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Future relevance of genetic testing: A systematic horizon scanning analysis

Published online by Cambridge University Press:  01 October 2007

Philipp Storz ,
Kai Kolpatzik ,
Matthias Perleth ,
Silvia Klein  and
Bertram Häussler
Philipp Storz
Affiliation:
IGES (Institute for Health and Social Research)
Kai Kolpatzik
Affiliation:
Federal Association of the Local Health Insurance Funds
Matthias Perleth
Affiliation:
Federal Joint Committee/G-BA
Silvia Klein
Affiliation:
IGES (Institute for Health and Social Research)
Bertram Häussler
Affiliation:
Technische Universität Berlin and IGES (Institute for Health and Social Research)
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Abstract

Objectives: The aim of this study was to identify research and development on genetic testing to find out if research addresses important disease areas, how far it is from potential clinical use, and what consequences might arise for the prioritization of health technology assessment (HTA) activities. Also a horizon scanning methodology developed in Germany is demonstrated.

Methods: A systematic search on genetic testing was conducted in an innovation database (ZIM database). Based on a daily monitoring of literature and Internet sources, reports from 2003 up to 2005 were classified related to the type of innovation, the addressed disease categories, and the developmental phase of the technology. More detailed analyses for the most frequently addressed groups of diseases were conducted.

Results: From 239 relevant reports, 41 percent referred to neoplasms; 10 percent to diseases of the cardiovascular system; 9 percent to diseases of the nervous system; 7 percent to mental and behavioral disorders; and 5 percent to endocrine, nutritional, and metabolic diseases. A total of 69 percent of research is situated in basic preclinical research, 22 percent in clinical/experimental research, and 6 percent are genetic tests being used. Diagnostic applications were most frequently reported (28 percent), followed by therapeutic prediction (22 percent), preventive prediction (18 percent), pharmacogenetics (16 percent), and screening (16 percent).

Conclusions: Widespread diseases are frequently addressed in research. HTA on genetic testing might focus on innovations addressing neoplastic diseases (in particular breast, colon, and prostate cancers) and pharmacogenetic applications for therapeutic prediction. The horizon scanning approach seems useful in the early steps of HTA processes to identify emerging new technologies that might have significant impact on future health care.

Keywords

Biomedical technology assessmentGenetic techniquesBibliographic databasesResearch priorities
Type
GENERAL ESSAYS
Information
International Journal of Technology Assessment in Health Care , Volume 23 , Issue 4 , October 2007 , pp. 495 - 504
Copyright
Copyright © Cambridge University Press 2007

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References

REFERENCES

1.Brown, IT, Smale, A, Momandwall, V, Momandwall, S. Medical technology horizon scanning. Australas Phys Eng Sci Med. 2005;28:200–203.CrossRefGoogle ScholarPubMed
2.Collins, FS, Green, ED, Guttmacher, AE, Guyer, MS. A vision for the future of genomics research. A blueprint for the genomic era. Nature. 2003;422:835–847.CrossRefGoogle Scholar
3.Douw, K, Vondeling, H, Eskildsen, D, Simpson, S. Use of the internet in scanning the horizon for new and emerging health technologies: A survey of agencies involved in horizon scanning. J Med Internet Res. 2003;5:e6.CrossRefGoogle ScholarPubMed
4.Douw, K, Vondeling, H, Oortwijn, W. Priority setting for horizon scanning of new health technologies in Denmark: Views of health care stakeholders and health economists. Health Policy. 2006;76:334–345.CrossRefGoogle ScholarPubMed
5.Douw, K, Vondeling, H, Sǿrensen, J, Jǿrgensen, T, Sigmund, H. “The future should not take us by surprise”: Preparation of an early warning system in Denmark. Int J Technol Assess Health Care. 2004;20:342–350.CrossRefGoogle ScholarPubMed
6.Douw, K, Vondeling, H. Selection of new health technologies for assessment aimed at informing decision making: A survey among horizon scanning systems. Int J Technol Assess Health Care. 2006;22:177–183.CrossRefGoogle ScholarPubMed
7.Evans, A, Van Baal, GC, McCarron, P, et al. The genetics of coronary heart disease: The contribution of twin studies. Twin Res. 2003;6:432–441.CrossRefGoogle ScholarPubMed
8.Fierz, W. Challenge of personalized health care: To what extent is medicine already individualized and what are the future trends? Med Sci Monit. 2004;10:RA111-RA123.Google ScholarPubMed
9.Giacomini, M, Miller, F, Browman, G. Confronting the “gray zones” of technology assessment: Evaluating genetic testing services for public insurance coverage in Canada. Int J Technol Assess Health Care. 2003;19:301–316.CrossRefGoogle ScholarPubMed
10.Hall, WD, Morley, KI, Lucke, JC. The prediction of disease risk in genomic medicine. Scientific prospects an implications for public policy and ethics. EMBO Rep. 2004;5:S22-S26.CrossRefGoogle Scholar
11.Higashi, MK, Veenstra, DL. Managed care in the genomics era: Assessing the cost effectiveness of genetic tests. Am J Manag Care. 2003;9:493–500.Google ScholarPubMed
12.Langer, T, Wild, C, Douw, K. Overview on Horizon Scanning System (HSS) for Priority Setting on emerging/new technologies. Ludwig Boltzmann Institute LBI-HTA Projektbericht Nr.: 002 (EUNetHTA WP7 Strand B – 1 Deliverable). 2006.Google Scholar
13.Mundy, L, Merlin, TL, Parrella, A. The Australia and New Zealand horizon scanning network. Aust Health Rev. 2005;29:395–397.CrossRefGoogle ScholarPubMed
14.Robert, G, Stevens, A, Gabbay, J. ‘Early warning systems’ for identifying new healthcare technologies. Health Technol Assess. 1999;3.CrossRefGoogle ScholarPubMed
15.Rogowski, W. Genetic Screening by DNA technology: A systematic review of health economic evidence. Int J Technol Assess Health Care. 2006;22:327–337.CrossRefGoogle ScholarPubMed
16.Simpson, S, Hyde, C, Cook, A, Packer, C, Stevens, A. Assessing the accuracy of forecasting: Applying standard diagnostic assessment tools to a health technology early warning system. Int J Technol Assess Health Care. 2004;20:381–384.CrossRefGoogle ScholarPubMed
17.Van Delden, J, Bold, I, Kalis, A, Derijks, J, Leufkens, H. Tailor-made pharmacotherapy: Future developments and ethical challenges in the field of pharmacogenomics. Bioethics. 2004;18:303–321.CrossRefGoogle ScholarPubMed