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Prostate Clinical Outlook Visualization System
Revision: 8
Please use this identifier to cite or link to this publication: http://hdl.handle.net/10909/11297
Background: When a patient presents with localized prostate cancer, referral for radiation oncology consultation includes a discussion of likely outcomes of therapy. Among current radiation treatments for prostate cancers, hypo-fractionated stereotactic body radiation therapy (SBRT) has gained clinical acceptance based on efficacy, short duration of treatment and potential radiobiological advantages. The Prostate Clinical Outlook Visualization System (PCOVS) was developed to provide the patient and the clinician with a tool to visualize probable treatment outcomes using institutional, patient specific data for comparing results of treatment. Methods: We calculated the prostate cancer outcomes - for each prospective patient using the EPIC-26 quality of life parameters based on clinical outcomes data of 580 prostate cancer patients treated with SBRT. We applied Kaplan-Meier analysis using the ASTRO method for biochemical recurrence (BCR) free survival and likely outcome and the PCOVS nomogram to calculate parameters for quality of life. Open-source R, RShiny, and MySQL were used to develop a modularized architecture system. Results: The PCOVS presents patient specific risk scores in a gauge chart style and risk free probability bar plots to compare treatment data of patients treated with SBRT. The PCOVS generates reports, in PDF, which consist of a comparison chart of risk free probabilities and gauge charts of risk scores. This system is now being expanded as a web-based service to patients. Conclusions: The PCOVS visualized patient specific likely outcomes were compared to treatment data from a single department, helping the patient and the clinician to visualize likely outcomes. The PCOVS approach can be expanded to other specialties of oncology with the flexible, modularized architecture which can be customized by changing independent modules.
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9Joe Snyder06-28-2017Level 2OSEHRA Update: Remove "append" directive to table that is dropped in MySQL
8Jihwan Park06-12-2017Debug: Survival Plot Debug
Cause: Progress numbers in Survival Plot function has wrong sequence
Solve: Matching exact number of sequence in Survival Plot function
File: SurvivalCurve_Hazard_Overall.R
7Jihwan Park06-12-2017Debug: Date type data loading
Cause: Conversion error happened while converting R date type into mysql date type
Solve: Explicitly convert date type in R
File: SAVE_CLADATA.R, SAVE_SURVIVAL_DATA2.R
6Jihwan Park06-12-2017Debug: RMySQL package installation
Cause: plotly library on ubuntu has unexpected behavior on ubuntu
Workaround: install stable version of plotly for ubuntu
File: install_libraries.R
5Jihwan Park06-10-2017Debug: RMySQL package installation
Cause: Stable version of RMySQL has error when patching data with development version of DBI on Ubuntu.
Workaround: remove RMySQL package and install git-hub version of RMySQL.
File: install_libraries.R
4Jihwan Park06-09-2017Add data argument option to the ggsurvplot function.
related file name: SurvivalCurve_Hazard_Overall.R
3Jihwan Park05-26-2017checkDB.R : crate log table if not exists.
2Jihwan Park05-25-2017Add checkDB.R : checking database for initial data loading process.
edit server.R : implement checkDB.R function
1Jihwan Park05-23-2017

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