Abstract
To validate the association between body composition and all-cause mortality in men treated with radiation therapy for localized prostate cancer (PCa). Secondarily, to integrate body composition as a factor to help classify patients by risk of all-cause mortality.All participants of NRG/RTOG 9406 and NRG/RTOG 0126 with archived computed tomography that extended cranially to include the L4-L5 interface were included. Muscle mass and muscle density were estimated by measuring the cross-sectional area and average attenuation of the paired psoas muscles on a single slice at the level of L4-L5. Bone density was estimated by measuring the average attenuation of the vertebral body cancellous bone on a single slice at mid-L5. Adipose tissue density was estimated by measuring the average attenuation of the subcutaneous adipose tissue on a single slice at L4-L5. Survival analyses, including Cox proportional hazards models, were performed to assess the relationship between body composition variables and all-cause mortality. Recursive partitioning (RPA) was utilized to create a classification tree to classify NRG/RTOG 0126 participants by risk of death, and the discriminant ability of the classification model was validated using the NRG/RTOG 9406 data set.Data from 2,066 men was included in this study (864 from NRG/RTOG 9406 and 1,202 from NRG/RTOG 0126). A total of 648 men died in the follow-up period and 51 (7.9%) were due to PCa. Psoas area, psoas density, and vertebral body density were individually associated with overall survival. In the final multivariable model, psoas area, comorbidity score, and age were associated with overall survival (Table). The RPA yielded a classification tree with 4 prognostic groups determined by age, comorbidity, and psoas cross-sectional area. When the RPA classification was applied to the NRG/RTOG 9406 validation set the discriminant ability was preserved (P < 0.001 groupwise log-rank).The results of this study strongly support that body composition is related to all-cause mortality in men with localized PCa, with most deaths due to causes other than PCa. The inclusion of psoas cross-sectional area in the RPA classification tree suggests that body composition provides additive information to age and comorbidity status for mortality prediction. This study also confirms the feasibility of performing body composition analysis using archived CT scans using NRG Oncology clinical trial data sets. These methods can be applied to other NRG Oncology data sets to further explore how body composition is related to patient outcomes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Radiation Oncology*Biology*Physics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.