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.

Frantellizzi, V., Pani, A., Ippoliti, M.d., Farcomeni, A., Aloise, I., Colosi, M., et al. (2019). Scintigraphic load of bone disease evaluated by DASciS software as a survival predictor in metastatic castration-resistant prostate cancer patients candidates to 223RaCl treatment. RADIOLOGY AND ONCOLOGY, 54(1), 40-47 [10.2478/raon-2019-0058].

Scintigraphic load of bone disease evaluated by DASciS software as a survival predictor in metastatic castration-resistant prostate cancer patients candidates to 223RaCl treatment

Farcomeni, Alessio;
2019-01-01

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.
2019
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore SECS-S/01 - STATISTICA
English
DASciS software
bone disease
bone scan index
mCRPC
overall survival
radium223 dichloride
Frantellizzi, V., Pani, A., Ippoliti, M.d., Farcomeni, A., Aloise, I., Colosi, M., et al. (2019). Scintigraphic load of bone disease evaluated by DASciS software as a survival predictor in metastatic castration-resistant prostate cancer patients candidates to 223RaCl treatment. RADIOLOGY AND ONCOLOGY, 54(1), 40-47 [10.2478/raon-2019-0058].
Frantellizzi, V; Pani, A; Ippoliti, Md; Farcomeni, A; Aloise, I; Colosi, M; Polito, C; Pani, R; Vincentis, Gd
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/253089
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