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Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study
BACKGROUND: Accurate assessment of the nature of enlarged retropharyngeal lymph nodes (RLN) of nasopharyngeal carcinoma (NPC) patients after radiotherapy is related to selecting appropriate treatments and avoiding unnecessary therapy. This study aimed to develop a non-invasive and effective model fo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9752871/ https://www.ncbi.nlm.nih.gov/pubmed/36530897 http://dx.doi.org/10.3389/fmed.2022.996127 |
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author | Mao, Minjie Wang, Xueping Seeruttun, Sharvesh Raj Chi, Peidong Huang, Kewei Liu, Wen Tan, Wencheng |
author_facet | Mao, Minjie Wang, Xueping Seeruttun, Sharvesh Raj Chi, Peidong Huang, Kewei Liu, Wen Tan, Wencheng |
author_sort | Mao, Minjie |
collection | PubMed |
description | BACKGROUND: Accurate assessment of the nature of enlarged retropharyngeal lymph nodes (RLN) of nasopharyngeal carcinoma (NPC) patients after radiotherapy is related to selecting appropriate treatments and avoiding unnecessary therapy. This study aimed to develop a non-invasive and effective model for predicting the recurrence of RLN (RRLN) in NPC. MATERIALS AND METHODS: The data of post-radiotherapy NPC patients (N = 76) with abnormal enlargement of RLN who underwent endonasopharyngeal ultrasound-guided fine-needle aspirations (EPUS-FNA) were examined. They were randomly divided into a discovery (n = 53) and validation (n = 23) cohort. Univariate logistic regression was used to assess the association between variables (magnetic resonance imaging characteristics, EBV DNA) and RRLN. Multiple logistic regression was used to construct a prediction model. The accuracy of the model was assessed by discrimination and calibration, and decision curves were used to assess the clinical reliability of the model for the identification of high risk RLNs for possible recurrence. RESULTS: Abnormal enhancement, minimum axis diameter (MAD) and EBV-DNA were identified as independent risk factors for RRLN and could stratify NPC patients into three risk groups. The probability of RRLN in the low-, medium-, and high-risk groups were 37.5, 82.4, and 100%, respectively. The AUC of the final predictive model was 0.882 (95% CI: 0.782–0.982) in the discovery cohort and 0.926 (95% CI, 0.827–1.000) in the validation cohort, demonstrating good clinical accuracy for predicting the RRLN of NPC patients. The favorable performance of the model was confirmed by the calibration plot and decision curve analysis. CONCLUSION: The nomogram model constructed in the study could be reliable in predicting the risk of RRLN after radiotherapy for NPC patients. |
format | Online Article Text |
id | pubmed-9752871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97528712022-12-16 Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study Mao, Minjie Wang, Xueping Seeruttun, Sharvesh Raj Chi, Peidong Huang, Kewei Liu, Wen Tan, Wencheng Front Med (Lausanne) Medicine BACKGROUND: Accurate assessment of the nature of enlarged retropharyngeal lymph nodes (RLN) of nasopharyngeal carcinoma (NPC) patients after radiotherapy is related to selecting appropriate treatments and avoiding unnecessary therapy. This study aimed to develop a non-invasive and effective model for predicting the recurrence of RLN (RRLN) in NPC. MATERIALS AND METHODS: The data of post-radiotherapy NPC patients (N = 76) with abnormal enlargement of RLN who underwent endonasopharyngeal ultrasound-guided fine-needle aspirations (EPUS-FNA) were examined. They were randomly divided into a discovery (n = 53) and validation (n = 23) cohort. Univariate logistic regression was used to assess the association between variables (magnetic resonance imaging characteristics, EBV DNA) and RRLN. Multiple logistic regression was used to construct a prediction model. The accuracy of the model was assessed by discrimination and calibration, and decision curves were used to assess the clinical reliability of the model for the identification of high risk RLNs for possible recurrence. RESULTS: Abnormal enhancement, minimum axis diameter (MAD) and EBV-DNA were identified as independent risk factors for RRLN and could stratify NPC patients into three risk groups. The probability of RRLN in the low-, medium-, and high-risk groups were 37.5, 82.4, and 100%, respectively. The AUC of the final predictive model was 0.882 (95% CI: 0.782–0.982) in the discovery cohort and 0.926 (95% CI, 0.827–1.000) in the validation cohort, demonstrating good clinical accuracy for predicting the RRLN of NPC patients. The favorable performance of the model was confirmed by the calibration plot and decision curve analysis. CONCLUSION: The nomogram model constructed in the study could be reliable in predicting the risk of RRLN after radiotherapy for NPC patients. Frontiers Media S.A. 2022-12-01 /pmc/articles/PMC9752871/ /pubmed/36530897 http://dx.doi.org/10.3389/fmed.2022.996127 Text en Copyright © 2022 Mao, Wang, Seeruttun, Chi, Huang, Liu and Tan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Mao, Minjie Wang, Xueping Seeruttun, Sharvesh Raj Chi, Peidong Huang, Kewei Liu, Wen Tan, Wencheng Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study |
title | Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study |
title_full | Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study |
title_fullStr | Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study |
title_full_unstemmed | Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study |
title_short | Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study |
title_sort | recurrence risk stratification based on epstein–barr virus dna to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: a model-histopathologic correlation study |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9752871/ https://www.ncbi.nlm.nih.gov/pubmed/36530897 http://dx.doi.org/10.3389/fmed.2022.996127 |
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