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A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy
BACKGROUND: To develop a risk model based on dosimetric metrics to predict local recurrence in nasopharyngeal carcinoma (NPC) patients treated with intensive modulated radiation therapy (IMRT). METHODS: 493 consecutive patients were included, among whom 44 were with local recurrence. One-to-two prop...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461883/ https://www.ncbi.nlm.nih.gov/pubmed/34556123 http://dx.doi.org/10.1186/s13014-021-01911-5 |
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author | Liao, Wenjun He, Jinlan Liu, Zijian Tian, Maolang Yang, Jiangping Han, Jiaqi Xiao, Jianghong |
author_facet | Liao, Wenjun He, Jinlan Liu, Zijian Tian, Maolang Yang, Jiangping Han, Jiaqi Xiao, Jianghong |
author_sort | Liao, Wenjun |
collection | PubMed |
description | BACKGROUND: To develop a risk model based on dosimetric metrics to predict local recurrence in nasopharyngeal carcinoma (NPC) patients treated with intensive modulated radiation therapy (IMRT). METHODS: 493 consecutive patients were included, among whom 44 were with local recurrence. One-to-two propensity score matching (PSM) was used to balance variables between recurrent and non-recurrent groups. Dosimetric metrics were extracted, and critical dosimetric predictors of local recurrence were identified by Cox regression model. Moreover, recurrent sites and patterns were examined by transferring the recurrent tumor to the pretreatment planning computed tomography. RESULTS: After PSM, 44 recurrent and 88 non-recurrent patients were used for dosimetric analysis. The univariate analysis showed that eight dosimetric metrics and homogeneity index were significantly associated with local recurrence. The risk model integrating D(5) and D(95) achieved a C-index of 0.706 for predicting 3-year local recurrence free survival (LRFS). By grouping patients using median value of risk score, patients with risk score ˃ 0.885 had significantly lower 3-year LRFS (66.2% vs. 86.4%, p = 0.023). As for recurrent features, the proportion of relapse in nasopharynx cavity, clivus, and pterygopalatine fossa was 61.4%, 52.3%, and 40.9%, respectively; and in field, marginal, and outside field recurrence constituted 68.2%, 20.5% and 11.3% of total recurrence, respectively. CONCLUSIONS: The current study developed a novel risk model that could effectively predict the LRFS in NPC patients. Additionally, nasopharynx cavity, clivus, and pterygopalatine fossa were common recurrent sites and in field recurrence remained the major failure pattern of NPC in the IMRT era. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13014-021-01911-5. |
format | Online Article Text |
id | pubmed-8461883 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84618832021-09-24 A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy Liao, Wenjun He, Jinlan Liu, Zijian Tian, Maolang Yang, Jiangping Han, Jiaqi Xiao, Jianghong Radiat Oncol Research BACKGROUND: To develop a risk model based on dosimetric metrics to predict local recurrence in nasopharyngeal carcinoma (NPC) patients treated with intensive modulated radiation therapy (IMRT). METHODS: 493 consecutive patients were included, among whom 44 were with local recurrence. One-to-two propensity score matching (PSM) was used to balance variables between recurrent and non-recurrent groups. Dosimetric metrics were extracted, and critical dosimetric predictors of local recurrence were identified by Cox regression model. Moreover, recurrent sites and patterns were examined by transferring the recurrent tumor to the pretreatment planning computed tomography. RESULTS: After PSM, 44 recurrent and 88 non-recurrent patients were used for dosimetric analysis. The univariate analysis showed that eight dosimetric metrics and homogeneity index were significantly associated with local recurrence. The risk model integrating D(5) and D(95) achieved a C-index of 0.706 for predicting 3-year local recurrence free survival (LRFS). By grouping patients using median value of risk score, patients with risk score ˃ 0.885 had significantly lower 3-year LRFS (66.2% vs. 86.4%, p = 0.023). As for recurrent features, the proportion of relapse in nasopharynx cavity, clivus, and pterygopalatine fossa was 61.4%, 52.3%, and 40.9%, respectively; and in field, marginal, and outside field recurrence constituted 68.2%, 20.5% and 11.3% of total recurrence, respectively. CONCLUSIONS: The current study developed a novel risk model that could effectively predict the LRFS in NPC patients. Additionally, nasopharynx cavity, clivus, and pterygopalatine fossa were common recurrent sites and in field recurrence remained the major failure pattern of NPC in the IMRT era. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13014-021-01911-5. BioMed Central 2021-09-23 /pmc/articles/PMC8461883/ /pubmed/34556123 http://dx.doi.org/10.1186/s13014-021-01911-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Liao, Wenjun He, Jinlan Liu, Zijian Tian, Maolang Yang, Jiangping Han, Jiaqi Xiao, Jianghong A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy |
title | A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy |
title_full | A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy |
title_fullStr | A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy |
title_full_unstemmed | A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy |
title_short | A novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy |
title_sort | novel dosimetric metrics-based risk model to predict local recurrence in nasopharyngeal carcinoma patients treated with intensity-modulated radiation therapy |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8461883/ https://www.ncbi.nlm.nih.gov/pubmed/34556123 http://dx.doi.org/10.1186/s13014-021-01911-5 |
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