Cargando…

Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study

To investigate the relationship between dosimetric factors, including Lyman normal-tissue complication (NTCP) parameters and radiation-induced lung injury (RILI), in postoperative breast cancer patients treated by intensity modulated radiotherapy (IMRT). 109 breast cancer patients who received IMRT...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Zhi-Rui, Han, Qing, Liang, Shi-Xiong, He, Xiao-Dong, Cao, Nu-Yun, Zi, Ying-Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5464917/
https://www.ncbi.nlm.nih.gov/pubmed/27806340
http://dx.doi.org/10.18632/oncotarget.12979
_version_ 1783242863529689088
author Zhou, Zhi-Rui
Han, Qing
Liang, Shi-Xiong
He, Xiao-Dong
Cao, Nu-Yun
Zi, Ying-Jie
author_facet Zhou, Zhi-Rui
Han, Qing
Liang, Shi-Xiong
He, Xiao-Dong
Cao, Nu-Yun
Zi, Ying-Jie
author_sort Zhou, Zhi-Rui
collection PubMed
description To investigate the relationship between dosimetric factors, including Lyman normal-tissue complication (NTCP) parameters and radiation-induced lung injury (RILI), in postoperative breast cancer patients treated by intensity modulated radiotherapy (IMRT). 109 breast cancer patients who received IMRT between January 2012 and December 2013 were prospectively enrolled. A maximum likelihood analysis yielded the best estimates for Lyman NTCP parameters. Ten patients were diagnosed with RILI (primarily Grade 1 or Grade 2 RILI); the rate of RILI was 9.17% (10/109). Multivariate analysis demonstrated that ipsilateral lung V(20) was an independent predictor (P=0.001) of RILI. Setting V(20)=29.03% as the cut-off value, the prediction of RILI achieved high accuracy (94.5%), with a sensitivity of 80% and specificity of 96%. The NTCP model parameters for 109 patients were m=0.437, n=0.912, and TD(50)(1)=17.211 Gy. The sensitivity of the modified Lyman NTCP model to predict the RILI was 90% (9/10), the specificity was 69.7% (69/99), and the accuracy was 71.6% (78/109). The RILI rate of the NTCP<9.62% in breast cancer patients was 1.43% (1/70), but the RILI rate of the NTCP>9.62% in patients with breast cancer was 23.08% (9/39), (P=0.001). In conclusion, V(20) is an independent predictive factor for RILI in patients with breast cancer treated by IMRT; V(20)=29.03% could be a useful dosimetric parameter to predict the risk of RILI. The Lyman NTCP model parameters of the new value (m=0.437, n=0.912, TD50 (1) =17.211 Gy) can be used as an effective biological index to evaluate the risk of RILI.
format Online
Article
Text
id pubmed-5464917
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Impact Journals LLC
record_format MEDLINE/PubMed
spelling pubmed-54649172017-06-21 Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study Zhou, Zhi-Rui Han, Qing Liang, Shi-Xiong He, Xiao-Dong Cao, Nu-Yun Zi, Ying-Jie Oncotarget Clinical Research Paper To investigate the relationship between dosimetric factors, including Lyman normal-tissue complication (NTCP) parameters and radiation-induced lung injury (RILI), in postoperative breast cancer patients treated by intensity modulated radiotherapy (IMRT). 109 breast cancer patients who received IMRT between January 2012 and December 2013 were prospectively enrolled. A maximum likelihood analysis yielded the best estimates for Lyman NTCP parameters. Ten patients were diagnosed with RILI (primarily Grade 1 or Grade 2 RILI); the rate of RILI was 9.17% (10/109). Multivariate analysis demonstrated that ipsilateral lung V(20) was an independent predictor (P=0.001) of RILI. Setting V(20)=29.03% as the cut-off value, the prediction of RILI achieved high accuracy (94.5%), with a sensitivity of 80% and specificity of 96%. The NTCP model parameters for 109 patients were m=0.437, n=0.912, and TD(50)(1)=17.211 Gy. The sensitivity of the modified Lyman NTCP model to predict the RILI was 90% (9/10), the specificity was 69.7% (69/99), and the accuracy was 71.6% (78/109). The RILI rate of the NTCP<9.62% in breast cancer patients was 1.43% (1/70), but the RILI rate of the NTCP>9.62% in patients with breast cancer was 23.08% (9/39), (P=0.001). In conclusion, V(20) is an independent predictive factor for RILI in patients with breast cancer treated by IMRT; V(20)=29.03% could be a useful dosimetric parameter to predict the risk of RILI. The Lyman NTCP model parameters of the new value (m=0.437, n=0.912, TD50 (1) =17.211 Gy) can be used as an effective biological index to evaluate the risk of RILI. Impact Journals LLC 2016-10-28 /pmc/articles/PMC5464917/ /pubmed/27806340 http://dx.doi.org/10.18632/oncotarget.12979 Text en Copyright: © 2017 Zhou et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Clinical Research Paper
Zhou, Zhi-Rui
Han, Qing
Liang, Shi-Xiong
He, Xiao-Dong
Cao, Nu-Yun
Zi, Ying-Jie
Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study
title Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study
title_full Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study
title_fullStr Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study
title_full_unstemmed Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study
title_short Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study
title_sort dosimetric factors and lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study
topic Clinical Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5464917/
https://www.ncbi.nlm.nih.gov/pubmed/27806340
http://dx.doi.org/10.18632/oncotarget.12979
work_keys_str_mv AT zhouzhirui dosimetricfactorsandlymannormaltissuecomplicationmodellinganalysisforpredictingradiationinducedlunginjuryinpostoperativebreastcancerradiotherapyaprospectivestudy
AT hanqing dosimetricfactorsandlymannormaltissuecomplicationmodellinganalysisforpredictingradiationinducedlunginjuryinpostoperativebreastcancerradiotherapyaprospectivestudy
AT liangshixiong dosimetricfactorsandlymannormaltissuecomplicationmodellinganalysisforpredictingradiationinducedlunginjuryinpostoperativebreastcancerradiotherapyaprospectivestudy
AT hexiaodong dosimetricfactorsandlymannormaltissuecomplicationmodellinganalysisforpredictingradiationinducedlunginjuryinpostoperativebreastcancerradiotherapyaprospectivestudy
AT caonuyun dosimetricfactorsandlymannormaltissuecomplicationmodellinganalysisforpredictingradiationinducedlunginjuryinpostoperativebreastcancerradiotherapyaprospectivestudy
AT ziyingjie dosimetricfactorsandlymannormaltissuecomplicationmodellinganalysisforpredictingradiationinducedlunginjuryinpostoperativebreastcancerradiotherapyaprospectivestudy