LAUSR

Simple Summary Sarcoma is a rare cancer originating in soft tissue or bone. Prognostic models are used to modify therapy and improve survival. The present study aimed to evaluate if the combination of PET parameters and circulating biomarkers can improve the prognostic accuracy. When PET parameters were added to the existing models, the prognostic value increased in all models. A new prognostic model (SBSpib), including the biomarkers albumin, lymphocytes, and one PET parameter, metabolic tumor volume, was developed. SBSpib separates patients into four different groups, where the chance of survival increases with decreasing scores. Overall, combining PET parameters and circulating biomarkers improves the prognostic value. However, SBSpib must be validated before implementation. Abstract Sarcomas are rare and have a high mortality rate. Further prognostic classification, with readily available parameters, is warranted, and several studies have examined circulating biomarkers and PET parameters separately. This single-site, retrospective study aimed to examine the prognostic values of several scoring systems in combination with PET parameters. We included 148 patients with sarcoma, who were treated and scanned at Aarhus University Hospital from 1 January 2016 to 31 December 2019. The Akaike information criterion and Harrell’s concordance index were used to evaluate whether the PET parameters added prognostic information to existing prognostic models using circulating biomarkers. Of the PET parameters, metabolic tumor volume (MTV) performed best, and when combined with the existing prognostic models, the prognostic value improved in all models. Backward stepwise selection was used to create a new model, SBSpib, which included albumin, lymphocytes, and one PET parameter, MTV. It has scores ranging from zero to three and increasing hazard ratios; HR = 4.83 (1.02–22.75) for group one, HR = 7.40 (1.6–33.42) for group two, and HR = 17.32 (3.45–86.93) for group three. Consequently, implementing PET parameters in prognostic models improved the prognostic value. SBSpib is a new prognostic model that includes both circulating biomarkers and PET parameters; however, validation in another sarcoma cohort is warranted.