Current and Evolving Methods to Visualize Biological Data in Cancer Research

J Natl Cancer Inst. 2016 May 31;108(8):djw031. doi: 10.1093/jnci/djw031. Print 2016 Aug.

Abstract

Although the measurements of clinical outcomes for cancer treatments have become diverse and complex, there remains a need for clear, easily interpreted representations of patients' experiences. With oncology trials increasingly reporting non-time-to-event outcomes, data visualization has evolved to incorporate parameters such as responses to therapy, duration and degree of response, and novel representations of underlying tumor biology. We review both commonly used and newly developed methods to display outcomes in oncology, with a focus on those that have evolved to represent complex datasets.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomedical Research
  • Clinical Trials as Topic*
  • Computer Graphics / trends*
  • Disease-Free Survival
  • Genotype
  • Humans
  • Kaplan-Meier Estimate
  • Neoplasms / genetics
  • Neoplasms / therapy*
  • Phenotype
  • Research Design
  • Survival Rate