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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.
- Source :
- Radiology & Oncology; Mar2020, Vol. 54 Issue 1, p40-47, 8p
- Publication Year :
- 2020
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13182099
- Volume :
- 54
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Radiology & Oncology
- Publication Type :
- Academic Journal
- Accession number :
- 142385796
- Full Text :
- https://doi.org/10.2478/raon-2019-0058