Precision Oncology Decision Support: Current Approaches and Strategies for the Future

Clin Cancer Res. 2018 Jun 15;24(12):2719-2731. doi: 10.1158/1078-0432.CCR-17-2494. Epub 2018 Feb 2.

Abstract

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719-31. ©2018 AACR.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Review

MeSH terms

  • Biomarkers, Tumor
  • Clinical Trials as Topic
  • Computational Biology / methods
  • Decision Support Systems, Clinical*
  • Decision Trees
  • Disease Management
  • Disease Susceptibility
  • Genetic Predisposition to Disease
  • Genetic Testing
  • Genomics / methods
  • Humans
  • Medical Oncology* / methods
  • Molecular Diagnostic Techniques
  • Molecular Targeted Therapy
  • Neoplasms / diagnosis*
  • Neoplasms / etiology
  • Neoplasms / therapy*
  • Precision Medicine* / methods

Substances

  • Biomarkers, Tumor