The prediction model can support shared decision making for patients dealing with non-small cell lung cancer (NSCLC)
Within 4 months, we connected databases with 23203 patient cases across 8 healthcare institutes in 5 countries (Amsterdam, Cardiff, Maastricht, Manchester, Nijmegen, Rome, Rotterdam, Shanghai) using the PHT. A distributed logistic regression model predicting post-treatment two-year survival was trained on 14810 patients treated between 1978 and 2011 and validated on 8393 patients treated between 2012 and 2015.
This project did not address a novel analysis technique or infrastructure. However, it showed that the personal health train can scale to multiple countries and hospitals within 4 months, which is a small timespan for sharing insights from data. Especially when hospitals were involved in PHT-projects previously.
- The personal health train is a scalable model
- Research questions can be relatively quickly conducting across multiple continents while data is not leaving the individual institutes
- Extending the set of used variables in the current model (e.g. image-derived information)
- Including more different (e.g. American) countries to extend the mix in represented countries and continents
In this project, we used the PHT implementation developed by Varian Medical Systems, where we developed the infrastructure and algorithms ourselves. These algorithms are publicly available at GitHub. The infrastructure is commercially available for oncology purposes (TRL 7-8). The algorithms are available, and can be executed on the commercial infrastructure (TRL 6).
|Funders||Varian Medical Systems, NOW, Province of Limburg, Dutch Cancer Society|
Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
T.M. Deist, F.J.W.M. Dankers, P. Ojha, M. Scott Marshall, T. Janssen, C. Faivre-Finn, C. Masciocchi, V. Valentini, J. Wang, J. Chen, Z. Zhang, E. Spezi, M. Button, J. Jan Nuyttens, R. Vernhout, J. van Soest, A. Jochems, R. Monshouwer, J. Bussink, G. Price, P. Lambin, A. Dekker, Distributed learning on 20 000+ lung cancer patients – The Personal Health Train, Radiotherapy and Oncology. 144 (2020) 189–200. https://doi.org/10.1016/j.radonc.2019.11.019