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CC BY-NC-ND 4.0 · Yearb Med Inform 2020; 29(01): 235-242
DOI: 10.1055/s-0040-1701983
Section 12: Cancer Informatics
Survey
Georg Thieme Verlag KG Stuttgart

From Patient Engagement to Precision Oncology: Leveraging Informatics to Advance Cancer Care

Ashley C. Griffin
1   University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
,
Umit Topaloglu
2   Wake Forest University School of Medicine, Winston-Salem, NC, USA
,
Sean Davis
3   National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
,
Arlene E. Chung
1   University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
4   University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA
5   UNC Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA
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Publikationsverlauf

Publikationsdatum:
21. August 2020 (online)

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Summary

Objectives: Conduct a survey of the literature for advancements in cancer informatics over the last three years in three specific areas where there has been unprecedented growth: 1) digital health; 2) machine learning; and 3) precision oncology. We also highlight the ethical implications and future opportunities within each area.

Methods: A search was conducted over a three-year period in two electronic databases (PubMed, Google Scholar) to identify peer-reviewed articles and conference proceedings. Search terms included variations of the following: neoplasms[MeSH], informatics[MeSH], cancer, oncology, clinical cancer informatics, medical cancer informatics. The search returned too many articles for practical review (23,994 from PubMed and 23,100 from Google Scholar). Thus, we conducted searches of key PubMed-indexed informatics journals and proceedings. We further limited our search to manuscripts that demonstrated a clear focus on clinical or translational cancer informatics. Manuscripts were then selected based on their methodological rigor, scientific impact, innovation, and contribution towards cancer informatics as a field or on their impact on cancer care and research.

Results: Key developments and opportunities in cancer informatics research in the areas of digital health, machine learning, and precision oncology were summarized.

Conclusion: While there are numerous innovations in the field of cancer informatics to advance prevention and clinical care, considerable challenges remain related to data sharing and privacy, digital accessibility, and algorithm biases and interpretation. The implementation and application of these findings in cancer care necessitates further consideration and research.

Keywords

Cancer informatics - precision medicine - oncology - machine learning - digital health
 

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