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Are There Different Evidence Thresholds for Genomic Versus Clinical Precision Medicine? A Value of Information-Based Framework Applied to Antiplatelet Drug Therapy

Overview
Journal Value Health
Publisher Elsevier
Date 2019 Sep 13
PMID 31511188
Citations 1
Authors
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Abstract

Background: The threshold of sufficient evidence for adoption of clinically- and genomically-guided precision medicine (PM) has been unclear.

Objective: To evaluate evidence thresholds for clinically guided PM versus genomically guided PM.

Methods: We develop an "evidence threshold criterion" (ETC), which is the time-weighted difference between expected value of perfect information and incremental net health benefit minus the cost of research, and use it as a measure of evidence threshold that is proportional to the upper bound of disutility to a risk-averse decision maker for adopting a new intervention under decision uncertainty. A larger (more negative) ETC value indicates that only decision makers with low risk aversion would adopt new intervention. We evaluated the ETC plus cost of research (ETCc), assuming the same cost of research for both interventions, over time for a pharmacogenomic (PGx) testing intervention and avoidance of a drug-drug interaction (aDDI) intervention for acute coronary syndrome patients indicated for antiplatelet therapy. We then examined how the ETC may explain incongruous decision making across different national decision-making bodies.

Results: The ETCc for PGx increased over time, whereas the ETCc for aDDI decreased to a negative value over time, indicating that decision makers with even low risk aversion will have doubts in adopting PGx, whereas decision makers who are highly risk-averse will continue to have doubts about adopting aDDI. National recommendation bodies appear to be consistent over time within their own decision making, but had different levels of risk aversion.

Conclusion: The ETC may be a useful metric for assessing policy makers' risk preferences and, in particular, understanding differences in policy recommendations for genomic versus clinical PM.

Citing Articles

Evaluating genetic and genomic tests for heritable conditions in Australia: lessons learnt from health technology assessments.

Norris S, Belcher A, Howard K, Ward R J Community Genet. 2021; 13(5):503-522.

PMID: 34570356 PMC: 9530105. DOI: 10.1007/s12687-021-00551-2.

References
1.
Jneid H, Anderson J, Wright R, Adams C, Bridges C, Casey Jr D . 2012 ACCF/AHA focused update of the guideline for the management of patients with unstable angina/non-ST-elevation myocardial infarction (updating the 2007 guideline and replacing the 2011 focused update): a report of the American College of.... J Am Coll Cardiol. 2012; 60(7):645-81. DOI: 10.1016/j.jacc.2012.06.004. View

2.
Simon T, Verstuyft C, Mary-Krause M, Quteineh L, Drouet E, Meneveau N . Genetic determinants of response to clopidogrel and cardiovascular events. N Engl J Med. 2008; 360(4):363-75. DOI: 10.1056/NEJMoa0808227. View

3.
Wallentin L, Becker R, Budaj A, Cannon C, Emanuelsson H, Held C . Ticagrelor versus clopidogrel in patients with acute coronary syndromes. N Engl J Med. 2009; 361(11):1045-57. DOI: 10.1056/NEJMoa0904327. View

4.
Heilman R, Green E, Reddy K, Moss A, Kaplan B . Potential Impact of Risk and Loss Aversion on the Process of Accepting Kidneys for Transplantation. Transplantation. 2017; 101(7):1514-1517. DOI: 10.1097/TP.0000000000001715. View

5.
Bouman H, Schomig E, van Werkum J, Velder J, Hackeng C, Hirschhauser C . Paraoxonase-1 is a major determinant of clopidogrel efficacy. Nat Med. 2010; 17(1):110-6. DOI: 10.1038/nm.2281. View