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Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study
BACKGROUND: Immune checkpoint inhibitors (ICIs) have been used to successfully treat primary liver cancer (PLC); however, identifying modifiable patient factors associated with therapeutic benefits is challenging. Obesity is known to be associated with increased survival after ICI treatment; however...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258103/ https://www.ncbi.nlm.nih.gov/pubmed/35794525 http://dx.doi.org/10.1186/s12885-022-09823-7 |
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author | Xiao, Lu-shan Li, Rui-ning Cui, Hao Hong, Chang Huang, Chao-yi Li, Qi-mei Hu, Cheng-yi Dong, Zhong-yi Zhu, Hong-bo Liu, Li |
author_facet | Xiao, Lu-shan Li, Rui-ning Cui, Hao Hong, Chang Huang, Chao-yi Li, Qi-mei Hu, Cheng-yi Dong, Zhong-yi Zhu, Hong-bo Liu, Li |
author_sort | Xiao, Lu-shan |
collection | PubMed |
description | BACKGROUND: Immune checkpoint inhibitors (ICIs) have been used to successfully treat primary liver cancer (PLC); however, identifying modifiable patient factors associated with therapeutic benefits is challenging. Obesity is known to be associated with increased survival after ICI treatment; however, the relationship between body composition (muscle, fat) and outcomes is unclear. This study aimed to evaluate the association between sarcopenia and CT-derived fat content and the prognosis of ICIs for the treatment of PLC. METHODS: In this retrospective cohort study of 172 patients with PLC, we measured the skeletal muscle index (SMI), skeletal muscle density, visceral adipose tissue index, subcutaneous adipose tissue index, total adipose tissue index (TATI), and visceral-to-subcutaneous adipose tissue area ratio using CT. In addition, we analyzed the impact of body composition on the prognosis of the patients. Multivariate Cox regression analysis was used to screen for influencing factors. RESULTS: Among the seven body composition components, low SMI (sarcopenia) and low TATI were significantly associated with poor clinical outcomes. Multivariate analysis revealed that sarcopenia (hazard ratio [HR], 5.39; 95% confidence interval [CI], 1.74–16.74; p = 0.004) was a significant predictor of overall survival (OS). Kaplan–Meier curves showed that sarcopenia and TATI were significant predictors of OS. Body mass index was not associated with survival outcomes. CONCLUSIONS: Sarcopenia and fat tissue content appear to be independently associated with reduced survival rates in patients with PLC treated with ICIs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09823-7. |
format | Online Article Text |
id | pubmed-9258103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-92581032022-07-07 Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study Xiao, Lu-shan Li, Rui-ning Cui, Hao Hong, Chang Huang, Chao-yi Li, Qi-mei Hu, Cheng-yi Dong, Zhong-yi Zhu, Hong-bo Liu, Li BMC Cancer Research BACKGROUND: Immune checkpoint inhibitors (ICIs) have been used to successfully treat primary liver cancer (PLC); however, identifying modifiable patient factors associated with therapeutic benefits is challenging. Obesity is known to be associated with increased survival after ICI treatment; however, the relationship between body composition (muscle, fat) and outcomes is unclear. This study aimed to evaluate the association between sarcopenia and CT-derived fat content and the prognosis of ICIs for the treatment of PLC. METHODS: In this retrospective cohort study of 172 patients with PLC, we measured the skeletal muscle index (SMI), skeletal muscle density, visceral adipose tissue index, subcutaneous adipose tissue index, total adipose tissue index (TATI), and visceral-to-subcutaneous adipose tissue area ratio using CT. In addition, we analyzed the impact of body composition on the prognosis of the patients. Multivariate Cox regression analysis was used to screen for influencing factors. RESULTS: Among the seven body composition components, low SMI (sarcopenia) and low TATI were significantly associated with poor clinical outcomes. Multivariate analysis revealed that sarcopenia (hazard ratio [HR], 5.39; 95% confidence interval [CI], 1.74–16.74; p = 0.004) was a significant predictor of overall survival (OS). Kaplan–Meier curves showed that sarcopenia and TATI were significant predictors of OS. Body mass index was not associated with survival outcomes. CONCLUSIONS: Sarcopenia and fat tissue content appear to be independently associated with reduced survival rates in patients with PLC treated with ICIs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09823-7. BioMed Central 2022-07-06 /pmc/articles/PMC9258103/ /pubmed/35794525 http://dx.doi.org/10.1186/s12885-022-09823-7 Text en © The Author(s) 2022 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 Xiao, Lu-shan Li, Rui-ning Cui, Hao Hong, Chang Huang, Chao-yi Li, Qi-mei Hu, Cheng-yi Dong, Zhong-yi Zhu, Hong-bo Liu, Li Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study |
title | Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study |
title_full | Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study |
title_fullStr | Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study |
title_full_unstemmed | Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study |
title_short | Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study |
title_sort | use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258103/ https://www.ncbi.nlm.nih.gov/pubmed/35794525 http://dx.doi.org/10.1186/s12885-022-09823-7 |
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