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Author Notes:

Mehmet Asim Bilen, M.D., Department of Hematology and Medical Oncology and Winship Cancer Institute, Emory University, 1365B Clifton Road NE Suite B400, Office 4212, Atlanta, 30322, Atlanta, Georgia, USA. Telephone: 404‐778‐3693; e‐mail: mbilen@emory.edu

Conception/design: Dylan J. Martini, Subir Goyal, Yuan Liu, Mehmet Asim Bilen Provision of study material or patients: Deepak Ravindranathan, Jacqueline T. Brown, Lauren Yantorni, Greta Anne Russler, Sarah Caulfield, Jamie M. Goldman, Bassel Nazha, Shreyas Subhash Joshi, Haydn T. Kissick, Kenneth E. Ogan, Wayne B. Harris, Omer Kucuk, Bradley C. Carthon, Viraj A. Master, Mehmet Asim Bilen Collection and/or assembly of data: Dylan J Martini, Julie M. Shabto, T. Anders Olsen, Sean T. Evans, Benjamin L. Magod Data analysis and interpretation: Dylan J. Martini, Subir Goyal, Yuan Liu, Mehmet Asim Bilen Manuscript writing: Dylan J. Martini, Subir Goyal, Yuan Liu, Mehmet Asim Bilen Final approval of manuscript: Dylan J. Martini, Julie M. Shabto, Subir Goyal, Yuan Liu, T. Anders Olsen, Sean T. Evans, Benjamin L. Magod, Deepak Ravindranathan, Jacqueline T. Brown, Lauren Yantorni, Greta Anne Russler, Sarah Caulfield, Jamie M. Goldman, Bassel Nazha, Shreyas Subhash Joshi, Haydn T. Kissick, Kenneth E. Ogan, Wayne B. Harris, Omer Kucuk, Bradley C. Carthon, Viraj A. Master, Mehmet Asim Bilen

The data reported in this article were presented as a poster presentation at the 2020 SITC Annual Meeting.

Bradley C. Carthon: Astellas Medivation, Pfizer, Blue Earth Diagnostics (C/A), Bristol‐Myers Squibb (Travel); Mehmet Asim Bilen: Exelixis, Bayer, Bristol‐Myers Squibb, Eisai, Pfizer, AstraZeneca, Janssen, Calithera Biosciences, Genomic Health, Nektar, Sanofi (C/A), Xencor, Bayer, Bristol‐Myers Squibb, Genentech/Roche, Seattle Genetics, Incyte, Nektar, AstraZeneca, Tricon Pharmaceuticals, Genome & Company, AAA, Peloton Therapeutics, Pfizer (RF [institution]). The other authors indicated no financial relationships.

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Research Funding:

Research reported in this publication was supported in part by the Biostatistics Shared Resource of Winship Cancer Institute of Emory University and the National Institutes of Health/National Cancer Institute under award number P30CA138292. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Oncology
  • Body composition
  • Urothelial carcinoma
  • Immune checkpoint inhibitors
  • Sarcopenia
  • Adiposity
  • Myosteatosis
  • Prognostic model
  • Biomarkers
  • THERAPY
  • MULTICENTER
  • SARCOPENIA
  • PARADOX
  • OBESITY

Body Composition as an Independent Predictive and Prognostic Biomarker in Advanced Urothelial Carcinoma Patients Treated with Immune Checkpoint Inhibitors

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Journal Title:

ONCOLOGIST

Volume:

Volume 26, Number 12

Publisher:

, Pages 1017-1025

Type of Work:

Article | Final Publisher PDF

Abstract:

Background: Several immune checkpoint inhibitors (ICIs) are approved for the treatment of advanced urothelial carcinoma (UC). There are limited biomarkers for ICI-treated patients with UC. We investigated the association between body composition and clinical outcomes in ICI-treated UC patients. Materials and Methods: We conducted a retrospective analysis of 70 ICI-treated patients with advanced UC at Winship Cancer Institute from 2015 to 2020. Baseline computed tomography images within 2 months of ICI initiation were collected at mid-L3 and muscle and fat compartments (subcutaneous, intermuscular, and visceral) were segmented using SliceOMatic v5.0 (TomoVision, Magog, Canada). A prognostic body composition risk score (high: 0–1, intermediate: 2–3, or low-risk: 4) was created based on the β coefficient from the multivariate Cox model (MVA) following best-subset variable selection. Our body composition risk score was skeletal muscle index (SMI) + 2 × attenuated skeletal muscle (SM) mean + visceral fat index (VFI). Concordance statistics (C-statistics) were used to quantify the discriminatory magnitude of the predictive model. Results: Most patients (70%) were men and the majority received ICIs in the second- (46%) or third-line (21%) setting. High-risk patients had significantly shorter overall survival (OS; hazard ratio [HR], 6.72; p <.001), progression-free survival (HR, 5.82; p <.001), and lower chance of clinical benefit (odds ratio [OR], 0.02; p =.003) compared with the low-risk group in MVA. The C-statistics for our body composition risk group and myosteatosis analyses were higher than body mass index for all clinical outcomes. Conclusion: Body composition variables such as SMI, SM mean, and VFI may be prognostic and predictive of clinical outcomes in ICI-treated patients with UC. Larger, prospective studies are warranted to validate this hypothesis-generating data. Implications for Practice: This study developed a prognostic body composition risk scoring system using radiographic biomarkers for patients with bladder cancer treated with immunotherapy. The study found that the high-risk patients had significantly worse clinical outcomes. Notably, the study's model was better at predicting outcomes than body mass index. Importantly, these results suggest that radiographic measures of body composition should be considered for inclusion in updated prognostic models for patients with urothelial carcinoma treated with immunotherapy. These findings are useful for practicing oncologists in the academic or community setting, particularly given that baseline imaging is routine for patients starting on treatment with immunotherapy.

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© 2021 AlphaMed Press.

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