ISSUE: Measuring entire population change from baseline and time to deterioration has long been a standard for interpreting PRO data. However, these results can be challenging to interpret for those not trained in PRO science, are not always informative and can include inherent bias. In this issue panel, we will discuss approaches for drawing insight from PRO data and making it more intuitive to patients and decision makers.

OVERVIEW: Dr. Roydhouse will begin the session by providing an overview of the challenge of interpreting PRO data. The session will discuss different ways of approaching the challenge of visualization from research, regulatory and industry perspectives. Dr. Manson will discuss from a manufacturer’s perspective how visualizing PRO data on a patient level using r shiny to create lasagna plots, Sankey diagrams and animations can help identify trends within PROs. She will also discuss the benefits of linking PRO data with clinical data and stratification factors. Dr. Snyder will share stakeholder-driven evidence-based recommendations for presenting PRO data to promote patient and clinician understanding and use. The recommendations were developed based on extensive evidence regarding accuracy of interpretation and clarity, and through a stakeholder-engaged Delphi process. Dr Fiero will share from a regulator perspective how better interrogation and presentation of PRO data can improve interpretation of patient experience data for regulatory decision-making. This will include the importance of incorporating additional information such as treatment discontinuation and missing data in order provide a full picture and avoid misinterpretation of patient experience. She will also discuss the trade-off between simplicity of presentation aimed for patients versus presentations aimed for regulators with more granularity. Panelists will then debate the practical and scientific challenges that could influence implementation of better PRO visualization. The presenters will poll the audience on their priorities for better understanding PRO data.