Stem Cell Engraftment Application

Stem Cell Engraftment Application

To assist research staff with outcomes reporting, we developed a R/Shiny application we refer to as the Stem Cell Engraftment Application. I presented on the development and reception of the app on at R/Medicine 2021 and you can view the video recording here as well as in the links at the top of the page. The repository for this app is private to CHOP and not made publicly available but I welcome any questions any viewers have regarding it.

Stem cell transplantation is a life-saving therapeutic solution for cancers and other malignancies. During the process, a donor provides stem cells from their bone marrow which are separated from the blood using apheresis. Before the stem cells can be provided, the recipient must first have their blood-forming cells destroyed through chemotherapy so that both cancerous and non-cancerous cells are eliminated. The patient then receives the stem cells to replenish the lost cells and produce non-cancerous ones.

The key factor to monitor when undergoing this process is known as engraftment: the process when cells of interest re-emerge at appropriate count levels. In this case, we’re most interested in neutrophils (white blood cells responsible for fighting off infection) and platelets (responsible for blood clotting). We want the patient’s neutrophil level to reach a count of 500cells/uL and their platelet count to reach 20cells/uL.

For research staff, reporting these outcome values requires labor-intensive and error-prone calculations taken from multiple sources. By using the application, users need only supply a patient medical record number and receive all related transplants with easy to use buttons that copy the automated calculation directly to their clipboard for direct transcription into the data registry. This is further supported with interactive visuals for confirmation that the calculations are correct.

After using the application for just a few months, research staff were able to correct numerous past entry errors as well as effectively eliminate prospective error reporting. Please feel free to watch the video recording to learn more!

Engraftment App

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Richard Hanna
Data Scientist & Biomedical Engineer