Investigation of the relationship between functional parameters in Fluor-18 fluorodeoxyglucose positron emission tomography/computed tomography and sarcopenia with treatment response and survival in patients undergoing immunotherapy

Immunotherapy (IT) is an important treatment option that prolongs survival in advanced malignancies such as Malignant Melanoma, Non–small Cell Lung Cancer, and Renal Cell Carcinoma. However, treatment response and survival outcomes vary widely among patients, making prognostication challenging. Our study aimed to evaluate the role of functional parameters obtained from pre-treatment, treatment-response, and follow-up F-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (F-18 FDG PET/CT) imaging, together with the sarcopenia and clinical parameters, in predicting treatment response and survival in patients receiving IT. A total of 121 patients who received IT between 2016 and 2024 and had available pre-treatment F-18 FDG PET/CT scans were retrospectively analyzed. Demographic characteristics, clinical and laboratory data, F-18 FDG PET/CT parameters obtained before and during treatment, nutritional status, and survival outcomes were recorded. Sarcopenia was defined based on the Skeletal Muscle Index (SMI) measured at the level of the third lumbar vertebra. Relationships between parameters and survival outcomes were analyzed using SPSS v25.0. High pre-treatment metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were found to have an adverse impact on overall survival (OS). Moreover, reductions in MTV and TLG on treatment-response and follow-up F-18 FDG PET/CT scans were associated with improved survival. Sarcopenia, albumin levels, performance status and several other factors were also significantly related to shorter OS. In patients receiving IT, volumetric F-18 FDG PET/CT parameters (MTV and TLG), sarcopenia, and selected clinical variables were identified as important prognostic markers for predicting response and survival. Combined use of these parameters may contribute to more accurate risk stratification and better identification of candidates for IT.