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Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases

BACKGROUND: The objective of this study was to construct a risk classification system integrating cell-free Epstein-Barr virus (cfEBV) DNA with T- and N- categories for better prognostication in nasopharyngeal carcinoma (NPC). METHODS: Clinical records of 10,149 biopsy-proven, non-metastatic NPC wer...

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Autores principales: Chen, Fo-Ping, Lin, Li, Liang, Jin-Hui, Tan, Sze Huey, Ong, Enya H.W., Luo, Ying-Shan, Huang, Luo, Sim, Adelene Y.L., Wang, Hai-Tao, Gao, Tian-Sheng, Deng, Bin, Zhou, Guan-Qun, Kou, Jia, Chua, Melvin L.K., Sun, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554575/
https://www.ncbi.nlm.nih.gov/pubmed/34721672
http://dx.doi.org/10.1177/17588359211052417
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author Chen, Fo-Ping
Lin, Li
Liang, Jin-Hui
Tan, Sze Huey
Ong, Enya H.W.
Luo, Ying-Shan
Huang, Luo
Sim, Adelene Y.L.
Wang, Hai-Tao
Gao, Tian-Sheng
Deng, Bin
Zhou, Guan-Qun
Kou, Jia
Chua, Melvin L.K.
Sun, Ying
author_facet Chen, Fo-Ping
Lin, Li
Liang, Jin-Hui
Tan, Sze Huey
Ong, Enya H.W.
Luo, Ying-Shan
Huang, Luo
Sim, Adelene Y.L.
Wang, Hai-Tao
Gao, Tian-Sheng
Deng, Bin
Zhou, Guan-Qun
Kou, Jia
Chua, Melvin L.K.
Sun, Ying
author_sort Chen, Fo-Ping
collection PubMed
description BACKGROUND: The objective of this study was to construct a risk classification system integrating cell-free Epstein-Barr virus (cfEBV) DNA with T- and N- categories for better prognostication in nasopharyngeal carcinoma (NPC). METHODS: Clinical records of 10,149 biopsy-proven, non-metastatic NPC were identified from two cancer centers; this comprised a training (N = 9,259) and two validation cohorts (N = 890; including one randomized controlled phase 3 trial cohort). Adjusted hazard ratio (AHR) method using a two-tiered stratification by cfEBV DNA and TN-categories was applied to generate the risk model. Primary clinical endpoint was overall survival (OS). Performances of the models were compared against American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) 8th edition TNM-stage classification and two published recursive partitioning analysis (RPA) models, and were validated in the validation cohorts. RESULTS: We chose a cfEBV DNA cutoff of ⩾2,000 copies for optimal risk discretization of OS, disease-free survival (DFS) and distant metastasis-free survival (DMFS) in the training cohort. AHR modeling method divided NPC into six risk groups with significantly disparate survival (p  < 0.001 for all): AHR1, T1N0; AHR2A, T1N1/T2-3N0 cfEBV DNA  < 2,000 (EBV(low)); AHR2B, T1N1/T2-3N0 cfEBV DNA ⩾ 2,000 (EBV(high)) and T1-2N2/T2-3N1 EBV(low); AHR3, T1-2N2/T2-3N1 EBV(high) and T3N2/T4N0 EBV(low); AHR4, T3N2/T4 N0-1 EBV(high) and T1-3N3/T4N1-3 EBV(low); AHR5, T1-3N3/T4 N2-3 EBV(high). Our AHR model outperformed the published RPA models and TNM stage with better hazard consistency (1.35 versus 3.98–12.67), hazard discrimination (5.29 versus 6.69–13.35), explained variation (0.248 versus 0.164–0.225), balance (0.385 versus 0.438–0.749) and C-index (0.707 versus 0.662–0.700). In addition, our AHR model was superior to the TNM stage for risk stratification of OS in two validation cohorts (p  < 0.001 for both). CONCLUSION: Herein, we developed and validated a risk classification system that combines the AJCC/UICC 8th edition TN-stage classification and cfEBV DNA for non-metastatic NPC. Our new clinicomolecular model provides improved OS prediction over the current staging system.
