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Decision thresholds with genetic testing.

Stefan Felder1

  • 1Department of Business and Economics, University of Basel, Peter Merian-Weg 6, 4002, Basel, Switzerland. stefan.felder@unibas.ch.

The European Journal of Health Economics : HEPAC : Health Economics in Prevention and Care
|December 2, 2021
PubMed
Summary
This summary is machine-generated.

Genetic testing for mutations like BRCA1/2 can guide preventive cancer treatments. Decision-making depends on mutation probability, test-treatment thresholds, and disease penetrance, balancing costs and benefits.

Keywords:
Decision thresholdsDiagnostic riskGenetic risksICER

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Area of Science:

  • Genetics
  • Medical Decision Making
  • Health Economics

Background:

  • Genetic tests identify mutations linked to increased disease risk.
  • Preventive treatments are considered when mutation penetrance is high.
  • Informed decisions require understanding test thresholds and treatment benefits.

Purpose of the Study:

  • To derive test and test-treatment thresholds for genetic testing.
  • To define the mutation probability interval for optimal genetic test use.
  • To model the impact of costs and penetrance on genetic testing decisions.

Main Methods:

  • Developed a mathematical model to define test and test-treatment thresholds.
  • Analyzed the influence of mutation penetrance and costs on decision intervals.
  • Applied the model to BRCA1/2 gene testing and breast cancer prevention.

Main Results:

  • Established thresholds that delineate the appropriate use of genetic tests.
  • Demonstrated that test/treatment costs and low penetrance narrow the decision interval.
  • Illustrated the model's applicability using BRCA1/2 and breast cancer data.

Conclusions:

  • The derived thresholds provide a framework for rational genetic testing and treatment decisions.
  • Cost-effectiveness and penetrance are critical factors in the utility of genetic screening.
  • This model aids in optimizing the use of genetic information for personalized medicine.