Over the last years has emerged the urgent need for the identification of reliable prognostic biomarkers able to potentially identify metastatic castration-resistant prostate cancer (mCRPC) patients most likely to benefit from Radium-223 (Ra-223) since baseline. In the present monocentric retrospective study, we analyzed the prognostic power of systemic inflammation biomarkers and 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET)-derived parameters and their potential interplay in this clinical setting. The following baseline laboratory parameters were collected in 59 mCRPC patients treated with Ra-223: neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), lymphocyte-to-monocyte ratio (LMR), platelets-to-lymphocyte ratio (PLR), and systemic inflammation index (SII), while maximum Standardized Uptake Value, Metabolic Tumor Volume (MTV), and Total Lesion Glycolysis (TLG) were calculated in the 48 of them submitted to baseline FDG-PET. At the univariate analysis, NLR, dNLR, MTV, and TLG were able to predict the overall survival (OS). However, only NLR and MTV were independent predictors of OS at the multivariate analysis. Additionally, the occurrence of both increased NLR and MTV at baseline identified mCRPC patients at higher risk for lower long-term survival after treatment with Ra-223. In conclusion, the degree of systemic inflammation, the quantification of the metabolically active tumor burden and their combination might represent potentially valuable tools for identifying mCRPC patients who are most likely to benefit from Ra-223. However, further studies are needed to reproduce these findings in larger settings.
Cancers. 2020 Oct 31*** epublish ***
Matteo Bauckneht, Sara Elena Rebuzzi, Alessio Signori, Maria Isabella Donegani, Veronica Murianni, Alberto Miceli, Roberto Borea, Stefano Raffa, Alessandra Damassi, Marta Ponzano, Fabio Catalano, Valentino Martelli, Cecilia Marini, Francesco Boccardo, Silvia Morbelli, Gianmario Sambuceti, Giuseppe Fornarini
Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy., Medical Oncology Unit 1, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy., Department of Health Sciences (DISSAL), University of Genova, Largo R. Benzi 10, 16132 Genova, Italy., Academic Unit of Medical Oncology, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy.