Oncospace: A Database Designed for Personalized Medicine in Radiation Oncology
T McNutt*, K Evans, J Moore, W Yang, J Herman, H Quon, A Sharabi, J Wong, T DeWeese, Johns Hopkins University, Baltimore, MDWE-G-108-2 Wednesday 4:30PM - 6:00PM Room: 108
Purpose: The Oncospace database aggregates treatment planning and clinical information about prior patients facilitating extraction of knowledge from prior courses of care. The goal is to use this knowledge to influence clinical decisions, quality and safety of care for new patients.
Methods: The Oncospace website, built in C# and ASP.NET, accesses the MS SQLServer database for analysis. The data tables are designed to support patient geometry, targets and organs at risk (OAR) and their spatial relationships, dose distributions, toxicities, diagnosis and disease progression, chemotherapy and medications, laboratory values, patient histories and demographics. Data is collected directly from the treatment planning system and the oncology information system (OIS). Point of service data collection is facilitated with tablet (iPad) forms linked to the OIS.
Results: Web pages have been built to answer the following:
A) For a selected toxicity and OAR, display the dose volume histogram (DVH) and colorize them by the maximum toxicity grade of the patient while identifying a selected patients DVH
B) For a selected OAR and percent volume (%V), find the lowest dose achieved from all patients whose %V is closer to the selected target volume?
C) For a given diagnosis, toxicity and treatment, display the aggregate trend in toxicity from start of treatment (acute) through several year follow-up (late)?
Oncospace currently supports: and a full H&N database, a multi-institutional pancreatic stereotactic trial, and shape database for automated planning pancreas cancer.
Conclusion: Oncospace can provide fast access to large amounts of data through complex queries designed to answer specific clinical questions to influence the safety and quality of care for new patients. This system can be used in the clinical setting to assess both plan quality and outcome expectations for new patients based on the data of prior patients.
Funding Support, Disclosures, and Conflict of Interest: Funding for this research was provided by the Commonwealth Foundation, Elekta/IMPAC Medical Systems, Inc., Philips Radiation Oncology Sytems, and the Johns Hopkins University.
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