the test result and treatment choice may sometimes be weak, at best. For instance, a
genetic test may identify patients at risk of an early onset of a disease. However, it
may be the case that the actual preventive treatment for that disease is not yet
available. One may wonder what the added benefit is of a test that predicts an illness
for which there is no cure or no mitigation is as yet possible. May this test, in fact,
be producing ill effects instead of benefits, and how does the “value of knowing”
trade off against the “value of not knowing” both for the patient and the health care
system? This is a normative as well as an empirical question. Alternatively, a test
can also show that the patient will not benefit from any known treatment, which
creates another situation with multiple ethical and clinical facets that HTA and
economic evaluations may need to take into account.
Finally, as Hamburg and Collins argue ( 2010 ), the main contribution of person-
alized medicine will be marked when clinically beneficial new products and
approaches are incorporated into day-to-day clinical practice. Currently, however,
despite the great attention given to personalized medicines, the pace at which they
are being adopted into clinical practice has been limited (at least not as quick as
expected), and the policy challenges such as the ones discussed in this chapter may
need to be overcome to deliver a larger scope of benefits to patients. The current
“one-drug-fits-all” approach is increasingly being exposed as cost-ineffective,
while evidence is increasing of the cost-effectiveness of patient biomarker stratifi-
cation. Judging by the recent trends in technology development (not just in the
medical field), we can expect the cost of new companion diagnostics to decrease
(e.g., technologies based on genotyping, sequencing) and the cost of new therapies
(e.g., chemotherapies) to increase in the future. This will, in turn, ensure that
personalized medicine becomes even more economically attractive and its associ-
ated cost-offset potential even more highly pronounced.
Acknowledgements This work is part of the VENI research programme, which is financed by the
Netherlands Organisation for Scientific Research (NWO). The researchers were free in study
design, data collection, analysis and interpretation, as well as writing and submitting the manu-
script for publication. The views expressed in this chapter are those of the authors.
References
Allison M (2008) Is personalized medicine finally arriving? Nat Biotechnol 26:509–517
Annemans L, Redekop K, Payne K (2013) Current methodological issues in the economic
assessment of personalized medicine. Value Health 16:20–26
Bassi J, Lau F (2013) Measuring value for money: a scoping review on economic evaluation of
health information systems. J Am Med Inform Assoc 20(4):792–801
Behl AS, Goddard KA, Flottemesch TJ, Veenstra D, Meenan RT, Lin JS, Maciosek MV (2012)
Cost-effectiveness analysis of screening for KRAS and BRAF mutations in metastatic colo-
rectal cancer. J Natl Cancer Inst 104:1785–1795
Bobinac A (2012) Economic evaluations of health technologies: insights into the valuation and
measurement of benefits. Erasmus University Rotterda, Rotterdam. ISBN 978-94-6169-250-4
132 A. Bobinac and M. Vehovec