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Activity Number: 33 - Recent Advances in Statistical Graphics
Type: Contributed
Date/Time: Sunday, August 7, 2022 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Graphics
Abstract #323295
Title: A Dynamic Mapping Tool for Spatial-Temporal Data: Visualizing Data for Patients Registered to a National Cancer Clinical Trials Network
Author(s): Samuel LeBlanc* and Cathy Rankin and Phyllis Goodman and Michael LeBlanc
Companies: Georgetown University and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center
Keywords: dynamic; graphics; clinical; triasl

We develop a visualization mapping tool to explore attributes of patients registered to cancer clinical trials as part of a publicly funded national oncology group (SWOG Cancer Research Network). SWOG, part of the National Clinical Trials Network, conducts a broad range of therapeutic and non-therapeutic clinical trials. The application is implemented in JavaScript using a combination of data visualization libraries. The map portion is created using Mapbox, which provides an excellent framework for dynamic mapping applications with vector tiles. The additional graphics are created using D3.js, the premier open-source data visualization library which combines SVG, HTML, and CSS to create a range of beautiful dynamic data visualizations. An important goal was to provide dynamic visualizations to clinical researchers and staff in our group. The tool allows the dynamic exploration of the types of clinical trials (therapeutic and non-therapeutic), the numbers of patients registered to trials over time (2014-2021) including during the COVID pandemic, and locations of registering institutions. Graphical and tabular summaries of race , ethnicity, sex and age are also generated,

Authors who are presenting talks have a * after their name.

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