Development and validation of a web‐based calculator to predict individualized conditional risk of site‐specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases
Background Conditional survival (CS) provides dynamic prognostic estimates by considering the patients existing survival time. Since CS for endemic nasopharyngeal carcinoma (NPC) is lacking, we aimed to assess the CS of endemic NPC and establish a web‐based calculator to predict individualized, cond...
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| Veröffentlicht in: | Cancer communications (London, England) England), 2021-01, Vol.41 (1), p.37-50 |
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| creator | Wu, Chen‐Fei Lv, Jia‐Wei Lin, Li Mao, Yan‐Ping Deng, Bin Zheng, Wei‐Hong Wen, Dan‐Wan Chen, Yue Kou, Jia Chen, Fo‐Ping Yang, Xing‐Li Zheng, Zi‐Qi Li, Zhi‐Xuan Xu, Si‐Si Ma, Jun Sun, Ying |
| description | Background
Conditional survival (CS) provides dynamic prognostic estimates by considering the patients existing survival time. Since CS for endemic nasopharyngeal carcinoma (NPC) is lacking, we aimed to assess the CS of endemic NPC and establish a web‐based calculator to predict individualized, conditional site‐specific recurrence risk.
Methods
Using an NPC‐specific database with a big‐data intelligence platform, 10,058 endemic patients with non‐metastatic stage I–IVA NPC receiving intensity‐modulated radiotherapy with or without chemotherapy between April 2009 and December 2015 were investigated. Crude CS estimates of conditional overall survival (COS), conditional disease‐free survival (CDFS), conditional locoregional relapse‐free survival (CLRRFS), conditional distant metastasis‐free survival (CDMFS), and conditional NPC‐specific survival (CNPC‐SS) were calculated. Covariate‐adjusted CS estimates were generated using inverse probability weighting. A prediction model was established using competing risk models and was externally validated with an independent, non‐metastatic stage I–IVA NPC cohort undergoing intensity‐modulated radiotherapy with or without chemotherapy (n = 601) at another institution.
Results
The median follow‐up of the primary cohort was 67.2 months. The 5‐year COS, CDFS, CLRRFS, CDMFS, and CNPC‐SS increased from 86.2%, 78.1%, 89.8%, 87.3%, and 87.6% at diagnosis to 87.3%, 87.7%, 94.4%, 96.0%, and 90.1%, respectively, for an existing survival time of 3 years since diagnosis. Differences in CS estimates between prognostic factor subgroups of each endpoint were noticeable at diagnosis but diminished with time, whereas an ever‐increasing disparity in CS between different age subgroups was observed over time. Notably, the prognoses of patients that were poor at diagnosis improved greatly as patients survived longer. For individualized CS predictions, we developed a web‐based model to estimate the conditional risk of local (C‐index, 0.656), regional (0.667), bone (0.742), lung (0.681), and liver (0.711) recurrence, which significantly outperformed the current staging system (P < 0.001). The performance of this web‐based model was further validated using an external validation cohort (median follow‐up, 61.3 months), with C‐indices of 0.672, 0.736, 0.754, 0.663, and 0.721, respectively.