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spelling pubmed-85545752021-10-30 Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases Chen, Fo-Ping Lin, Li Liang, Jin-Hui Tan, Sze Huey Ong, Enya H.W. Luo, Ying-Shan Huang, Luo Sim, Adelene Y.L. Wang, Hai-Tao Gao, Tian-Sheng Deng, Bin Zhou, Guan-Qun Kou, Jia Chua, Melvin L.K. Sun, Ying Ther Adv Med Oncol Original Research BACKGROUND: The objective of this study was to construct a risk classification system integrating cell-free Epstein-Barr virus (cfEBV) DNA with T- and N- categories for better prognostication in nasopharyngeal carcinoma (NPC). METHODS: Clinical records of 10,149 biopsy-proven, non-metastatic NPC were identified from two cancer centers; this comprised a training (N = 9,259) and two validation cohorts (N = 890; including one randomized controlled phase 3 trial cohort). Adjusted hazard ratio (AHR) method using a two-tiered stratification by cfEBV DNA and TN-categories was applied to generate the risk model. Primary clinical endpoint was overall survival (OS). Performances of the models were compared against American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) 8th edition TNM-stage classification and two published recursive partitioning analysis (RPA) models, and were validated in the validation cohorts. RESULTS: We chose a cfEBV DNA cutoff of ⩾2,000 copies for optimal risk discretization of OS, disease-free survival (DFS) and distant metastasis-free survival (DMFS) in the training cohort. AHR modeling method divided NPC into six risk groups with significantly disparate survival (p  < 0.001 for all): AHR1, T1N0; AHR2A, T1N1/T2-3N0 cfEBV DNA  < 2,000 (EBV(low)); AHR2B, T1N1/T2-3N0 cfEBV DNA ⩾ 2,000 (EBV(high)) and T1-2N2/T2-3N1 EBV(low); AHR3, T1-2N2/T2-3N1 EBV(high) and T3N2/T4N0 EBV(low); AHR4, T3N2/T4 N0-1 EBV(high) and T1-3N3/T4N1-3 EBV(low); AHR5, T1-3N3/T4 N2-3 EBV(high). Our AHR model outperformed the published RPA models and TNM stage with better hazard consistency (1.35 versus 3.98–12.67), hazard discrimination (5.29 versus 6.69–13.35), explained variation (0.248 versus 0.164–0.225), balance (0.385 versus 0.438–0.749) and C-index (0.707 versus 0.662–0.700). In addition, our AHR model was superior to the TNM stage for risk stratification of OS in two validation cohorts (p  < 0.001 for both). CONCLUSION: Herein, we developed and validated a risk classification system that combines the AJCC/UICC 8th edition TN-stage classification and cfEBV DNA for non-metastatic NPC. Our new clinicomolecular model provides improved OS prediction over the current staging system. SAGE Publications 2021-10-26 /pmc/articles/PMC8554575/ /pubmed/34721672 http://dx.doi.org/10.1177/17588359211052417 Text en © The Author(s), 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Chen, Fo-Ping
Lin, Li
Liang, Jin-Hui
Tan, Sze Huey
Ong, Enya H.W.
Luo, Ying-Shan
Huang, Luo
Sim, Adelene Y.L.
Wang, Hai-Tao
Gao, Tian-Sheng
Deng, Bin
Zhou, Guan-Qun
Kou, Jia
Chua, Melvin L.K.
Sun, Ying
Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases
title Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases
title_full Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases
title_fullStr Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases
title_full_unstemmed Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases
title_short Development of a risk classification system combining TN-categories and circulating EBV DNA for non-metastatic NPC in 10,149 endemic cases
title_sort development of a risk classification system combining tn-categories and circulating ebv dna for non-metastatic npc in 10,149 endemic cases
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554575/
https://www.ncbi.nlm.nih.gov/pubmed/34721672
http://dx.doi.org/10.1177/17588359211052417
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