Body Composition Variables as Radiographic Biomarkers of Clinical Outcomes in Metastatic Renal Cell Carcinoma Patients Receiving Immune Checkpoint Inhibitors

• DOI: 10.3389/fonc.2021.707050
• Publication Date: 2021-07-09T09:31:16Z
• Authors: Dylan J. Martini; T. Anders Olsen; Subir Goyal; Yuan Liu; Sean T. Evans; Benjamin Magod; Jacqueline T. Brown; Lauren Yantorni; Greta Anne Russler; Sarah Caulfield; Jamie M. Goldman; Bassel Nazha; Haydn T. Kissick; Wayne B. Harris; Omer Kucuk; Bradley C. Carthon; Viraj A. Master; Mehmet Asim Bilen
• Keywords: Concordance; Kidney cancer

Background Immune checkpoint inhibitors (ICI) have revolutionized the treatment of metastatic renal cell carcinoma (mRCC). Biomarkers for mRCC patients treated with ICI are limited, and body composition is underutilized in mRCC. We investigated association between clinical outcomes ICI-treated patients. Methods performed a retrospective analysis 79 at Winship Cancer Institute from 2015-2020. Baseline CT images were collected mid-L3 segmented using SliceOMatic v5.0 (TomoVision). Density skeletal muscle (SM), subcutaneous fat, inter-muscular visceral fat measured converted to indices by dividing height(m) 2 (SMI, SFI, IFI, VFI, respectively). Total index (TFI) was defined as sum VFI. Patients characterized high versus low each variable gender-specific optimal cuts overall survival (OS) primary outcome. A prognostic risk score created based on beta coefficient multivariable Cox model after best subset selection. Body calculated IFI + 2*SM mean SFI classified poor (0-1), intermediate (2), or favorable (3-4). Kaplan-Meier method Log-rank test used estimate OS PFS compare groups. Concordance statistics (C-statistics) measure discriminatory magnitude model. Results Most male (73%) most received first (35%) second-line (51%) therapy. The poor-risk had significantly shorter (HR: 6.37, p<0.001), 4.19, lower chance CB (OR: 0.23, p=0.044) compared analysis. TFI 2.72, p=0.002), 1.91, p=0.025), 0.25, p=0.008) C-statistics higher groups (all ≥ 0.598) IMDC BMI. Conclusions Risk stratification variables SM mean, may be predictive ICI. Larger, prospective studies warranted validate this hypothesis-generating data.