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Establishment and validation of a recursive partitioning analysis based prognostic model for guiding re-radiotherapy in locally recurrent nasopharyngeal carcinoma patients
•A total of 531 patients with local recurrence nasopharyngeal carcinoma (lrNPC) were retrospectively reviewed.•We established and validated an integrated prognostic model for lrNPC patients.•Three risk groups were derived from an RPA model that combined rT stage and EBV DNA.•Re-radiotherapy could be...
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| Published in: | Radiotherapy and oncology 2022-03, Vol.168, p.61-68 |
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| creator | Sun, Xue-Song Zhu, Man-Yi Wen, Dong-Xiang Luo, Dong-Hua Sun, Rui Chen, Qiu-Yan Mai, Hai-Qiang |
| description | •A total of 531 patients with local recurrence nasopharyngeal carcinoma (lrNPC) were retrospectively reviewed.•We established and validated an integrated prognostic model for lrNPC patients.•Three risk groups were derived from an RPA model that combined rT stage and EBV DNA.•Re-radiotherapy could benefit patients in the low and intermediate-risk subgroups.•No association between re-RT and survival benefit was found in the high-risk. subgroup.
In this study, we aimed to establish and validate an integrated prognostic model for locally recurrent nasopharyngeal carcinoma (lrNPC) patients, and evaluate the benefit of re-radiotherapy (re-RT) in patients with different risk levels.
In total, 531 patients with lrNPC were retrospectively reviewed in this study, including 271 patients from 2006 to 2012 as the training cohort and 260 patients from 2013 to 2016 as the validation cohort. Overall survival (OS) was the primary endpoint. Multivariate analysis was performed to select the significant prognostic factors (P |
| doi_str_mv | 10.1016/j.radonc.2022.01.026 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2624658911</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0167814022000287</els_id><sourcerecordid>2624658911</sourcerecordid><originalsourceid>FETCH-LOGICAL-c362t-b7975df1e7af9db7d0448b7d1c57b16cbb8e35f162e2a4cca23f1ff41dd20823</originalsourceid><addsrcrecordid>eNp9kc2OFCEUhYnROD2jb2AMSzdVAvXbGxMzGR2TSdzMntyCSzcdClqgOuln8iWlUqNLV3fBd8_h3EPIB85qznj_-VRH0MGrWjAhasZrJvpXZMfHYV-xcRxek13BhmrkLbshtymdGGOCNcNbctN0RaLtxx35_ZAyTM6m44w-U_CaXsBZDdkGT4OhQCOqJSZ7QXqGmO36YP2hoOCuySY6QUJNzzEcfEjZKjoHjY6aEOlhsXplI1blszbkI0Y4X6n11AUFzl039bh6e0jhfIR49QcERxVEZX2YodhmW4D0jrwx4BK-f5l35Pnbw_P9Y_X08_uP-69PlWp6katp2A-dNhwHMHs9DZq17VgGV90w8V5N04hNZ3gvUECrFIjGcGNarrVgo2juyKdNtkT6tWDKcrZJoXPgMSxJil60fTfuOS9ou6EqhpQiGnmOdi4RJGdybUme5NaSXFuSjMvSUln7-OKwTDPqf0t_aynAlw3AEvNiMcqkygkUalvulaUO9v8OfwCI7quw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2624658911</pqid></control><display><type>article</type><title>Establishment and validation of a recursive partitioning analysis based prognostic model for guiding re-radiotherapy in locally recurrent nasopharyngeal carcinoma patients</title><source>ScienceDirect Journals</source><creator>Sun, Xue-Song ; Zhu, Man-Yi ; Wen, Dong-Xiang ; Luo, Dong-Hua ; Sun, Rui ; Chen, Qiu-Yan ; Mai, Hai-Qiang</creator><creatorcontrib>Sun, Xue-Song ; Zhu, Man-Yi ; Wen, Dong-Xiang ; Luo, Dong-Hua ; Sun, Rui ; Chen, Qiu-Yan ; Mai, Hai-Qiang</creatorcontrib><description>•A total of 531 patients with local recurrence nasopharyngeal carcinoma (lrNPC) were retrospectively reviewed.•We established and validated an integrated prognostic model for lrNPC patients.•Three risk groups were derived from an RPA model that combined rT stage and EBV DNA.•Re-radiotherapy could benefit patients in the low and intermediate-risk subgroups.•No association between re-RT and survival benefit was found in the high-risk. subgroup.
