Pan-sarcoma database (PSDB): A model-view-controller framework application utilizing REDCap, shiny, and R to create a continuous pipeline of sarcoma data that can inform the care of current patients.

Authors

Brandon Rose

Brandon Edward Rose

University of Miami Sylvester Comprehensive Cancer Center, Miami, FL

Brandon Edward Rose, Priscila Barreto Coelho, Steven Bialick, Pooja Patel, Kurt Statz-Geary, Osvaldo Nunez, Aditi Dhir, Alina Kang, Mason Thornton, Emily Jonczak, Gina Z. D'Amato, Jonathan C. Trent

Organizations

University of Miami Sylvester Comprehensive Cancer Center, Miami, FL, University of Miami Miller School of Medicine/Sylvester Comprehensive Cancer Center, Miami, FL, University of Miami Leonard M. Miller School of Medicine, Miami, FL

Research Funding

No funding received
None.

Background: Sarcomas are a rare group of mesenchymal malignancies arising soft tissue and bone, often requiring multidisciplinary care. 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. This process can be customized to fit other institutions and can be used to explore disparities and improve quality for cancer patients. We will share our data structure, process, and code as an adaptable framework for other multidisciplinary research groups with overlapping patients. 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. We integrated relational database concepts in our design, such as normalization, and utilized standards from Clinical Data Interchange Standards Consortium (CDISC). The database is comprised of 290 data fields to capture demographics, survival data, initial HPI, pathology, stage, grade, detailed location, detailed progression history, and associated treatment data. Results: We captured data from 28,380 candidate sarcoma patients from 2010 to present, including 3,291 confirmed cases, with 751 cases reviewed to date, merging data from multiple databases, pathology, and prior projects. Currently, 30.6% of our cases are metastatic at diagnosis; 57.7% are High grade, 28.9% are Intermediate grade, and 8.9% low grade; the median age at diagnosis is 55; 93.5% of reviewed cases received systemic therapy and 73.1% received radiation. 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. Conclusions: The PSDB successfully addresses the unique data challenges faced in sarcoma research group. 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. This project also emphasizes the importance of employing appropriate tools for data management and encourages similar initiatives to enhance collaboration and benefit both research teams and the patients they study. Furthermore, because it is open-source it can be used and modified by other research teams to improve the quality of care for cancer patients.

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Abstract Details

Meeting

2023 ASCO Quality Care Symposium

Session Type

Poster Session

Session Title

Poster Session B

Track

Health Care Access, Equity, and Disparities,Technology and Innovation in Quality of Care,Palliative and Supportive Care

Sub Track

Use of IT/Analytics to Improve Quality

Citation

JCO Oncol Pract 19, 2023 (suppl 11; abstr 589)

DOI

10.1200/OP.2023.19.11_suppl.589

Abstract #

589

Poster Bd #

N12

Abstract Disclosures

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