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Development of a Nomogram Model for Treatment of Elderly Patients with Locoregionally Advanced Nasopharyngeal Carcinoma

(1) Purpose: This study aims to explore risk-adapted treatment for elderly patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) according to their pretreatment risk stratification and the degree of comorbidity. (2) Methods: A total of 583 elderly LA-NPC patients diagnosed from Jan...

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Published in:Journal of personalized medicine 2021-10, Vol.11 (11), p.1065
Main Authors: Kou, Jia, Zhang, Lu-Lu, Yang, Xing-Li, Wen, Dan-Wan, Zhou, Guan-Qun, Wu, Chen-Fei, Xu, Si-Si, Zheng, Wei-Hong, Qi, Zhen-Yu, Sun, Ying, Lin, Li
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container_title Journal of personalized medicine
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creator Kou, Jia
Zhang, Lu-Lu
Yang, Xing-Li
Wen, Dan-Wan
Zhou, Guan-Qun
Wu, Chen-Fei
Xu, Si-Si
Zheng, Wei-Hong
Qi, Zhen-Yu
Sun, Ying
Lin, Li
description (1) Purpose: This study aims to explore risk-adapted treatment for elderly patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) according to their pretreatment risk stratification and the degree of comorbidity. (2) Methods: A total of 583 elderly LA-NPC patients diagnosed from January 2011 to January 2018 are retrospectively studied. A nomogram for disease-free survival (DFS) is constructed based on multivariate Cox regression analysis. The performance of the model is evaluated by using the area under the curve (AUC) of the receiver operating characteristic curve and Harrell concordance index (C-index). Then, the entire cohort is divided into different risk groups according to the nomogram cutoff value determined by X-tile analysis. The degree of comorbidities is assessed by the Charlson Comorbidity Index (CCI). Finally, survival rates are estimated and compared by the Kaplan–Meier method and the log-rank test. (3) Results: A nomogram for DFS is constructed with T/N classification, Epstein-Barr virus DNA and albumin. The nomogram shows well prognostic performance and significantly outperformed the tumor-node-metastasis staging system for estimating DFS (AUC, 0.710 vs. 0.607; C-index, 0.668 vs. 0.585; both p < 0.001). The high-risk group generated by nomogram has significantly poorer survival compared with the low-risk group (3-year DFS, 76.7% vs. 44.6%, p < 0.001). For high-risk patients with fewer comorbidities (CCI = 2), chemotherapy combined with radiotherapy is associated with significantly better survival (p < 0.05) than radiotherapy alone. (4) Conclusion: A prognostic nomogram for DFS is constructed with generating two risk groups. Combining risk stratification and the degree of comorbidities can guide risk-adapted treatment for elderly LA-NPC patients.
doi_str_mv 10.3390/jpm11111065
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(2) Methods: A total of 583 elderly LA-NPC patients diagnosed from January 2011 to January 2018 are retrospectively studied. A nomogram for disease-free survival (DFS) is constructed based on multivariate Cox regression analysis. The performance of the model is evaluated by using the area under the curve (AUC) of the receiver operating characteristic curve and Harrell concordance index (C-index). Then, the entire cohort is divided into different risk groups according to the nomogram cutoff value determined by X-tile analysis. The degree of comorbidities is assessed by the Charlson Comorbidity Index (CCI). Finally, survival rates are estimated and compared by the Kaplan–Meier method and the log-rank test. (3) Results: A nomogram for DFS is constructed with T/N classification, Epstein-Barr virus DNA and albumin. The nomogram shows well prognostic performance and significantly outperformed the tumor-node-metastasis staging system for estimating DFS (AUC, 0.710 vs. 0.607; C-index, 0.668 vs. 0.585; both p &lt; 0.001). The high-risk group generated by nomogram has significantly poorer survival compared with the low-risk group (3-year DFS, 76.7% vs. 44.6%, p &lt; 0.001). For high-risk patients with fewer comorbidities (CCI = 2), chemotherapy combined with radiotherapy is associated with significantly better survival (p &lt; 0.05) than radiotherapy alone. (4) Conclusion: A prognostic nomogram for DFS is constructed with generating two risk groups. Combining risk stratification and the degree of comorbidities can guide risk-adapted treatment for elderly LA-NPC patients.