Abdominal Fat Characteristics and Mortality in Rectal Cancer: A Retrospective Study

Pellegrini, Massimo; Besutti, Giulia; Ottone, Marta; Canovi, Simone; Bonelli, Efrem; Venturelli, Francesco; Farì, Roberto; Damato, Angela; Bonelli, Candida; Pinto, Carmine; Ligabue, Guido; Pattacini, Pierpaolo; Rossi, Paolo Giorgi; Ghoch, Marwan El

doi:10.3390/nu15020374

Cited by 6 publications

(1 citation statement)

References 31 publications

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“…Furthermore, the SHAP plot indicates a negative correlation between SATD and OS rate. Similar to our ndings, Pellegrini et al [47] found increased SATD is associated with poorer cancer-speci c survival in rectal cancer; Patrick T. Bradshaw et al [48] found that elevated SAT was associated with worse survival among the women with non-metastatic breast cancer. The associated underlying mechanism may be attributed to the shrinkage, brosis, or in ammation of adipose tissue [49,50].…”

Section: Discussionsupporting

confidence: 90%

Integration of body composition data in developing a Random Survival Forest model for the Prognosis of Locally Advanced Cervical Cancer patients treated with definitive Chemoradiotherapy

Xu,

Liu,

Dou

et al. 2024

Preprint

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Objective This study aims to integrate body composition data in developing a random survival forest (RSF) model for predicting overall survival (OS) in locally advanced cervical cancer (LACC) patients treated with definitive chemoradiotherapy (CRT). Methods: 374 LACC patients from the First Affiliated Hospital of Soochow University were enrolled in the study. Eleven features were selected using least absolute shrinkage and selection operator (LASSO) regression in constructing the RSF model. The Optuna algorithm was applied to optimize the hyperparameters. The constructed RSF model was evaluated based on the C-index, AUC, Brier scores, and decision curve analysis (DCA). Furthermore, we compared the RSF model with the traditional Cox regression and deep learning (Deepsurv) models. Results: The C-index of the RSF model in the test set was 0.809 (95%CI: 0.708–0.911), superior to the Cox regression (0.739, 95%CI: 0.627–0.852) and Deepsurv (0.774, 95%CI: 0.656–0.892) models. The Brier scores for 1-, 3-, and 5-year OS in the test set (0.044, 0.069, and 0.096) and DCA demonstrated that the RSF model has good calibration and clinical benefits. Furthermore, skeletal muscle density (SMD) ranked top in visualization using SHapley Additive exPlanations (SHAP) plotting. Lastly, we applied the RSF model in risk stratification, which showed a favorable performance. Conclusions: The RSF model, which is based on body composition characteristics, performs well in predicting OS in LACC patients treated with definitive CRT. Moreover, the RSF model demonstrates value in risk stratification.

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Section: Discussionsupporting

confidence: 90%

Integration of body composition data in developing a Random Survival Forest model for the Prognosis of Locally Advanced Cervical Cancer patients treated with definitive Chemoradiotherapy

Xu,

Liu,

Dou

et al. 2024

Preprint

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Morphomics, Survival, and Metabolites in Patients With Metastatic Pancreatic Cancer

Gunchick,

Brown,

Liu

et al. 2024

JAMA Netw Open

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ImportanceAssociations of body mass index (BMI) with survival in pancreatic ductal adenocarcinoma (PDA) have substantial variability in literature, potentially due to heterogeneous patient populations and retrospective analyses. Additionally, BMI may inadequately describe body composition (ie, morphomics; including subcutaneous and visceral fats, muscle, and fascia), which might have independent biological roles and associations with survival.ObjectiveTo study the associations of BMI and morphomics with survival and metabolomics in metastatic PDA.Design, Setting, and ParticipantsThis cohort study prospectively collected patient data, imaging, and serum on the phase 3 trial (Avenger500), which investigated the efficacy and safety of 5-fluorouracil, leucovorin, oxaliplatin, and irinotecan (FOLFIRINOX) versus modified FOLFIRINOX plus devimistat. The randomized trial accrued 528 patients with chemotherapy-naive, metastatic PDA from Europe, Israel, Korea, and the US between 2018 and 2020. In the present study, per-protocol patients with L1 to L4, T10 to T12 vertebral levels were evaluated. Data analysis occurred from January 2023 to April 2024.ExposurePatient data were collected by clinical staff. Morphomics were analyzed from baseline imaging. Metabolites were extracted from baseline serum.Main Outcome and MeasuresA multifaceted statistical approach evaluated associations of BMI and morphomics with progression-free survival (PFS) and overall survival (OS). Associations of morphomics with metabolites were also studied.ResultsOf the 528 initial patients, 476 (median [IQR] age, 63 [56-68] years; 280 male [58.8%]; median [IQR] BMI, 25.0 [22.1-25.9]) were evaluable for the present study. BMI (obese [≥30] compared with normal [18.5-24.9]) was not associated with OS (hazard ratio [HR], 0.90; 95% CI, 0.67-1.22; P for trend = .33). More subcutaneous fat was associated with longer OS (HR, 0.62; 95% CI, 0.41-0.94; P for trend = .02). Higher visceral fat density was associated with shorter PFS (HR, 1.74; 95% CI, 1.23-2.48; P for trend = .002) and OS (HR, 1.50; 95% CI, 1.12-2.00; P for trend = .008). A higher muscle-to-fascia ratio was associated with longer PFS (HR, 0.58; 95% CI, 0.40-0.84; P for trend = .005) and OS (HR, 0.56; 95% CI, 0.41-0.75; P for trend = 1.7 × 10−4). Subcutaneous fat was positively associated with long-chain fatty acid metabolism including pristanic acid, decanoylcarnitine, decenoylcarnitine, and octanoylcarnitine. Muscle-to-fascia was positively associated with metabolites including acetylcarnosine (β = 0.34; 95% CI, 0.21-0.47; P = 1.27 × 10−6).Conclusions and RelevanceIn cohort study of patients with metastatic PDA, BMI was not associated with survival. Higher visceral fat density, subcutaneous fat area, and muscle-to-fascia ratio were associated with survival independent of BMI. The latter 2 were associated with higher levels of animal product metabolism. These findings could represent novel focuses for prognostication and intervention to improve survival of patients with PDA.

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Characteristics of Abdominal Fat Based on CT Measurements to Predict Early Recurrence After Initial Surgery of NMIBC in Stage Ta/T1

Yu,

Xu,

Jiang

et al. 2024

Clinical Genitourinary Cancer

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Abdominal Fat Characteristics and Mortality in Rectal Cancer: A Retrospective Study

Cited by 6 publications

References 31 publications

Integration of body composition data in developing a Random Survival Forest model for the Prognosis of Locally Advanced Cervical Cancer patients treated with definitive Chemoradiotherapy

Integration of body composition data in developing a Random Survival Forest model for the Prognosis of Locally Advanced Cervical Cancer patients treated with definitive Chemoradiotherapy

Morphomics, Survival, and Metabolites in Patients With Metastatic Pancreatic Cancer

Characteristics of Abdominal Fat Based on CT Measurements to Predict Early Recurrence After Initial Surgery of NMIBC in Stage Ta/T1

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