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How Will Big Data Impact Clinical Decision Making and Precision Medicine in Radiation Therapy?

Published:November 05, 2015DOI:https://doi.org/10.1016/j.ijrobp.2015.10.052
      “Personalized” or “precision” medicine refers to medical treatment tailored to the individual characteristics of each patient. As noted by the President's Council of Advisors on Science and Technology, precision medicine involves “the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment. Preventive or therapeutic interventions can then be concentrated on those who will benefit, sparing expense and side effects for those who will not” (

      President's Council of Advisors on Science and Technology. Priorities for Personalized Medicine. Available at: https://www.whitehouse.gov/files/documents/ostp/PCAST/pcast_report_v2.pdf. Accessed August 27, 2015.

      ). Although much attention has focused on discovering genomic predictors of risk and outcomes and incorporating this information into treatment decisions, consideration of patient preferences and a variety of other individual characteristics are also important components of truly personalized care.
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      References

      1. President's Council of Advisors on Science and Technology. Priorities for Personalized Medicine. Available at: https://www.whitehouse.gov/files/documents/ostp/PCAST/pcast_report_v2.pdf. Accessed August 27, 2015.

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      Linked Article

      • Overview of the American Society for Radiation Oncology–National Institutes of Health–American Association of Physicists in Medicine Workshop 2015: Exploring Opportunities for Radiation Oncology in the Era of Big Data
        International Journal of Radiation Oncology • Biology • PhysicsVol. 95Issue 3
        • Preview
          Big data research refers to the collection and analysis of large sets of data elements and interrelationships that are difficult to process with traditional methods. It can be considered a subspecialty of the medical informatics domain under data science and analytics. This approach has been used in many areas of medicine to address topics such as clinical care and quality assessment (1-3). The need for informatics research in radiation oncology emerged as an important initiative during the 2013 National Institutes of Health (NIH)–National Cancer Institute (NCI), American Society for Radiation Oncology (ASTRO), and American Association of Physicists in Medicine (AAPM) workshop on the topic “Technology for Innovation in Radiation Oncology” (4).
        • Full-Text
        • PDF
      • Introduction to Big Data in Radiation Oncology: Exploring Opportunities for Research, Quality Assessment, and Clinical Care
        International Journal of Radiation Oncology • Biology • PhysicsVol. 95Issue 3
        • Preview
          Radiation oncology is in the vanguard of the collection of digital and structured information about patients for use in learning and advancing care through new big data initiatives. With its ingrained data collection history, the field provides a rich and fertile environment for exploring emerging big data opportunities in cancer care and research. Radiation therapy provides a unique combination of clinical patient demographics; physical use of radiation; application of image guidance (“radiomics”); and biological markers (genomics, proteomics, metabolomics) generated over a treatment period that can span a few days to several weeks and months.
        • Full-Text
        • PDF

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