Conclusions
We characterized the CS of endemic NPC in the largest cohort to date. Moreover, we established a web‐based calculator to predict the CS of site‐spe |
| doi_str_mv | 10.1002/cac2.12113 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7819551</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2702741446</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4483-ebfc02d19c6405a6e1c75805761a2fb87cdae23b2f5317171f9213c12254ac603</originalsourceid><addsrcrecordid>eNp9kc1u1DAUhSMEolXphgdAltghpvgnzg8LpNHwK1ViA2vr5vqmdcnYwU6mGlY8Ai_Ey_AkOEypygZ5YVs-5_OxT1E8FvxMcC5fIKA8E1IIda84llqqldJlc__O-qg4TemKcy7api21elgcKSVr3rb8uPj5mnY0hHFLfmLgLdvB4CxMLngWegbsmrpf3390kMgyhAHnAaYQ2RTYGMk6nJjz1u2cnbPx2yIKeb_4YWDRpS8LJrmJMiWNhK53yCLhHCN5pOxmHlIYLyHu_QVlE0JE58MWXrJ1huyTSwtD8OdcN4y8pW1GYE6UHhUPehgSnd7MJ8Xnt28-bd6vzj---7BZn6-wLBu1oq5HLq1osSq5hooE1rrhuq4EyL5rarRAUnWy10rUefStFAqFlLoErLg6KV4duOPcbcli_qwIgxmj2-bYJoAz_554d2kuws7UjWi1Fhnw9AYQw9eZ0mSuwhzz65LJTci6FGVZZdWzgwpjSClSf3uD4GZp2yxtmz9tZ_GTu5lupX-7zQJxEFy7gfb_QZnNeiMP0N8SebnQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2702741446</pqid></control><display><type>article</type><title>Development and validation of a web‐based calculator to predict individualized conditional risk of site‐specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases</title><source>Wiley Online Library Journals Frontfile Complete</source><source>Wiley Online Library Open Access</source><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central</source><creator>Wu, Chen‐Fei ; Lv, Jia‐Wei ; Lin, Li ; Mao, Yan‐Ping ; Deng, Bin ; Zheng, Wei‐Hong ; Wen, Dan‐Wan ; Chen, Yue ; Kou, Jia ; Chen, Fo‐Ping ; Yang, Xing‐Li ; Zheng, Zi‐Qi ; Li, Zhi‐Xuan ; Xu, Si‐Si ; Ma, Jun ; Sun, Ying</creator><creatorcontrib>Wu, Chen‐Fei ; Lv, Jia‐Wei ; Lin, Li ; Mao, Yan‐Ping ; Deng, Bin ; Zheng, Wei‐Hong ; Wen, Dan‐Wan ; Chen, Yue ; Kou, Jia ; Chen, Fo‐Ping ; Yang, Xing‐Li ; Zheng, Zi‐Qi ; Li, Zhi‐Xuan ; Xu, Si‐Si ; Ma, Jun ; Sun, Ying</creatorcontrib><description>Background
Conditional survival (CS) provides dynamic prognostic estimates by considering the patients existing survival time. Since CS for endemic nasopharyngeal carcinoma (NPC) is lacking, we aimed to assess the CS of endemic NPC and establish a web‐based calculator to predict individualized, conditional site‐specific recurrence risk.
Methods
Using an NPC‐specific database with a big‐data intelligence platform, 10,058 endemic patients with non‐metastatic stage I–IVA NPC receiving intensity‐modulated radiotherapy with or without chemotherapy between April 2009 and December 2015 were investigated. Crude CS estimates of conditional overall survival (COS), conditional disease‐free survival (CDFS), conditional locoregional relapse‐free survival (CLRRFS), conditional distant metastasis‐free survival (CDMFS), and conditional NPC‐specific survival (CNPC‐SS) were calculated. Covariate‐adjusted CS estimates were generated using inverse probability weighting. A prediction model was established using competing risk models and was externally validated with an independent, non‐metastatic stage I–IVA NPC cohort undergoing intensity‐modulated radiotherapy with or without chemotherapy (n = 601) at another institution.
Results
The median follow‐up of the primary cohort was 67.2 months. The 5‐year COS, CDFS, CLRRFS, CDMFS, and CNPC‐SS increased from 86.2%, 78.1%, 89.8%, 87.3%, and 87.6% at diagnosis to 87.3%, 87.7%, 94.4%, 96.0%, and 90.1%, respectively, for an existing survival time of 3 years since diagnosis. Differences in CS estimates between prognostic factor subgroups of each endpoint were noticeable at diagnosis but diminished with time, whereas an ever‐increasing disparity in CS between different age subgroups was observed over time. Notably, the prognoses of patients that were poor at diagnosis improved greatly as patients survived longer. For individualized CS predictions, we developed a web‐based model to estimate the conditional risk of local (C‐index, 0.656), regional (0.667), bone (0.742), lung (0.681), and liver (0.711) recurrence, which significantly outperformed the current staging system (P < 0.001). The performance of this web‐based model was further validated using an external validation cohort (median follow‐up, 61.3 months), with C‐indices of 0.672, 0.736, 0.754, 0.663, and 0.721, respectively.