</description><identifier>ISSN: 2075-4426</identifier><identifier>EISSN: 2075-4426</identifier><identifier>DOI: 10.3390/jpm11111065</identifier><identifier>PMID: 34834417</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Age ; Cancer ; Chemotherapy ; Comorbidity ; DNA viruses ; Epstein-Barr virus ; Medical prognosis ; Medical records ; Metastases ; Mortality ; Multivariate analysis ; Nasopharyngeal carcinoma ; Patients ; Precision medicine ; Radiation therapy ; Regression analysis ; Risk groups ; Software ; Survival ; Tumors</subject><ispartof>Journal of personalized medicine, 2021-10, Vol.11 (11), p.1065</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-ddcb4e02c2db075825489f29eb67181c12c8cb81b856622bae8b315555d1e0083</citedby><cites>FETCH-LOGICAL-c386t-ddcb4e02c2db075825489f29eb67181c12c8cb81b856622bae8b315555d1e0083</cites><orcidid>0000-0002-7989-4224 ; 0000-0003-1052-1566</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2602094165/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2602094165?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids></links><search><creatorcontrib>Kou, Jia</creatorcontrib><creatorcontrib>Zhang, Lu-Lu</creatorcontrib><creatorcontrib>Yang, Xing-Li</creatorcontrib><creatorcontrib>Wen, Dan-Wan</creatorcontrib><creatorcontrib>Zhou, Guan-Qun</creatorcontrib><creatorcontrib>Wu, Chen-Fei</creatorcontrib><creatorcontrib>Xu, Si-Si</creatorcontrib><creatorcontrib>Zheng, Wei-Hong</creatorcontrib><creatorcontrib>Qi, Zhen-Yu</creatorcontrib><creatorcontrib>Sun, Ying</creatorcontrib><creatorcontrib>Lin, Li</creatorcontrib><title>Development of a Nomogram Model for Treatment of Elderly Patients with Locoregionally Advanced Nasopharyngeal Carcinoma</title><title>Journal of personalized medicine</title><description>(1) Purpose: This study aims to explore risk-adapted treatment for elderly patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) according to their pretreatment risk stratification and the degree of comorbidity. (2) Methods: A total of 583 elderly LA-NPC patients diagnosed from January 2011 to January 2018 are retrospectively studied. A nomogram for disease-free survival (DFS) is constructed based on multivariate Cox regression analysis. The performance of the model is evaluated by using the area under the curve (AUC) of the receiver operating characteristic curve and Harrell concordance index (C-index). Then, the entire cohort is divided into different risk groups according to the nomogram cutoff value determined by X-tile analysis. The degree of comorbidities is assessed by the Charlson Comorbidity Index (CCI). Finally, survival rates are estimated and compared by the Kaplan–Meier method and the log-rank test. (3) Results: A nomogram for DFS is constructed with T/N classification, Epstein-Barr virus DNA and albumin. 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Zhang, Lu-Lu ; Yang, Xing-Li ; Wen, Dan-Wan ; Zhou, Guan-Qun ; Wu, Chen-Fei ; Xu, Si-Si ; Zheng, Wei-Hong ; Qi, Zhen-Yu ; Sun, Ying ; Lin, Li</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-ddcb4e02c2db075825489f29eb67181c12c8cb81b856622bae8b315555d1e0083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Age</topic><topic>Cancer</topic><topic>Chemotherapy</topic><topic>Comorbidity</topic><topic>DNA viruses</topic><topic>Epstein-Barr virus</topic><topic>Medical prognosis</topic><topic>Medical records</topic><topic>Metastases</topic><topic>Mortality</topic><topic>Multivariate analysis</topic><topic>Nasopharyngeal carcinoma</topic><topic>Patients</topic><topic>Precision medicine</topic><topic>Radiation therapy</topic><topic>Regression analysis</topic><topic>Risk