Body Composition to Define Prognosis of Cancers Treated by Anti-Angiogenic Drugs

Decazes, Pierre; Prévia, Antoine De; Mottay, Léo; Lawrance, Littisha; Belkouchi, Younes; Benatsou, Baya; Albigès, Laurence; Balleyguier, Corinne; Véra, Pierre; Lassau, Nathalie

doi:10.3390/diagnostics13020205

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…This evidence allow us to believe that BIA is an effective diagnostic and prognostic tool [ 43 ]. On the other hand, it is also reported that there is a close relationship between osteoporosis and coronary artery calcification, indicating osteoporosis as a predisposing factor for cardiovascular disease [ 44 ]. In this context, the role of BIA clustering results becomes important as a prognostic factor in many different diseases.…”

Section: Discussionmentioning

confidence: 99%

The Role of BIA Analysis in Osteoporosis Risk Development: Hierarchical Clustering Approach

et al. 2023

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Osteoporosis is a common musculoskeletal disorder among the elderly and a chronic condition which, like many other chronic conditions, requires long-term clinical management. It is caused by many factors, including lifestyle and obesity. Bioelectrical impedance analysis (BIA) is a method to estimate body composition based on a weak electric current flow through the body. The measured voltage is used to calculate body bioelectrical impedance, divided into resistance and reactance, which can be used to estimate body parameters such as total body water (TBW), fat-free mass (FFM), fat mass (FM), and muscle mass (MM). This study aims to find the tendency of osteoporosis in obese subjects, presenting a method based on hierarchical clustering, which, using BIA parameters, can group patients who show homogeneous characteristics. Grouping similar patients into clusters can be helpful in the field of medicine to identify disorders, pathologies, or more generally, characteristics of significant importance. Another added value of the clustering process is the possibility to define cluster prototypes, i.e., imaginary patients who represent models of “states”, which can be used together with clustering results to identify subjects with similar characteristics in a classification context. The results show that hierarchical clustering is a method that can be used to provide the detection of states and, consequently, supply a more personalized medicine approach. In addition, this method allowed us to elect BIA as a potential prognostic and diagnostic instrument in osteoporosis risk development.

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Section: Discussionmentioning

confidence: 99%

The Role of BIA Analysis in Osteoporosis Risk Development: Hierarchical Clustering Approach

et al. 2023

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Trifluridine/tipiracil + oxaliplatin ± nivolumab vs FOLFOX ± nivolumab in HER2 negative advanced oesogastric adenocarcinoma: The PRODIGE73-UCGI40-LOGICAN trial

Botsen,

Chabaud,

Perrier

et al. 2024

Digestive and Liver Disease

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Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer

Decazes,

Ammari,

Belkouchi

et al. 2023

J Immunother Cancer

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BackgroundOur aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy.MethodsWe 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.ResultsIn 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/m2), low FBM (<3.26 kg/m2), low VFM (<0.91 kg/m2), low MBM (<5.85 kg/m2) and low BMI (<24.97 kg/m2). 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/m2) and MBM (<6.86 kg/m2) (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).Conclusions3D 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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Body Composition to Define Prognosis of Cancers Treated by Anti-Angiogenic Drugs

Cited by 3 publications

References 30 publications

The Role of BIA Analysis in Osteoporosis Risk Development: Hierarchical Clustering Approach

The Role of BIA Analysis in Osteoporosis Risk Development: Hierarchical Clustering Approach

Trifluridine/tipiracil + oxaliplatin ± nivolumab vs FOLFOX ± nivolumab in HER2 negative advanced oesogastric adenocarcinoma: The PRODIGE73-UCGI40-LOGICAN trial

Synergic prognostic value of 3D CT scan subcutaneous fat and muscle masses for immunotherapy-treated cancer

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