ESTRO 2024 - Abstract Book

S2952

Interdiscplinary - Other

ESTRO 2024

RWD, 3) The maturity of data and digital infrastructures for rapid-learning, 4) Further support, education and evidence needed to convince stakeholders to adopt rapid-learning approaches.

Conclusion:

Rapid-learning approaches using RWD may help provide evidence where clinical trial data does not exist and allow timely evaluation of radiotherapy technique and treatment changes that are introduced. However, rapid-learning is highly dependent upon the quality of supporting data whilst the capacity for different radiotherapy centres to develop local evidence bases may pose a key challenge. The development of data and digital infrastructures are necessary to improve data accessibility and quality, along with support mechanisms for implementation that include analytical support, time and resource investment. This will strengthen the evidence and clinical confidence needed to support adoption of rapid-learning approaches in the routine setting.

Keywords: Rapid-learning methodology, real-world data

References:

1. Price G, Mackay R, Aznar M, et al. Learning healthcare systems and rapid learning in radiation oncology: Where are we and where are we going? Radiother Oncol 2021;164:183-95.

2. Lawler M, Davies L, Oberst S, et al. European Groundshot—addressing Europe’s cancer research challenges: a Lancet Oncology Commission. Lancet Oncol 2023;24: e11-56.

3. Van Loon J, Grutters J, Macbeth F. Evaluation of novel radiotherapy technologies: What evidence is needed to assess their clinical and cost effectiveness, and how should we get it? Lancet Oncol 2012;13:e169-77.