Conclusions
We characterized the CS of endemic NPC in the largest cohort to date. Moreover, we established a web‐based calculator to predict the CS of site‐specific recurrence, which may help to tailor individualized, risk‐based, time‐adapted follow‐up strategies.</description><identifier>ISSN: 2523-3548</identifier><identifier>EISSN: 2523-3548</identifier><identifier>DOI: 10.1002/cac2.12113</identifier><identifier>PMID: 33270990</identifier><language>eng</language><publisher>United States: John Wiley & Sons, Inc</publisher><subject>big data ; Cancer therapies ; Chemotherapy ; conditional survival ; endemic nasopharyngeal carcinoma ; Epstein-Barr virus ; Estimates ; Liver ; Medical prognosis ; Metastasis ; Original ; Patients ; Radiation therapy ; Throat cancer ; web‐based, individualized prediction model, overall survival, disease‐free survival, locoregional relapse‐free survival, distant metastasis‐free survival, NPC‐specific survival</subject><ispartof>Cancer communications (London, England), 2021-01, Vol.41 (1), p.37-50</ispartof><rights>2020 The Authors. published by John Wiley & Sons Australia, Ltd. on behalf of Sun Yat‐sen University Cancer Center</rights><rights>2020 The Authors. Cancer Communications published by John Wiley & Sons Australia, Ltd. on behalf of Sun Yat-sen University Cancer Center.</rights><rights>2021. This work is published under http://creativecommons.org/licenses/by-nc-nd/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-c4483-ebfc02d19c6405a6e1c75805761a2fb87cdae23b2f5317171f9213c12254ac603</citedby><cites>FETCH-LOGICAL-c4483-ebfc02d19c6405a6e1c75805761a2fb87cdae23b2f5317171f9213c12254ac603</cites><orcidid>0000-0003-1027-071X ; 0000-0002-5888-2929</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/PMC7819551/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7819551/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,1411,11542,27903,27904,45553,45554,46031,46455,53770,53772</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33270990$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wu, Chen‐Fei</creatorcontrib><creatorcontrib>Lv, Jia‐Wei</creatorcontrib><creatorcontrib>Lin, Li</creatorcontrib><creatorcontrib>Mao, Yan‐Ping</creatorcontrib><creatorcontrib>Deng, Bin</creatorcontrib><creatorcontrib>Zheng, Wei‐Hong</creatorcontrib><creatorcontrib>Wen, Dan‐Wan</creatorcontrib><creatorcontrib>Chen, Yue</creatorcontrib><creatorcontrib>Kou, Jia</creatorcontrib><creatorcontrib>Chen, Fo‐Ping</creatorcontrib><creatorcontrib>Yang, Xing‐Li</creatorcontrib><creatorcontrib>Zheng, Zi‐Qi</creatorcontrib><creatorcontrib>Li, Zhi‐Xuan</creatorcontrib><creatorcontrib>Xu, Si‐Si</creatorcontrib><creatorcontrib>Ma, Jun</creatorcontrib><creatorcontrib>Sun, Ying</creatorcontrib><title>Development and validation of a web‐based calculator to predict individualized conditional risk of site‐specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases</title><title>Cancer communications (London, England)</title><addtitle>Cancer Commun (Lond)</addtitle><description>Background
Conditional survival (CS) provides dynamic prognostic estimates by considering the patients existing survival time. Since CS for endemic nasopharyngeal carcinoma (NPC) is lacking, we aimed to assess the CS of endemic NPC and establish a web‐based calculator to predict individualized, conditional site‐specific recurrence risk.
Methods
Using an NPC‐specific database with a big‐data intelligence platform, 10,058 endemic patients with non‐metastatic stage I–IVA NPC receiving intensity‐modulated radiotherapy with or without chemotherapy between April 2009 and December 2015 were investigated. Crude CS estimates of conditional overall survival (COS), conditional disease‐free survival (CDFS), conditional locoregional relapse‐free survival (CLRRFS), conditional distant metastasis‐free survival (CDMFS), and conditional NPC‐specific survival (CNPC‐SS) were calculated. Covariate‐adjusted CS estimates were generated using inverse probability weighting. A prediction model was established using competing risk models and was externally validated with an independent, non‐metastatic stage I–IVA NPC cohort undergoing intensity‐modulated radiotherapy with or without chemotherapy (n = 601) at another institution.
