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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
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.
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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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