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Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer
BACKGROUND: Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy. METHODS: We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-check...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10496660/ https://www.ncbi.nlm.nih.gov/pubmed/37678919 http://dx.doi.org/10.1136/jitc-2023-007315 |
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author | Decazes, Pierre Ammari, Samy Belkouchi, Younes Mottay, Léo Lawrance, Littisha de Prévia, Antoine Talbot, Hugues Farhane, Siham Cournède, Paul-Henry Marabelle, Aurelien Guisier, Florian Planchard, David Ibrahim, Tony Robert, Caroline Barlesi, Fabrice Vera, Pierre Lassau, Nathalie |
author_facet | Decazes, Pierre Ammari, Samy Belkouchi, Younes Mottay, Léo Lawrance, Littisha de Prévia, Antoine Talbot, Hugues Farhane, Siham Cournède, Paul-Henry Marabelle, Aurelien Guisier, Florian Planchard, David Ibrahim, Tony Robert, Caroline Barlesi, Fabrice Vera, Pierre Lassau, Nathalie |
author_sort | Decazes, Pierre |
collection | PubMed |
description | BACKGROUND: Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy. METHODS: We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-checkpoint-inhibitor having a pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort of 55 patients with NSCLC was used. Anthropometric parameters were measured three-dimensionally (3D) by a deep learning software (Anthropometer3DNet) allowing an automatic multislice measurement of lean body mass, fat body mass (FBM), muscle body mass (MBM), visceral fat mass (VFM) and sub-cutaneous fat mass (SFM). Body mass index (BMI) and weight loss (WL) were also retrieved. Receiver operator characteristic (ROC) curve analysis was performed and overall survival was calculated using Kaplan-Meier (KM) curve and Cox regression analysis. RESULTS: In the overall cohort, 1-year mortality rate was 0.496 (95% CI: 0.457 to 0.537) for 309 events and 5-year mortality rate was 0.196 (95% CI: 0.165 to 0.233) for 477 events. In the univariate Kaplan-Meier analysis, prognosis was worse (p<0.001) for patients with low SFM (<3.95 kg/m(2)), low FBM (<3.26 kg/m(2)), low VFM (<0.91 kg/m(2)), low MBM (<5.85 kg/m(2)) and low BMI (<24.97 kg/m(2)). The same parameters were significant in the Cox univariate analysis (p<0.001) and, in the multivariate stepwise Cox analysis, the significant parameters were MBM (p<0.0001), SFM (0.013) and WL (0.0003). In subanalyses according to the type of cancer, all body composition parameters were statistically significant for NSCLC in ROC, KM and Cox univariate analysis while, for melanoma, none of them, except MBM, was statistically significant. In multivariate Cox analysis, the significant parameters for NSCLC were MBM (HR=0.81, p=0.0002), SFM (HR=0.94, p=0.02) and WL (HR=1.06, p=0.004). For NSCLC, a KM analysis combining SFM and MBM was able to separate the population in three categories with the worse prognostic for the patients with both low SFM (<5.22 kg/m(2)) and MBM (<6.86 kg/m(2)) (p<0001). On the external validation cohort, combination of low SFM and low MBM was pejorative with 63% of mortality at 1 year versus 25% (p=0.0029). CONCLUSIONS: 3D measured low SFM and MBM are significant prognosis factors of NSCLC treated by immune checkpoint inhibitors and can be combined to improve the prognostic value. |
format | Online Article Text |
id | pubmed-10496660 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-104966602023-09-13 Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer Decazes, Pierre Ammari, Samy Belkouchi, Younes Mottay, Léo Lawrance, Littisha de Prévia, Antoine Talbot, Hugues Farhane, Siham Cournède, Paul-Henry Marabelle, Aurelien Guisier, Florian Planchard, David Ibrahim, Tony Robert, Caroline Barlesi, Fabrice Vera, Pierre Lassau, Nathalie J Immunother Cancer Immunotherapy Biomarkers BACKGROUND: Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy. METHODS: We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318) or melanoma (n=305) treated by an immune-checkpoint-inhibitor having a pretreatment (thorax-)abdomen-pelvis CT scan. An external validation cohort of 55 patients with NSCLC was used. Anthropometric parameters were measured three-dimensionally (3D) by a deep learning software (Anthropometer3DNet) allowing an automatic multislice measurement of lean body mass, fat body mass (FBM), muscle body mass (MBM), visceral fat mass (VFM) and sub-cutaneous fat mass (SFM). Body mass index (BMI) and weight loss (WL) were also retrieved. Receiver operator characteristic (ROC) curve analysis was performed and overall survival was calculated using Kaplan-Meier (KM) curve and Cox regression analysis. RESULTS: In the overall cohort, 1-year mortality rate was 0.496 (95% CI: 0.457 to 0.537) for 309 events and 5-year mortality rate was 0.196 (95% CI: 0.165 to 0.233) for 477 events. In the univariate Kaplan-Meier analysis, prognosis was worse (p<0.001) for patients with low SFM (<3.95 kg/m(2)), low FBM (<3.26 kg/m(2)), low VFM (<0.91 kg/m(2)), low MBM (<5.85 kg/m(2)) and low BMI (<24.97 kg/m(2)). The same parameters were significant in the Cox univariate analysis (p<0.001) and, in the multivariate stepwise Cox analysis, the significant parameters were MBM (p<0.0001), SFM (0.013) and WL (0.0003). In subanalyses according to the type of cancer, all body composition parameters were statistically significant for NSCLC in ROC, KM and Cox univariate analysis while, for melanoma, none of them, except MBM, was statistically significant. In multivariate Cox analysis, the significant parameters for NSCLC were MBM (HR=0.81, p=0.0002), SFM (HR=0.94, p=0.02) and WL (HR=1.06, p=0.004). For NSCLC, a KM analysis combining SFM and MBM was able to separate the population in three categories with the worse prognostic for the patients with both low SFM (<5.22 kg/m(2)) and MBM (<6.86 kg/m(2)) (p<0001). On the external validation cohort, combination of low SFM and low MBM was pejorative with 63% of mortality at 1 year versus 25% (p=0.0029). CONCLUSIONS: 3D measured low SFM and MBM are significant prognosis factors of NSCLC treated by immune checkpoint inhibitors and can be combined to improve the prognostic value. BMJ Publishing Group 2023-09-07 /pmc/articles/PMC10496660/ /pubmed/37678919 http://dx.doi.org/10.1136/jitc-2023-007315 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 Decazes, Pierre Ammari, Samy Belkouchi, Younes Mottay, Léo Lawrance, Littisha de Prévia, Antoine Talbot, Hugues Farhane, Siham Cournède, Paul-Henry Marabelle, Aurelien Guisier, Florian Planchard, David Ibrahim, Tony Robert, Caroline Barlesi, Fabrice Vera, Pierre Lassau, Nathalie Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer |
title | Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer |
title_full | Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer |
title_fullStr | Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer |
title_full_unstemmed | Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer |
title_short | Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer |
title_sort | synergic prognostic value of 3d ct scan subcutaneous fat and muscle masses for immunotherapy-treated cancer |
topic | Immunotherapy Biomarkers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10496660/ https://www.ncbi.nlm.nih.gov/pubmed/37678919 http://dx.doi.org/10.1136/jitc-2023-007315 |
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