Results
The median follow‐up of the primary cohort was 67.2 months. The 5‐year COS, CDFS, CLRRFS, CDMFS, and CNPC‐SS increased from 86.2%, 78.1%, 89.8%, 87.3%, and 87.6% at diagnosis to 87.3%, 87.7%, 94.4%, 96.0%, and 90.1%, respectively, for an existing survival time of 3 years since diagnosis. Differences in CS estimates between prognostic factor subgroups of each endpoint were noticeable at diagnosis but diminished with time, whereas an ever‐increasing disparity in CS between different age subgroups was observed over time. Notably, the prognoses of patients that were poor at diagnosis improved greatly as patients survived longer. For individualized CS predictions, we developed a web‐based model to estimate the conditional risk of local (C‐index, 0.656), regional (0.667), bone (0.742), lung (0.681), and liver (0.711) recurrence, which significantly outperformed the current staging system (P < 0.001). The performance of this web‐based model was further validated using an external validation cohort (median follow‐up, 61.3 months), with C‐indices of 0.672, 0.736, 0.754, 0.663, and 0.721, respectively.
Conclusions
We characterized the CS of endemic NPC in the largest cohort to date. Moreover, we established a web‐based calculator to predict the CS of site‐specific recurrence, which may help to tailor individualized, risk‐based, time‐adapted follow‐up strategies.</description><subject>big data</subject><subject>Cancer therapies</subject><subject>Chemotherapy</subject><subject>conditional survival</subject><subject>endemic nasopharyngeal carcinoma</subject><subject>Epstein-Barr virus</subject><subject>Estimates</subject><subject>Liver</subject><subject>Medical prognosis</subject><subject>Metastasis</subject><subject>Original</subject><subject>Patients</subject><subject>Radiation therapy</subject><subject>Throat cancer</subject><subject>web‐based, individualized prediction model, overall survival, disease‐free survival, locoregional relapse‐free survival, distant metastasis‐free survival, NPC‐specific survival</subject><issn>2523-3548</issn><issn>2523-3548</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kc1u1DAUhSMEolXphgdAltghpvgnzg8LpNHwK1ViA2vr5vqmdcnYwU6mGlY8Ai_Ey_AkOEypygZ5YVs-5_OxT1E8FvxMcC5fIKA8E1IIda84llqqldJlc__O-qg4TemKcy7api21elgcKSVr3rb8uPj5mnY0hHFLfmLgLdvB4CxMLngWegbsmrpf3390kMgyhAHnAaYQ2RTYGMk6nJjz1u2cnbPx2yIKeb_4YWDRpS8LJrmJMiWNhK53yCLhHCN5pOxmHlIYLyHu_QVlE0JE58MWXrJ1huyTSwtD8OdcN4y8pW1GYE6UHhUPehgSnd7MJ8Xnt28-bd6vzj---7BZn6-wLBu1oq5HLq1osSq5hooE1rrhuq4EyL5rarRAUnWy10rUefStFAqFlLoErLg6KV4duOPcbcli_qwIgxmj2-bYJoAz_554d2kuws7UjWi1Fhnw9AYQw9eZ0mSuwhzz65LJTci6FGVZZdWzgwpjSClSf3uD4GZp2yxtmz9tZ_GTu5lupX-7zQJxEFy7gfb_QZnNeiMP0N8SebnQ</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Wu, Chen‐Fei</creator><creator>Lv, Jia‐Wei</creator><creator>Lin, Li</creator><creator>Mao, Yan‐Ping</creator><creator>Deng, Bin</creator><creator>Zheng, Wei‐Hong</creator><creator>Wen, Dan‐Wan</creator><creator>Chen, Yue</creator><creator>Kou, Jia</creator><creator>Chen, Fo‐Ping</creator><creator>Yang, Xing‐Li</creator><creator>Zheng, Zi‐Qi</creator><creator>Li, Zhi‐Xuan</creator><creator>Xu, Si‐Si</creator><creator>Ma, Jun</creator><creator>Sun, Ying</creator><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>WIN</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</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>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-1027-071X</orcidid><orcidid>https://orcid.org/0000-0002-5888-2929</orcidid></search><sort><creationdate>202101</creationdate><title>Development