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EPMA Journal

, Volume 9, Issue 2, pp 113–123 | Cite as

Preventive, predictive, and personalized medicine for effective and affordable cancer care

  • Jaak Ph. Janssens
  • Klaus Schuster
  • Andreas Voss
Mini Review

Abstract

Preventive, predictive, and personalized medicine (PPPM) has created a wealth of new opportunities but added also new complexities and challenges. The European Cancer Prevention Organization already embraced unanimously molecular biology for primary and secondary prevention. The rapidly exploding genomic language and complexity of methods face oncologists with exponentially growing knowledge they need to assess and apply. Tissue specimen quality becomes one major concern. Some new innovative medicines cost beyond any reasonable threshold of financial support from patients, health care providers, and governments and risk sustainability for the health care system. In this review, we evaluate the path for genomic guidance to become the standard for diagnostics in cancer care and formulate potential solutions to simplify its implementation. Basically, introduction of molecular biology to guide therapeutic decisions can be facilitated through supporting the oncologist, the pathologist, the molecular laboratory, and the interventionist. Oncologists need to know the exact indication, utility, and limitations of each genomic service. Minimal requirements on the label must be addressed by the service provider. The interventionist is there to bring the most optimal tissue sample to pathology where the tissue is expanded to a variety of appropriate liquid-based samples. The large body of results then should be translated into meaningful clinical guidance for the individual patient. Surveillance, with the appropriate application of health economic indicators, can make this system long lasting. For governments and health care providers, optimal cancer care must result in a cost-effective, resource-sustainable, and patient-focused outcome.

Keywords

Predictive preventive personalized medicine Molecular biology Patient selection Cancer care Biopsy Genomic profiling Health economics 

Notes

Acknowledgments

The authors thank Mrs. Sabine Janssens for preparing the manuscript. The authors were not paid to write this article. They have connections with the industry (Conflict of Interest). This paper represents the consolidated opinion of the European Cancer Prevention Organization regarding preventive, predictive, and personalized medicine.

Compliance with ethical standards

Not applicable

Conflict of interest

The authors declare that they have no conflict of interest.

Statement of informed consent

Patients have not been involved in the study.

Statement of human and animal rights

No experiments have been performed including patients and/or animals.