In this study, we aimed to establish and validate an integrated prognostic model for locally recurrent nasopharyngeal carcinoma (lrNPC) patients, and evaluate the benefit of re-radiotherapy (re-RT) in patients with different risk levels.
In total, 531 patients with lrNPC were retrospectively reviewed in this study, including 271 patients from 2006 to 2012 as the training cohort and 260 patients from 2013 to 2016 as the validation cohort. Overall survival (OS) was the primary endpoint. Multivariate analysis was performed to select the significant prognostic factors (P < 0.05). A prognostic model for OS was derived by recursive partitioning analysis (RPA) combining independent predictors using the algorithm of optimized binary partition.
Three independent prognostic factors (age, relapsed T [rT] stage, and Epstein-Barr virus [EBV] DNA) were identified from multivariate analysis. Five prognostic groups were derived from an RPA model that combined rT stage and EBV DNA. After further pair-wise comparisons of survival outcome in each group, three risk groups were generated. We investigated the role of re-RT in different risk groups, and found that re-RT could benefit patients in the low (P < 0.001) and intermediate-risk subgroups (P = 0.017), while no association between re-RT and survival benefit was found in the high-risk subgroup (P = 0.328). The results of risk stratification and re-RT efficacy were verified in the validation cohort.
Age, rT stage and EBV DNA were identified as independent predictors for lrNPC. We established an integrated RPA-based prognostic model for OS incorporating rT stage and EBV DNA, which could guide individual treatment for lrNPC.</description><identifier>ISSN: 0167-8140</identifier><identifier>EISSN: 1879-0887</identifier><identifier>DOI: 10.1016/j.radonc.2022.01.026</identifier><identifier>PMID: 35101468</identifier><language>eng</language><publisher>Ireland: Elsevier B.V</publisher><subject>DNA, Viral ; EBV DNA ; Epstein-Barr Virus Infections ; Herpesvirus 4, Human - genetics ; Humans ; Nasopharyngeal carcinoma ; Nasopharyngeal Carcinoma - pathology ; Nasopharyngeal Neoplasms - pathology ; Neoplasm Recurrence, Local ; Prognosis ; Radiotherapy ; Recurrence ; Retrospective Studies ; Survival</subject><ispartof>Radiotherapy and oncology, 2022-03, Vol.168, p.61-68</ispartof><rights>2022 Elsevier B.V.</rights><rights>Copyright © 2022 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-b7975df1e7af9db7d0448b7d1c57b16cbb8e35f162e2a4cca23f1ff41dd20823</citedby><cites>FETCH-LOGICAL-c362t-b7975df1e7af9db7d0448b7d1c57b16cbb8e35f162e2a4cca23f1ff41dd20823</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35101468$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sun, Xue-Song</creatorcontrib><creatorcontrib>Zhu, Man-Yi</creatorcontrib><creatorcontrib>Wen, Dong-Xiang</creatorcontrib><creatorcontrib>Luo, Dong-Hua</creatorcontrib><creatorcontrib>Sun, Rui</creatorcontrib><creatorcontrib>Chen, Qiu-Yan</creatorcontrib><creatorcontrib>Mai, Hai-Qiang</creatorcontrib><title>Establishment and validation of a recursive partitioning analysis based prognostic model for guiding re-radiotherapy in locally recurrent nasopharyngeal carcinoma patients</title><title>Radiotherapy and oncology</title><addtitle>Radiother Oncol</addtitle><description>•A total of 531 patients with local recurrence nasopharyngeal carcinoma (lrNPC) were retrospectively reviewed.•We established and validated an integrated prognostic model for lrNPC patients.•Three risk groups were derived from an RPA model that combined rT stage and EBV DNA.•Re-radiotherapy could benefit patients in the low and intermediate-risk subgroups.•No association between re-RT and survival benefit was found in the high-risk. subgroup.
In this study, we aimed to establish and validate an integrated prognostic model for locally recurrent nasopharyngeal carcinoma (lrNPC) patients, and evaluate the benefit of re-radiotherapy (re-RT) in patients with different risk levels.