and validation of a web‐based calculator to predict individualized conditional risk of site‐specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases</title><author>Wu, Chen‐Fei ; Lv, Jia‐Wei ; Lin, Li ; Mao, Yan‐Ping ; Deng, Bin ; Zheng, Wei‐Hong ; Wen, Dan‐Wan ; Chen, Yue ; Kou, Jia ; Chen, Fo‐Ping ; Yang, Xing‐Li ; Zheng, Zi‐Qi ; Li, Zhi‐Xuan ; Xu, Si‐Si ; Ma, Jun ; Sun, Ying</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4483-ebfc02d19c6405a6e1c75805761a2fb87cdae23b2f5317171f9213c12254ac603</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>big data</topic><topic>Cancer therapies</topic><topic>Chemotherapy</topic><topic>conditional survival</topic><topic>endemic nasopharyngeal carcinoma</topic><topic>Epstein-Barr virus</topic><topic>Estimates</topic><topic>Liver</topic><topic>Medical prognosis</topic><topic>Metastasis</topic><topic>Original</topic><topic>Patients</topic><topic>Radiation therapy</topic><topic>Throat cancer</topic><topic>web‐based, individualized prediction model, overall survival, disease‐free survival, locoregional relapse‐free survival, distant metastasis‐free survival, NPC‐specific survival</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Chen‐Fei</creatorcontrib><creatorcontrib>Lv, Jia‐Wei</creatorcontrib><creatorcontrib>Lin, Li</creatorcontrib><creatorcontrib>Mao, Yan‐Ping</creatorcontrib><creatorcontrib>Deng, Bin</creatorcontrib><creatorcontrib>Zheng, Wei‐Hong</creatorcontrib><creatorcontrib>Wen, Dan‐Wan</creatorcontrib><creatorcontrib>Chen, Yue</creatorcontrib><creatorcontrib>Kou, Jia</creatorcontrib><creatorcontrib>Chen, Fo‐Ping</creatorcontrib><creatorcontrib>Yang, Xing‐Li</creatorcontrib><creatorcontrib>Zheng, Zi‐Qi</creatorcontrib><creatorcontrib>Li, Zhi‐Xuan</creatorcontrib><creatorcontrib>Xu, Si‐Si</creatorcontrib><creatorcontrib>Ma, Jun</creatorcontrib><creatorcontrib>Sun, Ying</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library Free Content</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</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>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Publicly Available Content Database</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>PubMed Central (Full Participant titles)</collection><jtitle>Cancer communications (London, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Chen‐Fei</au><au>Lv, Jia‐Wei</au><au>Lin, Li</au><au>Mao, Yan‐Ping</au><au>Deng, Bin</au><au>Zheng, Wei‐Hong</au><au>Wen, Dan‐Wan</au><au>Chen, Yue</au><au>Kou, Jia</au><au>Chen, Fo‐Ping</au><au>Yang, Xing‐Li</au><au>Zheng, Zi‐Qi</au><au>Li, Zhi‐Xuan</au><au>Xu, Si‐Si</au><au>Ma, Jun</au><au>Sun, Ying</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development and validation of a web‐based calculator to predict individualized conditional risk of site‐specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases</atitle><jtitle>Cancer communications (London, England)</jtitle><addtitle>Cancer Commun (Lond)</addtitle><date>2021-01</date><risdate>2021</risdate><volume>41</volume><issue>1</issue><spage>37</spage><epage>50</epage><pages>37-50</pages><issn>2523-3548</issn><eissn>2523-3548</eissn><abstract>Background
Conditional survival (CS) provides dynamic prognostic estimates by considering the patients existing survival time. Since CS for endemic nasopharyngeal carcinoma (NPC) is lacking, we aimed to assess the CS of endemic NPC and establish a web‐based calculator to predict individualized, conditional site‐specific recurrence risk.
