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Scintigraphic Load of Bone Disease Evaluated by DASciS Software as a Survival Predictor in Metastatic Castration-resistant Prostate Cancer Patients Candidates to 223RaCl Treatment

BACKGROUND: Aim of our study was to assess the load of bone disease at starting and during Ra-223 treatment as an overall survival (OS) predictor in metastatic castration-resistant prostate cancer (mCRPC) patients. Bone scan index (BSI) is defined as the percentage of total amount of bone metastasis...

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Detalles Bibliográficos
Autores principales: Frantellizzi, Viviana, Pani, Arianna, Ippoliti, Maria Dea, Farcomeni, Alessio, Aloise, Irvin, Colosi, Mirco, Polito, Claudia, Pani, Roberto, Vincentis, Giuseppe De
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087429/
https://www.ncbi.nlm.nih.gov/pubmed/31855572
http://dx.doi.org/10.2478/raon-2019-0058
Descripción
Sumario:BACKGROUND: Aim of our study was to assess the load of bone disease at starting and during Ra-223 treatment as an overall survival (OS) predictor in metastatic castration-resistant prostate cancer (mCRPC) patients. Bone scan index (BSI) is defined as the percentage of total amount of bone metastasis on whole-body scintigraphic images. We present a specific software (DASciS) developed by an engineering team of “Sapienza” University of Rome for BSI calculation. PATIENTS AND METHODS: 127 mCRPC patients bone scan images were processed with DASciS software, and BSI was tested as OS predictor. RESULTS: 546 bone scans were analyzed revealing that the extension of disease is a predictor of OS (0–3% = 28 months of median survival (MoMS]; 3%–5% = 11 MoMS, > 5% = 5 MoMS). BSI has been analyzed as a single parameter for OS, determining an 88% AUC. Moreover, the composition between the BSI and the 3-PS (3-variable prognostic score) determines a remarkable improvement of the AUC (91%), defining these two parameters as the best OS predictors. CONCLUSIONS: This study suggests that OS is inversely correlated with the load of bone disease in mCRPC Ra-223-treated subjects. DASciS software appears a promising tool in identifying mCRPC patients that more likely take advantage from Ra-223 treatment. BSI is proposed as a predictive variable for OS and included to a multidimensional clinical evaluation permits to approach the patients’ enrollment in a rational way, allowing to enhance the treatment effectiveness together with cost optimization.