In total, 531 patients with lrNPC were retrospectively reviewed in this study, including 271 patients from 2006 to 2012 as the training cohort and 260 patients from 2013 to 2016 as the validation cohort. Overall survival (OS) was the primary endpoint. Multivariate analysis was performed to select the significant prognostic factors (P < 0.05). A prognostic model for OS was derived by recursive partitioning analysis (RPA) combining independent predictors using the algorithm of optimized binary partition.
Three independent prognostic factors (age, relapsed T [rT] stage, and Epstein-Barr virus [EBV] DNA) were identified from multivariate analysis. Five prognostic groups were derived from an RPA model that combined rT stage and EBV DNA. After further pair-wise comparisons of survival outcome in each group, three risk groups were generated. We investigated the role of re-RT in different risk groups, and found that re-RT could benefit patients in the low (P < 0.001) and intermediate-risk subgroups (P = 0.017), while no association between re-RT and survival benefit was found in the high-risk subgroup (P = 0.328). The results of risk stratification and re-RT efficacy were verified in the validation cohort.
Age, rT stage and EBV DNA were identified as independent predictors for lrNPC. We established an integrated RPA-based prognostic model for OS incorporating rT stage and EBV DNA, which could guide individual treatment for lrNPC.</description><subject>DNA, Viral</subject><subject>EBV DNA</subject><subject>Epstein-Barr Virus Infections</subject><subject>Herpesvirus 4, Human - genetics</subject><subject>Humans</subject><subject>Nasopharyngeal carcinoma</subject><subject>Nasopharyngeal Carcinoma - pathology</subject><subject>Nasopharyngeal Neoplasms - pathology</subject><subject>Neoplasm Recurrence, Local</subject><subject>Prognosis</subject><subject>Radiotherapy</subject><subject>Recurrence</subject><subject>Retrospective Studies</subject><subject>Survival</subject><issn>0167-8140</issn><issn>1879-0887</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kc2OFCEUhYnROD2jb2AMSzdVAvXbGxMzGR2TSdzMntyCSzcdClqgOuln8iWlUqNLV3fBd8_h3EPIB85qznj_-VRH0MGrWjAhasZrJvpXZMfHYV-xcRxek13BhmrkLbshtymdGGOCNcNbctN0RaLtxx35_ZAyTM6m44w-U_CaXsBZDdkGT4OhQCOqJSZ7QXqGmO36YP2hoOCuySY6QUJNzzEcfEjZKjoHjY6aEOlhsXplI1blszbkI0Y4X6n11AUFzl039bh6e0jhfIR49QcERxVEZX2YodhmW4D0jrwx4BK-f5l35Pnbw_P9Y_X08_uP-69PlWp6katp2A-dNhwHMHs9DZq17VgGV90w8V5N04hNZ3gvUECrFIjGcGNarrVgo2juyKdNtkT6tWDKcrZJoXPgMSxJil60fTfuOS9ou6EqhpQiGnmOdi4RJGdybUme5NaSXFuSjMvSUln7-OKwTDPqf0t_aynAlw3AEvNiMcqkygkUalvulaUO9v8OfwCI7quw</recordid><startdate>202203</startdate><enddate>202203</enddate><creator>Sun, Xue-Song</creator><creator>Zhu, Man-Yi</creator><creator>Wen, Dong-Xiang</creator><creator>Luo, Dong-Hua</creator><creator>Sun, Rui</creator><creator>Chen, Qiu-Yan</creator><creator>Mai, Hai-Qiang</creator><general>Elsevier B.V</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>7X8</scope></search><sort><creationdate>202203</creationdate><title>Establishment and validation of a recursive partitioning analysis based prognostic model for guiding re-radiotherapy in locally recurrent nasopharyngeal carcinoma patients</title><author>Sun, Xue-Song ; Zhu, Man-Yi ; Wen, Dong-Xiang ; Luo, Dong-Hua ; Sun, Rui ; Chen, Qiu-Yan ; Mai, Hai-Qiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-b7975df1e7af9db7d0448b7d1c57b16cbb8e35f162e2a4cca23f1ff41dd20823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>DNA, Viral</topic><topic>EBV DNA</topic><topic>Epstein-Barr Virus Infections</topic><topic>Herpesvirus 4, Human - genetics</topic><topic>Humans</topic><topic>Nasopharyngeal carcinoma</topic><topic>Nasopharyngeal Carcinoma - pathology</topic><topic>Nasopharyngeal Neoplasms - pathology</topic><topic>Neoplasm Recurrence, Local</topic><topic>Prognosis</topic><topic>Radiotherapy</topic><topic>Recurrence</topic><topic>Retrospective