Methods
Using an NPC‐specific database with a big‐data intelligence platform, 10,058 endemic patients with non‐metastatic stage I–IVA NPC receiving intensity‐modulated radiotherapy with or without chemotherapy between April 2009 and December 2015 were investigated. Crude CS estimates of conditional overall survival (COS), conditional disease‐free survival (CDFS), conditional locoregional relapse‐free survival (CLRRFS), conditional distant metastasis‐free survival (CDMFS), and conditional NPC‐specific survival (CNPC‐SS) were calculated. Covariate‐adjusted CS estimates were generated using inverse probability weighting. A prediction model was established using competing risk models and was externally validated with an independent, non‐metastatic stage I–IVA NPC cohort undergoing intensity‐modulated radiotherapy with or without chemotherapy (n = 601) at another institution.
Results
The median follow‐up of the primary cohort was 67.2 months. The 5‐year COS, CDFS, CLRRFS, CDMFS, and CNPC‐SS increased from 86.2%, 78.1%, 89.8%, 87.3%, and 87.6% at diagnosis to 87.3%, 87.7%, 94.4%, 96.0%, and 90.1%, respectively, for an existing survival time of 3 years since diagnosis. Differences in CS estimates between prognostic factor subgroups of each endpoint were noticeable at diagnosis but diminished with time, whereas an ever‐increasing disparity in CS between different age subgroups was observed over time. Notably, the prognoses of patients that were poor at diagnosis improved greatly as patients survived longer. For individualized CS predictions, we developed a web‐based model to estimate the conditional risk of local (C‐index, 0.656), regional (0.667), bone (0.742), lung (0.681), and liver (0.711) recurrence, which significantly outperformed the current staging system (P < 0.001). The performance of this web‐based model was further validated using an external validation cohort (median follow‐up, 61.3 months), with C‐indices of 0.672, 0.736, 0.754, 0.663, and 0.721, respectively.
Conclusions
We characterized the CS of endemic NPC in the largest cohort to date. Moreover, we established a web‐based calculator to predict the CS of site‐specific recurrence, which may help to tailor individualized, risk‐based, time‐adapted follow‐up strategies.</abstract><cop>United States</cop><pub>John Wiley & Sons, Inc</pub><pmid>33270990</pmid><doi>10.1002/cac2.12113</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-1027-071X</orcidid><orcidid>https://orcid.org/0000-0002-5888-2929</orcidid><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 2523-3548 |
| ispartof | Cancer communications (London, England), 2021-01, Vol.41 (1), p.37-50 |
| issn | 2523-3548 2523-3548 |
| language | eng |
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| source | Wiley Online Library Journals Frontfile Complete; Wiley Online Library Open Access; DOAJ Directory of Open Access Journals; PubMed Central |
| subjects | big data Cancer therapies Chemotherapy conditional survival endemic nasopharyngeal carcinoma Epstein-Barr virus Estimates Liver Medical prognosis Metastasis Original Patients Radiation therapy Throat cancer web‐based, individualized prediction model, overall survival, disease‐free survival, locoregional relapse‐free survival, distant metastasis‐free survival, NPC‐specific survival |
| title | Development and validation of a web‐based calculator to predict individualized conditional risk of site‐specific recurrence in nasopharyngeal carcinoma: Analysis of 10,058 endemic cases |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T10%3A06%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Development%20and%20validation%20of%20a%20web%E2%80%90based%20calculator%20to%20predict%20individualized%20conditional%20risk%20of%20site%E2%80%90specific%20recurrence%20in%20nasopharyngeal%20carcinoma:%20Analysis%20of%2010,058%20endemic%20cases&rft.jtitle=Cancer%20communications%20(London,%20England)&rft.au=Wu,%20Chen%E2%80%90Fei&rft.date=2021-01&rft.volume=41&rft.issue=1&rft.spage=37&rft.epage=50&rft.pages=37-50&rft.issn=2523-3548&rft.eissn=2523-3548&rft_id=info:doi/10.1002/cac2.12113&rft_dat=%3Cproquest_pubme%3E2702741446%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2702741446&rft_id=info:pmid/33270990&rfr_iscdi=true |