Cargando…

Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma

PURPOSE: There is no optimal prognostic model for T-cell lymphoblastic lymphoma (T-LBL). Here, we discussed the predictive value of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) measured on (18)F-fluorodeoxyglucose positron emission tomography–computed tomography (PET-CT) in...

Descripción completa

Detalles Bibliográficos
Autores principales: Feng, Xiaoyan, Wen, Xin, Li, Ling, Sun, Zhenchang, Li, Xin, Zhang, Lei, Wu, Jingjing, Fu, Xiaorui, Wang, Xinhua, Yu, Hui, Ma, Xinran, Zhang, Xudong, Xie, Xinli, Han, Xingmin, Zhang, Mingzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Cancer Association 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291183/
https://www.ncbi.nlm.nih.gov/pubmed/33285054
http://dx.doi.org/10.4143/crt.2020.123
_version_ 1783724599154835456
author Feng, Xiaoyan
Wen, Xin
Li, Ling
Sun, Zhenchang
Li, Xin
Zhang, Lei
Wu, Jingjing
Fu, Xiaorui
Wang, Xinhua
Yu, Hui
Ma, Xinran
Zhang, Xudong
Xie, Xinli
Han, Xingmin
Zhang, Mingzhi
author_facet Feng, Xiaoyan
Wen, Xin
Li, Ling
Sun, Zhenchang
Li, Xin
Zhang, Lei
Wu, Jingjing
Fu, Xiaorui
Wang, Xinhua
Yu, Hui
Ma, Xinran
Zhang, Xudong
Xie, Xinli
Han, Xingmin
Zhang, Mingzhi
author_sort Feng, Xiaoyan
collection PubMed
description PURPOSE: There is no optimal prognostic model for T-cell lymphoblastic lymphoma (T-LBL). Here, we discussed the predictive value of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) measured on (18)F-fluorodeoxyglucose positron emission tomography–computed tomography (PET-CT) in T-LBL. MATERIALS AND METHODS: Thirty-seven treatment naïve T-LBL patients with PET-CT scans were enrolled. TMTV was obtained using the 41% maximum standardized uptake value (SUVmax) threshold method, and TLG was measured as metabolic tumor volume multiplied by the mean SUV. Progression-free survival (PFS) and overall survival (OS) were analyzed by Kaplan-Meier curves and compared by the log-rank test. RESULTS: The optimal cutoff values for SUVmax, TMTV, and TLG were 12.7, 302 cm(3), and 890, respectively. A high SUVmax, TMTV, and TLG indicated a shorten PFS and OS. On multivariable analysis, TMTV ≥ 302 cm(3), and central nervous system (CNS) involvement predicted inferior PFS, while high SUVmax, TLG and CNS involvement were associated with worse OS. Subsequently, we generated a risk model comprising high SUVmax, TMTV or TLG and CNS involvement, which stratified the population into three risk groups, which had significantly different median PFS of not reached, 14 months, and 7 months for low-risk group, mediate-risk group, and high-risk group, respectively (p < 0.001). Median OS were not reached, 27 months, and 13 months, respectively (p < 0.001). CONCLUSION: Baseline SUVmax, TMTV, and TLG measured on PET-CT are strong predictors of worse outcome in T-LBL. A risk model integrating these three parameters with CNS involvement identifies patients at high risk of disease progression.
format Online
Article
Text
id pubmed-8291183
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Korean Cancer Association
record_format MEDLINE/PubMed
spelling pubmed-82911832021-08-04 Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma Feng, Xiaoyan Wen, Xin Li, Ling Sun, Zhenchang Li, Xin Zhang, Lei Wu, Jingjing Fu, Xiaorui Wang, Xinhua Yu, Hui Ma, Xinran Zhang, Xudong Xie, Xinli Han, Xingmin Zhang, Mingzhi Cancer Res Treat Original Article PURPOSE: There is no optimal prognostic model for T-cell lymphoblastic lymphoma (T-LBL). Here, we discussed the predictive value of total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG) measured on (18)F-fluorodeoxyglucose positron emission tomography–computed tomography (PET-CT) in T-LBL. MATERIALS AND METHODS: Thirty-seven treatment naïve T-LBL patients with PET-CT scans were enrolled. TMTV was obtained using the 41% maximum standardized uptake value (SUVmax) threshold method, and TLG was measured as metabolic tumor volume multiplied by the mean SUV. Progression-free survival (PFS) and overall survival (OS) were analyzed by Kaplan-Meier curves and compared by the log-rank test. RESULTS: The optimal cutoff values for SUVmax, TMTV, and TLG were 12.7, 302 cm(3), and 890, respectively. A high SUVmax, TMTV, and TLG indicated a shorten PFS and OS. On multivariable analysis, TMTV ≥ 302 cm(3), and central nervous system (CNS) involvement predicted inferior PFS, while high SUVmax, TLG and CNS involvement were associated with worse OS. Subsequently, we generated a risk model comprising high SUVmax, TMTV or TLG and CNS involvement, which stratified the population into three risk groups, which had significantly different median PFS of not reached, 14 months, and 7 months for low-risk group, mediate-risk group, and high-risk group, respectively (p < 0.001). Median OS were not reached, 27 months, and 13 months, respectively (p < 0.001). CONCLUSION: Baseline SUVmax, TMTV, and TLG measured on PET-CT are strong predictors of worse outcome in T-LBL. A risk model integrating these three parameters with CNS involvement identifies patients at high risk of disease progression. Korean Cancer Association 2021-07 2020-12-02 /pmc/articles/PMC8291183/ /pubmed/33285054 http://dx.doi.org/10.4143/crt.2020.123 Text en Copyright © 2021 by the Korean Cancer Association https://creativecommons.org/licenses/by-nc/4.0/This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Feng, Xiaoyan
Wen, Xin
Li, Ling
Sun, Zhenchang
Li, Xin
Zhang, Lei
Wu, Jingjing
Fu, Xiaorui
Wang, Xinhua
Yu, Hui
Ma, Xinran
Zhang, Xudong
Xie, Xinli
Han, Xingmin
Zhang, Mingzhi
Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma
title Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma
title_full Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma
title_fullStr Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma
title_full_unstemmed Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma
title_short Baseline Total Metabolic Tumor Volume and Total Lesion Glycolysis Measured on (18)F-FDG PET-CT Predict Outcomes in T-Cell Lymphoblastic Lymphoma
title_sort baseline total metabolic tumor volume and total lesion glycolysis measured on (18)f-fdg pet-ct predict outcomes in t-cell lymphoblastic lymphoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291183/
https://www.ncbi.nlm.nih.gov/pubmed/33285054
http://dx.doi.org/10.4143/crt.2020.123
work_keys_str_mv AT fengxiaoyan baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT wenxin baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT liling baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT sunzhenchang baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT lixin baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT zhanglei baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT wujingjing baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT fuxiaorui baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT wangxinhua baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT yuhui baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT maxinran baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT zhangxudong baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT xiexinli baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT hanxingmin baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma
AT zhangmingzhi baselinetotalmetabolictumorvolumeandtotallesionglycolysismeasuredon18ffdgpetctpredictoutcomesintcelllymphoblasticlymphoma