This article was originally published here
Oncologist. 2021 Aug 3. doi: 10.1002/onco.13922. Online ahead of print.
BACKGROUND: Several immune checkpoint inhibitors (ICI) are approved for the treatment of advanced urothelial carcinoma (UC). There are limited biomarkers for ICI-treated UC patients. We investigated the association between body composition and clinical outcomes in ICI-treated UC patients.
METHODS: We conducted a retrospective analysis of 70 ICI-treated advanced UC patients at Winship Cancer Institute from 2015-2020. Baseline CT images within 2 months of ICI-initiation were collected at mid-L3 and muscle and fat compartments (subcutaneous, inter-muscular, and visceral) were segmented using SliceOMatic v5.0 (TomoVision). A prognostic body composition risk score (high:0-1, intermediate:2-3, or low-risk:4) was created based on the beta coefficient from the multivariate Cox model (MVA) following best-subset variable selection. Our body composition risk score was: skeletal muscle index (SMI) + 2*attenuated 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 males and the majority received ICI in the second (46%) or third-line (21%) setting. High risk patients had significantly shorter overall survival (OS; HR: 6.72, p<0.001), progression-free survival (PFS; HR: 5.82, p<0.001), and lower chance of clinical benefit (CB; OR: 0.02, p=0.003) compared to the low-risk group in MVA. The C-statistics for our body composition risk group and myosteatosis analyses were higher than BMI for all clinical outcomes.
CONCLUSIONS: Body composition variables such as SMI, SM mean, VFI may be predictive of clinical outcomes in ICI-treated UC patients. Larger, prospective studies are warranted to validate this hypothesis-generating data.
IMPLICATIONS FOR PRACTICE: We developed a prognostic body composition risk scoring system using radiographic biomarkers for bladder cancer patients treated with immunotherapy. We found that the high risk patients had significantly worse clinical outcomes. Notably, our 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 UC patients 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.