Abstract
(1) Background: Prostate cancer risk classifiers have been used for predicting surgical and radiation therapy outcomes; however, a classifier for predicting biochemical recurrence (BCR) in patients undergoing stereotactic body radiation therapy (SBRT) is not available. We attempted to develop a model that creates a risk classifier to predict BCR in patients considering SBRT. (2) Methods: We studied the outcomes of 809 patients treated with SBRT between August 2007 and November 2016. We used Cox regression analysis with time to BCR as the outcome to develop a model that calculates a prostate clinical outlook (PCO) score based on age at diagnosis, clinical-radiological staging, and a modified risk level. We then created the PCO classifier application, which uses the model we created to categorize patients into risk groups based on multiple factors. We assessed the concordance index (c-index) to determine the accuracy of the PCO classifier application and compared the results to the D’Amico and Kattan nomogram classifications. (3) Results: The calculated PCO scores ranged from 0 to 156 points. The PCO classifier application categorized patients into three risk-groups, with 5-year BCR-free survival rates of 98.3% for low risk (n = 137), 95.4% for intermediate risk (n = 570), and 86.4% for high risk (n = 102). We demonstrated the improved prognostic power of the PCO classifier application, with a c-index of 0.75 (training set) and 0.67 (validation set); the c-index of the Kattan nomogram was 0.62 and 0.63, respectively, and that of the D’Amico classifier was 0.64 and 0.64, respectively. (4) Conclusions: The PCO classifier application is a predictive tool for employing readily available clinical parameters to stratify prostate cancer patients and to predict the probability of BCR after SBRT.
Highlights
As the most common solid malignancy diagnosed in men, prostate cancer was the second most common cause of cancer death in 2016 [1,2]
We have proposed a prostate clinical outlook visualization system (PCOVS) based on the PCO classifier application [13]
Using Cox regression analysis, with time to biochemical recurrence (BCR) as the outcome for prostate cancer patients who underwent Stereotactic body radiation therapy (SBRT), a model was developed that calculates a PCO score based on (1) age at diagnosis, (2) clinical-radiological staging, and (3) the modified risk level based on a combination of pretreatment prostate specific antigen (PSA) and the Gleason score
Summary
As the most common solid malignancy diagnosed in men, prostate cancer was the second most common cause of cancer death in 2016 [1,2]. SBRT is a safe and effective treatment for clinically localized prostate cancer. There are diverse benefits: no pain; minimal invasiveness; little or no recovery time; only five treatments instead of 40, the latter being typical of other forms of radiation therapy; few or reduced side effects; and speed, convenience, and effectiveness [3]. Such treatments are believed to be radiobiologically more effective in treating prostate cancers than the conventional low-dose fractions commonly used for prostate cancer radiotherapy [4,5]. SBRT treatment of localized prostate cancer has been reported as safe, and it offers excellent local control, as determined by freedom from biochemical recurrence (BCR) in patients presenting with low- and intermediate-risk cancers [6,7,8]
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