## 2 Materials and Methods
To generate electronic file report, such as PDF or HTML, the PCOVS used R packages knirt ([[https://cran.r-project.org/web/packages/knirt](https://cran.r-project.org/web/packages/knirt)]([https://cran.r-project.org/web/packages/knirt](https://cran.r-project.org/web/packages/knirt))) for dynamic report generation and rmarkdown ([[https://cran.r-project.org/web/packages/rmarkdown](https://cran.r-project.org/web/packages/rmarkdown)]([https://cran.r-project.org/web/packages/rmarkdown](https://cran.r-project.org/web/packages/rmarkdown))) for converting R documents into PDF or HTML. Eventually, the PCOVS was designed to achieve full stack architecture from data preparation to visualization. The PCOVS used BCR based on the American Society of Therapeutic Radiology and Oncology (ASTRO) definition [9]. In ASTRO, BCR means the mid-point between prostate specific antigen (PSA) nadir and the first of three consecutive rises in PSA level [10]. In the PCOVS, BCR was finally defined as the mid-point between PSA nadir and the first of three consecutive increases in PSA level at least 0.5 ng/mL based on the ASTRO BCR definition and physician comments. The Kaplan-Meier Survival analysis was done to show the survival curves for patient specific data when comparing to treated patient data in order to distinguish the difference of disease free survival probabilities [11]. R package survival was used to develop survival analysis ([[https://cran.r-project.org/package=survival](https://cran.r-project.org/package=survival)]([https://cran.r-project.org/package=survival](https://cran.r-project.org/package=survival))). Using disease free rate based on the ASTRO BCR definition, the PCOVS nomogram was developed by Open-source R with the cox model [12]. The PCOVS nomogram was used to store risk classification data and visualize estimated risk scores of BCR free survival and likely outcome. The PCOVS nomogram has three levels of risk score measurement, which are low, intermediate, and high risk group. The risk classification module was developed using R packages rms ([[https://cran.r-project.org/package=rms](https://cran.r-project.org/package=rms)]([https://cran.r-project.org/package=rms](https://cran.r-project.org/package=rms))), survival ([[https://cran.r-project.org/package=survival](https://cran.r-project.org/package=survival)]([https://cran.r-project.org/package=survival](https://cran.r-project.org/package=survival))), survey ([[https://cran.r-project.org/package=survey](https://cran.r-project.org/package=survey)]([https://cran.r-project.org/package=survey](https://cran.r-project.org/package=survey))), and SvyNom ([[https://cran.r-project.org/package=SvyNom](https://cran.r-project.org/package=SvyNom)]([https://cran.r-project.org/package=SvyNom](https://cran.r-project.org/package=SvyNom))). The quality of life (QOL) factors were used to develop QOL likely outcomes based on the Expanded EPIC-26, which includes three domains, such as rectal QOL, urinary QOL, and sexual QOL domains [13]. The EPIC-26 was developed by researchers at the University of Michigan and UCLA, and was intended to measure health related QOL among men with prostate cancer. The EPIC-26 was developed as a short-form version of the full EPIC. The EPIC-26 instrument contains four multi-item domains: (1) urinary domains such as urinary incontinence (four items), urinary irritation/ obstruction (four items), and one question related to overall bother, (2) bowel domain (six items), (3) sexual domain (six items), and (4) vitality/hormonal function domain (five items) [14; 15]. In addition, the EPIC-26 retains the single item measure of overall urinary bother from the University of California, Los Angeles, Prostate Cancer Index (UCLA-PCI) [14] (Appendix A). Each factor has their own scales to calculate 0-100 points. 0 means very bad and 100 means very good, in that the PCOVS can get a risk value with subtraction of each factor values from 100. This can result in negative values for QOL domains.