45 Body composition as a predictive and prognostic biomarker in advanced urothelial carcinoma (UC) patients treated with immune checkpoint inhibitors (ICI). (9th November 2020) - Martini, Dylan; Shabto, Julie; Goyal, Subir; Liu, Yuan; Anders Olsen, T; Evans, Sean; Magod, Benjamin; Ravindranathan, Deepak; Brown, Jacqueline; Yantorni, Lauren; Russler, Greta; Caulfield, Sarah; et al.
Abstract : Background: Several immune checkpoint inhibitors (ICI) have been approved for the treatment of advanced urothelial carcinoma (UC). There are limited predictive biomarkers for UC patients treated with ICI. In this study, we investigated the association between body composition and clinical outcomes in ICI-treated advanced UC patients. Methods: We conducted a retrospective analysis of 70 ICI-treated advanced UC patients at Winship Cancer Institute from 2015–2020. Inclusion criteria was available computed tomography (CT) scans within 2 months of ICI-initiation. Baseline CT images were collected at mid-L3 and muscle and fat compartments were segmented using SliceOMatic v5.0 (TomoVision). The density of subcutaneous fat, inter-muscular fat, visceral fat, and skeletal muscle (SM) were measured and converted to indices by dividing by height(m)2 (SFI, IFI, VFI and SMI, respectively). Attenuated SM mean (Hounsfield Units) was also collected. Myosteatosis was calculated by IFI/SMI*100%. Gender-specific optimal cuts were used to dichotomize patients as high or low for each variable using OS as the primary outcome. A prognostic body composition risk score was created based on the beta coefficient from the multivariable Cox model (MVA) following best-subset variable selection. Our body composite risk score was SMI + 2*SM mean + VFI and patients were categorized as high (0–1), intermediate (2–3), or low-risk (4). Comparison of OS and PFS between the risk groups was performed via Kaplan-Meier method and Log-rank test. Concordance statistics (C-statistics) were used to quantify the discriminatory magnitude of the predictive model. Results: Most patients (70%) were male and more than one-quarter (26%) had an ECOG PS ≥ 2. The majority received ICI in the second (46%) or third-line (21%) setting. Body composite poor-risk patients had significantly shorter OS (HR: 6.18, p<0.001), PFS (HR: 5.91, p<0.001), and lower chance at CB (OR: 0.02, p=0.004) compared to low-risk group in MVA (table 1). Patients with low myosteatosis had significantly longer OS (HR: 0.35, p=0.002), PFS (HR: 0.32, p<0.001), and higher chance at CB (OR: 20.47, p=0.034) compared to high myosteatosis patients in MVA. The C-statistics for our body composition risk group and myosteatosis analyses were higher than BMI for all clinical outcomes (table 2). High and intermediate-risk patients had significantly shorter OS and PFS compared to low-risk patients per Kaplan-Meier estimation (figure 1). Conclusions: Body composition variables such as SMI, SM mean, VFI and myosteatosis may be predictive of clinical outcomes in ICI-treated advanced UC patients. Larger, prospective studies are warranted to validate this hypothesis-generating data. Acknowledgements: Research reported in this publication was supported in part by the Biostatistics and Bioinformatics Shared Resource of Winship Cancer Institute of Emory University and NIH/NCI 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. Trial Registration: Not applicable Ethics Approval: This retrospective study was approved by the Emory University Institutional Review Board. Consent: Not applicable References: Not applicable