Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-22T22:08:28.079Z Has data issue: false hasContentIssue false
  • English
  • Français

Health technology assessment in the era of personalized health care

Published online by Cambridge University Press:  30 March 2011

Lidia Becla ,
Jeantine E. Lunshof ,
David Gurwitz ,
Tobias Schulte in den Bäumen ,
Hans V. Westerhoff ,
Bodo M. H. Lange  and
Angela Brand
Lidia Becla
Affiliation:
Maastricht University and Agency for Health Technology Assessment in Poland (AHTAPol)
Jeantine E. Lunshof
Affiliation:
Maastricht University and VU University Amsterdam
David Gurwitz
Affiliation:
Sackler Faculty of Medicine
Tobias Schulte in den Bäumen
Affiliation:
Maastricht University
Hans V. Westerhoff
Affiliation:
VU University Amsterdam; Netherlands Institute for Systems Biology; University of Manchester; and Manchester Interdisciplinary BioCentre
Bodo M. H. Lange
Affiliation:
FU Berlin and Max Planck Institute for Molecular Genetics
Angela Brand
Affiliation:
Maastricht University
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: This article examines the challenges for health technology assessment (HTA) in the light of new developments of personalized health care, focusing on European HTA perspectives.

Methods: Using the example of the Integrated Genome Research Network – Mutanom (IG Mutanom) project, with focus on personalized cancer diagnostics and treatment, we assess the scope of current HTA and examine it prospectively in the context of the translation of basic and clinical research into public health genomics and personalized health care.

Results: The approaches developed within the IG-Mutanom project are based on innovative technology potentially providing targeted therapies for cancer; making translation into clinical practice requires a novel course of action, however. New models of HTA are needed that can account for the unique types of evidence inherent to individualized targeted therapies. Using constructive health technology assessment (CTA) models is an option, but further suitable models should be developed.

Conclusions: Integrative, systems biology-based approaches toward personalized medicine call for novel assessment methods. The translation of their highly innovative technologies into the practice of health care requires the development of new HTA concepts.

