Prostate Clinical Outlook Visualization System for Patients and Clinicians Considering Cyberknife Treatment—A Personalized Approach
Open Source Electronic Health Record Alliance, 1934 Old Gallows Road Suite 420, Vienna, VA 22182, USA
Department of Medical Informatics, College of Medicine, The Catholic University of Korea, 222, Banpo-dong, Seocho-gu, Seoul 06591, Korea
Arlington Innovation Center, Virginia Tech, 900 N Glebe Road, Arlington, VA 22203, USA
Department of Radiation Medicine, Georgetown University Hospital, 3800 Reservoir Rd. NW, Washington, DC 20007, USA
Author to whom correspondence should be addressed.
Appl. Sci. 2018, 8(3), 471; https://doi.org/10.3390/app8030471
Received: 22 February 2018 / Revised: 15 March 2018 / Accepted: 16 March 2018 / Published: 19 March 2018
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 the 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 who were treated with SBRT. We applied Kaplan-Meier analysis using the ASTRO definition 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 the treatment data of patients treated with SBRT. The PCOVS generates reports, in PDF, which consists of a comparison charts of risk free probabilities late effects 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.