References

  1. 1.
    Davis C, Naci H, Gurpinar E, Poplasvka E, Pinto A, Aggarwal A. Availability of evidence of benefits on overall survival and quality of life of cancer drugs approved by European Medicines Agency: retrospective cohort study of drug approvals 2009-13. BMJ. 2017;359:j4530.CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Stephens Z, Lee S, Faghri F, Campbell R, Zhai C, Efron M, et al. Big data: astronomical or genomical? PLoS Biol. 2015;13(7):e1002195.  https://doi.org/10.1371/journal.pbio.1002195.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Aftimos PG, Barthelemy P, Awada A. Molecular biology in medical oncology: diagnosis, prognosis, and precision medicine. Discov Med. 2014;17:81–91.PubMedGoogle Scholar
  4. 4.
    Hyman DM, Taylor BS, Baselga J. Implementaing genome-driven oncology. Cell. 2017;168:584–99.CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Jackson DB. Clinical and Economic impact of the nonresponder phenomenon—implications for systems-based discovery. Drug Discov Today. 2009;14:380–5.  https://doi.org/10.1016/j.drudis.2009.01.006.CrossRefPubMedGoogle Scholar
  6. 6.
    Alexandrescu DT, Ichim TE, Riordan NH, Marincola FM, Di Nardo A, Kabigting FD, et al. Immunotherapy for melanoma: current status and perspectives. J Immunother. 2010;33:570–90. https://www.nccn.org CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Surrey LF, Luo M, Chang F, Li M. The genomic era of clinical oncology: integrated genomic analysis for precision cancer care. Cytogenet Genome Res. 2016;150:162–75.CrossRefPubMedGoogle Scholar
  8. 8.
    Golubnitschaja O, Baban B, Boniolo G, Wang W, Bubnov R, Kapalla M, et al. Medicine in the early twenty-first century: paradigm and anticipation–EPMA position paper 2016. EPMA J. 2016;7:23.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Janssens J, Gallagher WM, Dean A, Ussla G, Stamp G. Tumor profiling-directed precision cancer therapy—comparison of commerical and academic clinical utility. Int J Surg Surgical Proced. 2017;2:123.Google Scholar
  10. 10.
    Gabriel S, Normand SL. Getting the methods right—the foundation of patient-centered outcomes research. N Engl J Med. 2012;367:787–90.CrossRefPubMedGoogle Scholar
  11. 11.
    Basik M, Aguilar-Mahecha A, Rousseau C, Diaz Z, Tejpar S, Spatz A, et al. Biopsies: next-generation biospecimens for tailoring therapy. Nat Rev Clin Oncol. 2013;10:437–50.CrossRefPubMedGoogle Scholar
  12. 12.
    Agorku D, Janssens J. Isolation and analysis of tumor cells from human solid tumor tissue extracted by needle biopsy. Application Note Miltenyi Biotec. 2017;Google Scholar
  13. 13.
    San Miguel L, Hulstaert F. The importance of test accuracy in economic evaluations of companion diagnostics. J Com Eff Res. 2015;4:569–77.CrossRefGoogle Scholar
  14. 14.
    Simon R, Roychowdhury S. Implementing personalized cancer genomics in clinical trials. Nature Rev Drug Discov. 2013;12:358–69.Google Scholar
  15. 15.
    Cornelis A, Verjans M, Van den Bosch T, Wouters K, Van Robaeys J, Janssens J, et al. Efficacy and safety of direct and frontal macrobiopsies in breast cancer. Eur J Cancer Prev. 2009;18:280–4.CrossRefPubMedGoogle Scholar
  16. 16.
    Lalji UC, Wildberger JE, Zur Hausen A, Bendek M, Dingemans AC, Hochstenbag M, et al. CT-guided percutaneous transthoracic needle biopsies using 10G large-core needles: initial experience. Cardiovasc Intervent Radiol. 2014;38:1603–10.  https://doi.org/10.1007/s00270-015-1098-z.CrossRefGoogle Scholar
  17. 17.
    Ocak S, Duplaquet F, Jamart J, Pirard L, Weynand B, Delos M, et al. Diagnostic accuracy and safety of CT-guided percutaneous transthoracic needle biopsies: 14-gauge versus 22-gauge needles. J Vasc Interv Radiol. 2016;27:674–81.CrossRefPubMedGoogle Scholar
  18. 18.
    Dean A, Byrne A, Marinova M, Hayden I. Clinical outcomes of patients with rare and heavily pretreated solid tumors treated according to the results of tumor molecular profiling. Biomed Res Int. 2016;2016:4627214–9.  https://doi.org/10.1155/2016/4627214.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Temple, R. Clinical measurement in drug evaluation. Ningano W. Thicker GT, eds. John Wiley and Sons Ltd: 1995; Von Hoff, D.D. c 1999; Dhani et al. Clin Cancer Res 2009; 15: 118–123.Google Scholar
  20. 20.
    Radovich M, Kiel PJ, Nance SM, Niland EE, Parsley ME, Ferguson ME, et al. Clinical benefit of a precision medicine based approach for guiding treatment of refractory cancers. Oncotarget. 2017;7:56491–500.Google Scholar
  21. 21.
    Eifert C, Pantazi A, Sun R, Xu J, Cingolani P, Heyer J, et al. Clinical application of a cancer genomic profiling assay to guide precision medicine decisions. Per Med. 2017;14:309–25.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Cree IA, Deans Z, Ligtenberg MJL, Normanno N, Edsjö A, Rouleau E, Solé F, Thunnissen E, Timens W, Schuuring E, Dequeker E, Murray S, Dietel M, Groenen P, Van Krieken JH, European Society of Pathology Task Force on Quality Assurance in Molecular Pathology, Royal College of Pathologists. Guidance for laboratories performing molecular pathology for cancer patients. J Clin Pathol. 2014;67(11):923–31.  https://doi.org/10.1136/jclinpath-2014-202404.
  23. 23.
    Guidance for laboratories performing molecular pathology for cancer patients. J Clin Pathol. 2014; 67: 923–931.Google Scholar
  24. 24.
    Capdevila J, Rojo F, Gonzalez-Martin A, et al. Molecular profiling for clinical decision making in advanced cancer: a clinical appraisal. J Cancer Res Treat. 2017;5:77–85.Google Scholar
  25. 25.
    Cochrane DR, Bernales S, Jacobsen BM, Cittelly DM, Howe EN, D'Amato NC, et al. Role of the androgen receptor in breast cancer and preclinical analysis of enzalutamide. Breast Cancer Res. 2014;16:R7.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Ben-Baruch NE, Bose R, Kavuri SM, Ma CX, Ellis MJ. HER2-mutated breast cancer responds to treatment with single-agent neratinib, a second-generation HER2/EGFR tyrosine kinase inhibitor. J Natl Compr Cancer Netw. 2015;13:1061–4.CrossRefGoogle Scholar
  27. 27.
    Azimi NA, Welch HG. The effectiveness of cost-effectiveness analysis in containing costs. J Gen Intern Med. 1998;13:664–9.CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Cairns J. Using cost-effectiveness evidence to inform decisions as to which health services to provide. Health Syst Reform. 2016;2:32–8.Google Scholar

Copyright information

© European Association for Predictive, Preventive and Personalised Medicine (EPMA) 2018

Authors and Affiliations

  • Jaak Ph. Janssens
    • 1
  • Klaus Schuster
    • 2
  • Andreas Voss
    • 2
  1. 1.The European Cancer Prevention OrganizationHasseltBelgium
  2. 2.Caris Life SciencesBaselSwitzerland

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