 46.0%, and 26.0% in the medium-risk group, whereas it was 24.0%, 12.0%, and 6.0% in the high-risk group, respectively. The cumulative survival rate was significantly higher in the low-risk group than that in the medium-risk group and high-risk group (P&lt;0.001). Conclusion. The HbA1c-based score model can be used to predict death risk in patients with hepatocellular carcinoma and type 2 diabetes mellitus.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><pmid>28154829</pmid><doi>10.1155/2017/3819502</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-7218-0846</orcidid><oa>free_for_read</oa></addata></record>
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subjects Age
Aged
Carcinoma, Hepatocellular - blood
Carcinoma, Hepatocellular - complications
Carcinoma, Hepatocellular - mortality
Diabetes
Diabetes Mellitus, Type 2 - blood
Diabetes Mellitus, Type 2 - complications
Diabetes Mellitus, Type 2 - mortality
Family medical history
Female
Glucose
Glycated Hemoglobin A - analysis
Health risk assessment
Hemoglobin
Humans
Laboratories
Liver cancer
Liver Neoplasms - blood
Liver Neoplasms - complications
Liver Neoplasms - mortality
Magnetic resonance imaging
Male
Medical prognosis
Middle Aged
Models, Theoretical
NMR
Nuclear magnetic resonance
Prognosis
Regression analysis
Retrospective Studies
Risk
Risk Assessment
Risk factors
Statistical analysis
Survival Rate
Ultrasonic imaging
title HbA1c-Based Score Model for Predicting Death Risk in Patients with Hepatocellular Carcinoma and Type 2 Diabetes Mellitus
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