groups</topic><topic>Software</topic><topic>Survival</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kou, Jia</creatorcontrib><creatorcontrib>Zhang, Lu-Lu</creatorcontrib><creatorcontrib>Yang, Xing-Li</creatorcontrib><creatorcontrib>Wen, Dan-Wan</creatorcontrib><creatorcontrib>Zhou, Guan-Qun</creatorcontrib><creatorcontrib>Wu, Chen-Fei</creatorcontrib><creatorcontrib>Xu, Si-Si</creatorcontrib><creatorcontrib>Zheng, Wei-Hong</creatorcontrib><creatorcontrib>Qi, Zhen-Yu</creatorcontrib><creatorcontrib>Sun, Ying</creatorcontrib><creatorcontrib>Lin, Li</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</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>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>ProQuest Biological Science Journals</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>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of personalized medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kou, Jia</au><au>Zhang, Lu-Lu</au><au>Yang, Xing-Li</au><au>Wen, Dan-Wan</au><au>Zhou, Guan-Qun</au><au>Wu, Chen-Fei</au><au>Xu, Si-Si</au><au>Zheng, Wei-Hong</au><au>Qi, Zhen-Yu</au><au>Sun, Ying</au><au>Lin, Li</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a Nomogram Model for Treatment of Elderly Patients with Locoregionally Advanced Nasopharyngeal Carcinoma</atitle><jtitle>Journal of personalized medicine</jtitle><date>2021-10-22</date><risdate>2021</risdate><volume>11</volume><issue>11</issue><spage>1065</spage><pages>1065-</pages><issn>2075-4426</issn><eissn>2075-4426</eissn><abstract>(1) Purpose: This study aims to explore risk-adapted treatment for elderly patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) according to their pretreatment risk stratification and the degree of comorbidity. (2) Methods: A total of 583 elderly LA-NPC patients diagnosed from January 2011 to January 2018 are retrospectively studied. A nomogram for disease-free survival (DFS) is constructed based on multivariate Cox regression analysis. The performance of the model is evaluated by using the area under the curve (AUC) of the receiver operating characteristic curve and Harrell concordance index (C-index). Then, the entire cohort is divided into different risk groups according to the nomogram cutoff value determined by X-tile analysis. The degree of comorbidities is assessed by the Charlson Comorbidity Index (CCI). Finally, survival rates are estimated and compared by the Kaplan–Meier method and the log-rank test. (3) Results: A nomogram for DFS is constructed with T/N classification, Epstein-Barr virus DNA and albumin. The nomogram shows well prognostic performance and significantly outperformed the tumor-node-metastasis staging system for estimating DFS (AUC, 0.710 vs. 0.607; C-index, 0.668 vs. 0.585; both p &lt; 0.001). The high-risk group generated by nomogram has significantly poorer survival compared with the low-risk group (3-year DFS, 76.7% vs. 44.6%, p &lt; 0.001). For high-risk patients with fewer comorbidities (CCI = 2), chemotherapy combined with radiotherapy is associated with significantly better survival (p &lt; 0.05) than radiotherapy alone. (4) Conclusion: A prognostic nomogram for DFS is constructed with generating two risk groups. Combining risk stratification and the degree of comorbidities can guide risk-adapted treatment for elderly LA-NPC patients.</abstract><cop>Basel</cop><pub>MDPI AG</pub><pmid>34834417</pmid><doi>10.3390/jpm11111065</doi><orcidid>https://orcid.org/0000-0002-7989-4224</orcidid><orcidid>https://orcid.org/0000-0003-1052-1566</orcidid><oa>free_for_read</oa></addata></record>
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subjects Age
Cancer
Chemotherapy
Comorbidity
DNA viruses
Epstein-Barr virus
Medical prognosis
Medical records
Metastases
Mortality
Multivariate analysis
Nasopharyngeal carcinoma
Patients
Precision medicine
Radiation therapy
Regression analysis
Risk groups
Software
Survival
Tumors
title Development of a Nomogram Model for Treatment of Elderly Patients with Locoregionally Advanced Nasopharyngeal Carcinoma
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