With the increase in size and complexity of the data associated with clinical studies, in particular oncology studies, using data standards, visualization standards, and sophisticated algorithms are necessary to provide medical writers, clinical data scientists, and medical officers with the information needed to perform their tasks in an efficient manner. Utilizing interactive summary graphics to drill down on populations of interest allows clinicians to focus on patients with the greatest efficacy response or safety issues. Upon finding these subjects of interest, medical writers and medical officers can explore their details by generating Adverse Event Narratives or Patient Profiles to understand their impact on the overall results of the study.


Learning Objectives

  • Identify how to organize and select relevant supporting information such as concomitant medications, laboratory data, and other associated events that feed into adverse event narratives
  • Understand Progression Free Survival curves and hazard ratio forest plots for patient subgroups
  • Interpret a qualitative tumor response evaluation using a graphical technique called Swimmer Plots
  • Evaluate the patients’ overall quantitative “best” response in tumor shrinkage using a graphical technique called Waterfall Plots
  • Recognize patient trends in tumor results and new lesion occurrence across study visits/time using a graphical technique called Spider Plots


  • Avanti Karandikar, Senior Manager, Clinical Business and System Analysis RDIS, MedImmune (AstraZeneca Biologics)
  • Geoffrey Mann, PhD, JMP Life Sciences Product Manager, SAS Institute

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