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Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade

BACKGROUND: Systemic Immune-inflammation Index (SII) and body composition parameters are easily assessed, and can predict overall survival (OS) in various cancers, allowing early intervention. This study aimed to assess the correlation between CT-derived body composition parameters and SII and OS in...

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Autores principales: He, Meng, Chen, Zi-Fan, Zhang, Li, Gao, Xiangyu, Chong, Xiaoyi, Li, Hao-shen, Shen, Lin, Ji, Jiafu, Zhang, Xiaotian, Dong, Bin, Li, Zi-Yu, Lei, Tang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10314655/
https://www.ncbi.nlm.nih.gov/pubmed/37349127
http://dx.doi.org/10.1136/jitc-2023-007054
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author He, Meng
Chen, Zi-Fan
Zhang, Li
Gao, Xiangyu
Chong, Xiaoyi
Li, Hao-shen
Shen, Lin
Ji, Jiafu
Zhang, Xiaotian
Dong, Bin
Li, Zi-Yu
Lei, Tang
author_facet He, Meng
Chen, Zi-Fan
Zhang, Li
Gao, Xiangyu
Chong, Xiaoyi
Li, Hao-shen
Shen, Lin
Ji, Jiafu
Zhang, Xiaotian
Dong, Bin
Li, Zi-Yu
Lei, Tang
author_sort He, Meng
collection PubMed
description BACKGROUND: Systemic Immune-inflammation Index (SII) and body composition parameters are easily assessed, and can predict overall survival (OS) in various cancers, allowing early intervention. This study aimed to assess the correlation between CT-derived body composition parameters and SII and OS in patients with advanced gastric cancer receiving dual programmed death-1 (PD-1) and human epidermal growth factor receptor 2 (HER2) blockade. MATERIALS AND METHODS: This retrospective study enrolled patients with advanced gastric cancer treated with dual PD-1 and HER2 blockade from March 2019 to June 2022. We developed a deep learning model based on nnU-Net to automatically segment skeletal muscle, subcutaneous fat and visceral fat at the third lumbar level, and calculated the corresponding Skeletal Muscle Index, skeletal muscle density, subcutaneous fat area (SFA) and visceral fat area. SII was computed using the formula that total peripheral platelet count×neutrophil/lymphocyte ratio. Univariate and multivariate Cox regression analysis were used to determine the associations between SII, body composition parameters and OS. RESULTS: The automatic segmentation deep learning model was developed to efficiently segment body composition in 158 patients (0.23 s/image). Multivariate Cox analysis revealed that high SII (HR=2.49 (95% CI 1.54 to 4.01), p<0.001) and high SFA (HR=0.42 (95% CI 0.24 to 0.73), p=0.002) were independently associated with OS, whereas sarcopenia was not an independent prognostic factor for OS (HR=1.41 (95% CI 0.86 to 2.31), p=0.173). In further analysis, patients with high SII and low SFA had worse long-term prognosis compared with those with low SII and high SFA (HR=8.19 (95% CI 3.91 to 17.16), p<0.001). CONCLUSION: Pretreatment SFA and SII were significantly associated with OS in patients with advanced gastric cancer. A comprehensive analysis of SII and SFA may improve the prognostic stratification of patients with gastric cancer receiving dual PD-1 and HER2 blockade.
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spelling pubmed-103146552023-07-02 Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade He, Meng Chen, Zi-Fan Zhang, Li Gao, Xiangyu Chong, Xiaoyi Li, Hao-shen Shen, Lin Ji, Jiafu Zhang, Xiaotian Dong, Bin Li, Zi-Yu Lei, Tang J Immunother Cancer Immunotherapy Biomarkers BACKGROUND: Systemic Immune-inflammation Index (SII) and body composition parameters are easily assessed, and can predict overall survival (OS) in various cancers, allowing early intervention. This study aimed to assess the correlation between CT-derived body composition parameters and SII and OS in patients with advanced gastric cancer receiving dual programmed death-1 (PD-1) and human epidermal growth factor receptor 2 (HER2) blockade. MATERIALS AND METHODS: This retrospective study enrolled patients with advanced gastric cancer treated with dual PD-1 and HER2 blockade from March 2019 to June 2022. We developed a deep learning model based on nnU-Net to automatically segment skeletal muscle, subcutaneous fat and visceral fat at the third lumbar level, and calculated the corresponding Skeletal Muscle Index, skeletal muscle density, subcutaneous fat area (SFA) and visceral fat area. SII was computed using the formula that total peripheral platelet count×neutrophil/lymphocyte ratio. Univariate and multivariate Cox regression analysis were used to determine the associations between SII, body composition parameters and OS. RESULTS: The automatic segmentation deep learning model was developed to efficiently segment body composition in 158 patients (0.23 s/image). Multivariate Cox analysis revealed that high SII (HR=2.49 (95% CI 1.54 to 4.01), p<0.001) and high SFA (HR=0.42 (95% CI 0.24 to 0.73), p=0.002) were independently associated with OS, whereas sarcopenia was not an independent prognostic factor for OS (HR=1.41 (95% CI 0.86 to 2.31), p=0.173). In further analysis, patients with high SII and low SFA had worse long-term prognosis compared with those with low SII and high SFA (HR=8.19 (95% CI 3.91 to 17.16), p<0.001). CONCLUSION: Pretreatment SFA and SII were significantly associated with OS in patients with advanced gastric cancer. A comprehensive analysis of SII and SFA may improve the prognostic stratification of patients with gastric cancer receiving dual PD-1 and HER2 blockade. BMJ Publishing Group 2023-06-22 /pmc/articles/PMC10314655/ /pubmed/37349127 http://dx.doi.org/10.1136/jitc-2023-007054 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Immunotherapy Biomarkers
He, Meng
Chen, Zi-Fan
Zhang, Li
Gao, Xiangyu
Chong, Xiaoyi
Li, Hao-shen
Shen, Lin
Ji, Jiafu
Zhang, Xiaotian
Dong, Bin
Li, Zi-Yu
Lei, Tang
Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade
title Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade
title_full Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade
title_fullStr Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade
title_full_unstemmed Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade
title_short Associations of subcutaneous fat area and Systemic Immune-inflammation Index with survival in patients with advanced gastric cancer receiving dual PD-1 and HER2 blockade
title_sort associations of subcutaneous fat area and systemic immune-inflammation index with survival in patients with advanced gastric cancer receiving dual pd-1 and her2 blockade
topic Immunotherapy Biomarkers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10314655/
https://www.ncbi.nlm.nih.gov/pubmed/37349127
http://dx.doi.org/10.1136/jitc-2023-007054
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