Prognostic factors influencing prostate cancer-specific survival in non-castrate patients with metastatic prostate cancer

The Prostate ◽  
2014 ◽  
Vol 74 (3) ◽  
pp. 297-305 ◽  
Author(s):  
Piet Ost ◽  
Karel Decaestecker ◽  
Bieke Lambert ◽  
Valérie Fonteyne ◽  
Louke Delrue ◽  
...  
2019 ◽  
Vol 133 ◽  
pp. S855
Author(s):  
R. Pearson ◽  
X. Jiang ◽  
S. Atkinson ◽  
S. Cumming ◽  
A. Burns ◽  
...  

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e17507-e17507
Author(s):  
Vipal P. Durkal ◽  
Nicholas George Nickols ◽  
Matthew Rettig

e17507 Background: Prostate cancer commonly metastasizes to the bone and is associated with reduced survival, pathologic fractures and bone pain. The assessment of bone lesions is made with the technetium Tc99m(99mTc) bone scan, which relies on the subjective interpretation of radiologists and has a wide interobserver variability. There is an unmet need for a more objective and quantifiable measurement tool. Progenics Pharmaceuticals has introduced an automated bone scan index (aBSI), which employs artificial intelligence to quantify skeletal tumor burden. The automated bone scan index has been prospectively validated and is reproducible in large Phase III studies. The aBSI was validated by our study in the Veteran population at the West LA VA Medical Center. Methods: The first positive technetium 99 Tc99m bone scans of veterans diagnosed with metastatic, castration-sensitive prostate cancer were evaluated. Since 2011, a total of 107 evaluable patient bone scans were studied (n = 107). Patients with visceral metastases were excluded to evaluate only those with skeletal metastases. An automated bone scan index (aBSI) was generated for each scan using the Progenics Pharmaceuticals’ artificial intelligence platform. Multivariate analysis of aBSI with overall survival, prostate cancer specific survival, time from diagnosis to first positive bone scan, age at diagnosis, ethnicity, and Gleason score was assessed. Results: The study demonstrated a wide range of aBSI values (Range 0-16.84). Values calculated above the Median aBSI value (1.0) were prognostic for Overall Survival (p = 0.0009) and Prostate Cancer-Specific Survival (p = 0.0011). Patients in the highest quartile of aBSI values (range 5.2-16.84) showed a statistically significant Prostate Cancer-Specific Mortality (p = 0.0300) when compared to the lowest two quartiles (Range 0-1.07). The time from diagnosis to the first positive Tc99m bone scan statistically correlated with aBSI values (p = 0.0016). Multivariate analysis using Cox regression was utilized in the final statistical analysis of prostate cancer-specific mortality and overall survival. Conclusions: The automated Bone Scan Index provides a quantifiable and validated artificial intelligence biomarker to address an unmet need among metastatic prostate cancer patients. This tool was validated among Veterans, a pertinent population that is commonly affected by metastatic prostate cancer.


2020 ◽  
Vol 10 (07) ◽  
pp. 225-232
Author(s):  
Modou Ndiaye ◽  
Ousmane Sow ◽  
Babacar Sine ◽  
Omar Gaye ◽  
Alioune Sarr ◽  
...  

BMC Urology ◽  
2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Atsushi Tomioka ◽  
Nobumichi Tanaka ◽  
Motokiyo Yoshikawa ◽  
Makito Miyake ◽  
Satoshi Anai ◽  
...  

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