Keywords

Health technology assessmentPersonalized cancer therapyPublic health genomicsSystems biologyMutanom
Type
METHODS
Information
International Journal of Technology Assessment in Health Care , Volume 27 , Issue 2 , April 2011 , pp. 118 - 126
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Aggarwal, S. Targeted cancer therapies. Nat Rev Drug Discov. 2010;9:427–428.CrossRefGoogle ScholarPubMed
2. Ashley, EA, Butte, AJ, Wheeler, MT, et al. Clinical assessment incorporating a personal genome. Lancet. 2010;375:1525–1535.CrossRefGoogle ScholarPubMed
3. Atreja, A, Achkar, J-P, Jain, AK, Harris, CM, Lashner, BA. Using technology to promote gastrointestinal outcomes research: A case for electronic health records. Am J Gastroenterol. 2008;103:2171–2178.CrossRefGoogle ScholarPubMed
4. Barker, AD, Sigman, CC, Hylton, NM, Berry, DA, Esserman, LJ. I-SPY2: An adaptive breast cancer trial design in the setting of neoadjuvant chemotherapy. Clin Pharmacol Ther. 2009;86:97–100.CrossRefGoogle Scholar
5. Bies, RR, Gastonguay, MR, Schwartz, SL. Mathematics for understanding disease. Clin Pharmacol Ther. 2008;83:904–908.CrossRefGoogle ScholarPubMed
6. Brenner, S. Sequences and consequences. Philos Trans R Soc Lond B Biol Sci. 2010;365:207–212.CrossRefGoogle ScholarPubMed
7. Cooksey, D. A review of UK health research funding. Norwich: Crown copyright; 2006. http://www.hm-treasury.gov.uk/d/pbr06_cooksey_final_report_636.pdf (accessed June 1, 2010).Google Scholar
8. Economist Intelligence Unit. Breakaway: The global burden of cancer—challenges and opportunities. London, New York, Hong Kong: 2009. http://graphics.eiu.com/marketing/pdf/EIU_LIVESTRONG_Global_Cancer_Burden.pdf (accessed June 1, 2010).Google Scholar
9. European Network for Health Technology Assessment. Definition of HTA. http://www.eunethta.net/HTA (accessed June 1, 2010).Google Scholar
10. Guyatt, GH, Oxman, AD, Vist, GE, et al. GRADE: An emerging consensus on rating quality of evidence and strength of recommendations. BMJ. 2008;336:924–926.CrossRefGoogle ScholarPubMed
11. Hornberg, JJ, Bruggeman, FJ, Westerhoff, HV, Lankelma, J. Cancer: A systems biology disease. BioSystems. 2006;83:81–90.CrossRefGoogle Scholar
12. NGFN-Plus Integrated Genome Research Network–Mutanom. www.ngfn.de/en/mutanom.html; http://www.mutanom.org/ (accessed June 1, 2010).Google Scholar
13. International Network of Agencies for Health Technology Assessment. HTA resources. http://www.inahta.org/HTA/ (accessed June 1, 2010).Google Scholar
14. Kohane, IS. The twin questions of personalized medicine: Who are you and whom do you most resemble? Genome Med. 2009;1:4.CrossRefGoogle Scholar
15. Kravitz, RL, Duan, N, White, RH. N-of-1 Trials of expensive biological therapies: A third way? Arch Intern Med. 2008;168:1030–1033.CrossRefGoogle ScholarPubMed
16. Leary, RJ, Kinde, I, Diehl, F, et al. Development of personalized tumor biomarkers using massively parallel sequencing. Sci Transl Med. 2010;2:20ra14.CrossRefGoogle ScholarPubMed
17. Lunshof, JE. Personalized medicine: How much can we afford? A bioethics perspective. Per Med. 2005;2:43–47.CrossRefGoogle Scholar
18. Murgo, AJ, Kumar, S, Rubinstein, L, et al. Designing phase 0 cancer clinical trials. Clin Cancer Res. 2008;14:3675–3682.CrossRefGoogle Scholar
19. Ogilvie, D, Craig, P, Griffin, S, Macintyre, S, Wareham, NJ. A translational framework for public health research. BMC Public Health. 2009; 9:116–125.CrossRefGoogle ScholarPubMed
20. Retel, VP, Bueno-de-Mesquita, JM, Hummel, MJM, et al. Constructive technology assessment (CTA) as a tool in coverage with evidence development: The case of the 70-gene prognosis signature for breast cancer diagnostics. Int J Technol Assess Health Care. 2009;25:73–83.CrossRefGoogle ScholarPubMed
21. Rogowski, WH, Hartz, SC, John, JH. Clearing up the hazy road from bench to bedside: A framework for integrating the fourth hurdle into translational medicine. BMC Health Serv Res. 2008;8:194.CrossRefGoogle ScholarPubMed
22. Rosenkötter, N, Vondeling, H, Blancquaert, I, et al. The contribution of health technology assessment, health needs assessment, and health impact assessment to the assessment and translation of technologies in the field of public health genomics. Public Health Genomics. 2011;14:43–52.CrossRefGoogle Scholar
23. Samani, NJ, Tomaszewski, M, Schunkert, H. The personal genome—the future of personalized medicine? Lancet. 2010;375:1497–1498.CrossRefGoogle Scholar
24. Schulman, K, Valverde Vidal, A, Ackerly, DC. Personalized medicine and disruptive innovation: Implications for technology assessment. Genet Med. 2009;11:577–581.CrossRefGoogle ScholarPubMed
25. Shabo, A. Clinical genomics data standards for pharmacogenetics and pharmacogenomics. Pharmacogenomics. 2006;7:247–253.CrossRefGoogle ScholarPubMed
26. Westerhoff, HV, Palsson, BO. The evolution of molecular biology into systems biology. Nat Biotechnol. 2004;10:1249–1252.CrossRefGoogle Scholar