Studies</topic><topic>Survival</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sun, Xue-Song</creatorcontrib><creatorcontrib>Zhu, Man-Yi</creatorcontrib><creatorcontrib>Wen, Dong-Xiang</creatorcontrib><creatorcontrib>Luo, Dong-Hua</creatorcontrib><creatorcontrib>Sun, Rui</creatorcontrib><creatorcontrib>Chen, Qiu-Yan</creatorcontrib><creatorcontrib>Mai, Hai-Qiang</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Radiotherapy and oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sun, Xue-Song</au><au>Zhu, Man-Yi</au><au>Wen, Dong-Xiang</au><au>Luo, Dong-Hua</au><au>Sun, Rui</au><au>Chen, Qiu-Yan</au><au>Mai, Hai-Qiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Establishment and validation of a recursive partitioning analysis based prognostic model for guiding re-radiotherapy in locally recurrent nasopharyngeal carcinoma patients</atitle><jtitle>Radiotherapy and oncology</jtitle><addtitle>Radiother Oncol</addtitle><date>2022-03</date><risdate>2022</risdate><volume>168</volume><spage>61</spage><epage>68</epage><pages>61-68</pages><issn>0167-8140</issn><eissn>1879-0887</eissn><abstract>•A total of 531 patients with local recurrence nasopharyngeal carcinoma (lrNPC) were retrospectively reviewed.•We established and validated an integrated prognostic model for lrNPC patients.•Three risk groups were derived from an RPA model that combined rT stage and EBV DNA.•Re-radiotherapy could benefit patients in the low and intermediate-risk subgroups.•No association between re-RT and survival benefit was found in the high-risk. subgroup.
In this study, we aimed to establish and validate an integrated prognostic model for locally recurrent nasopharyngeal carcinoma (lrNPC) patients, and evaluate the benefit of re-radiotherapy (re-RT) in patients with different risk levels.
In total, 531 patients with lrNPC were retrospectively reviewed in this study, including 271 patients from 2006 to 2012 as the training cohort and 260 patients from 2013 to 2016 as the validation cohort. Overall survival (OS) was the primary endpoint. Multivariate analysis was performed to select the significant prognostic factors (P < 0.05). A prognostic model for OS was derived by recursive partitioning analysis (RPA) combining independent predictors using the algorithm of optimized binary partition.
Three independent prognostic factors (age, relapsed T [rT] stage, and Epstein-Barr virus [EBV] DNA) were identified from multivariate analysis. Five prognostic groups were derived from an RPA model that combined rT stage and EBV DNA. After further pair-wise comparisons of survival outcome in each group, three risk groups were generated. We investigated the role of re-RT in different risk groups, and found that re-RT could benefit patients in the low (P < 0.001) and intermediate-risk subgroups (P = 0.017), while no association between re-RT and survival benefit was found in the high-risk subgroup (P = 0.328). The results of risk stratification and re-RT efficacy were verified in the validation cohort.
Age, rT stage and EBV DNA were identified as independent predictors for lrNPC. We established an integrated RPA-based prognostic model for OS incorporating rT stage and EBV DNA, which could guide individual treatment for lrNPC.</abstract><cop>Ireland</cop><pub>Elsevier B.V</pub><pmid>35101468</pmid><doi>10.1016/j.radonc.2022.01.026</doi><tpages>8</tpages></addata></record> |
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| subjects | DNA, Viral EBV DNA Epstein-Barr Virus Infections Herpesvirus 4, Human - genetics Humans Nasopharyngeal carcinoma Nasopharyngeal Carcinoma - pathology Nasopharyngeal Neoplasms - pathology Neoplasm Recurrence, Local Prognosis Radiotherapy Recurrence Retrospective Studies Survival |
| title | Establishment and validation of a recursive partitioning analysis based prognostic model for guiding re-radiotherapy in locally recurrent nasopharyngeal carcinoma patients |
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