(P 224) PAN-SARCOMA DATABASE (PSDB): AN UPDATE ON MIAMI'S COLLABORATIVE MULTI-USER DATA PIPELINE OF SARCOMA DATA USING REDCAP AND R CODING

Objective: Sarcomas are a rare group of mesenchymal malignancies arising soft tissue and bone, often requiring multidisciplinary care. Capturing the complexity of patients’ sarcoma diagnoses, treatments, and progressions pose several logistical data challenges. The Pan-Sarcoma Database (PSDB) is an innovative open-source research application developed to efficiently collect and manage data on sarcoma patients to create a reliable research pipeline by funneling data from multiple sources.

Methods: The Model-View-Controller (MVC) framework is a software design pattern used by many modern applications. In this framework, "model" is the database, including the structure and metadata; "view" is the user interface software; "controller" is the coding language used to handle user input, update the model, and interact with the viewer. PSDB uses REDCap, shiny, and R, respectively. The database is comprised of over 400 data fields to capture demographics, survival, initial HPI, pathology, stage, grade, detailed location, detailed progression history, genetic testing, and all associated treatment data. Two developmental open-source R packages were written for these tasks: REDCapSync and RosyREDCap. REDCapSync uses the REDCap Application Program Interface (API) to maintain a feed of REDCap data. RosyREDCap uses the feed from REDCapSync to filter, visualize, and analyze the data from REDCap.

Results: We captured data from 31,253 candidate sarcoma patients from 2010 to present, including 4,303 confirmed cases, with 1,270 (30%) cases reviewed to date, merging data from multiple databases, pathology, and prior projects. Currently, 20% of our cases are metastatic at diagnosis; 51% are High grade; the median age at diagnosis is 52. By capturing key data and organizing an open-source code base in R mapped to our “model”, we produced updating tables, statistics, time-to-endpoint analyses, and other modifiable outputs to identify outcome disparities that produce data for dozens of real-world data projects.

Conclusion: The PSDB successfully addresses the unique data challenges faced by sarcoma research groups, allowing for in-depth exploratory data analysis from refreshing data sources. The use of the MVC framework with REDCap, shiny, and R, enabled the creation of an application that is secure, user-friendly, and adaptable, supporting collaborative research efforts. We hope to share our pipeline methods with other institutions to increase collaborative research efforts and data sharing in sarcoma.