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Outcomes Modeling (Tumor Control, Response Modeling, Clinical Decision Making)

W Tome1*, M Thor2*, A Appelt3*, (1) Montefiore Medical Center, Bronx, NY, (2) Memorial Sloan Kettering Cancer Center, New York, New York, (3) St James's University Hospital, West Yorkshire, UK


(Monday, 7/30/2018) 1:45 PM - 3:45 PM

Room: Karl Dean Ballroom A1

This session will focus on advances in outcomes modeling since the QUANTEC (QUAntitative Normal Tissue Effects in the Clinic) report, published in 2010. Advances since that time have accelerated, as larger data sets with full 3-D data have become available, allowing for more quantitative and comprehensive models.

This session will discuss high quality modeling results that have been published to predict tumor control probability, as well as multiple normal tissue endpoints for head and neck, lung, and pelvic radiotherapy treatments. While some models have introduced mechanistic elements, most radiotherapy outcome models are driven by determining the best correlation between dose-volume parameters and the endpoint in question. Advances have come about by using larger datasets, by combining datasets from multiple centers, by including spatial dose patterns, and by including non-dose-volume risk factors (e.g., smoking.)

We will also discuss how such models could potentially be used in clinical protocols. Although progress in the last eight years has been substantial, there are still limitations to the predictive accuracy of many models as well as the rigorousness of validation tests.

Funding Support, Disclosures, and Conflict of Interest: Varian Medical Systems, Philips Medical Systems, Breast Cancer Research Foundation, PAIGE.AI, and NIH 1R01CA198121



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