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Decision Thresholds and Changes in Risk for Preventive Treatment.

Christophe Courbage1, Béatrice Rey2

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This study examines preventive treatment decisions considering risk changes and side effects. Ignoring risk variations in treatment threshold calculations can lead to significant cost-benefit analysis errors.

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Area of Science:

  • Decision analysis
  • Health economics
  • Risk management

Background:

  • Preventive treatments often involve potential side effects and changing risk profiles.
  • Evaluating the optimal time for intervention requires careful consideration of disease probability and individual risk preferences.

Purpose of the Study:

  • To investigate the concept of treatment threshold for preventive interventions.
  • To analyze how changes in risk, effectiveness, side effects, disease severity, and comorbidity influence this threshold.

Main Methods:

  • Utilizing nth-order stochastic dominance to define and analyze changes in risk.
  • Developing a framework to assess the impact of riskier environments on treatment decisions.
  • Incorporating mixed risk-averse preferences into the decision-making model.

Main Results:

  • The probability of disease threshold for preventive treatment is sensitive to individual risk preferences and the nature of risk increase.
  • A riskier environment can alter the optimal decision threshold, depending on preference configurations.
  • Neglecting nuanced risk differences leads to substantial errors in cost-benefit analyses for preventive care.

Conclusions:

  • Accurate assessment of risk changes is crucial for determining appropriate preventive treatment thresholds.
  • Cost-benefit analyses for preventive treatments must account for individual preferences and complex risk dynamics.
  • Failure to consider risk configuration can misinform critical public health and clinical decisions.