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Method for Calculating the Simultaneous Maximum Acceptable Risk Threshold (SMART) from Discrete-Choice Experiment Benefit-Risk Studies

Author

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  • Angelyn Otteson Fairchild

    (University of North Carolina at Chapel Hill, Chapel Hill, NC, USA)

  • Shelby D. Reed

    (Duke Clinical Research Institute, Durham, NC, USA)

  • Juan Marcos Gonzalez

    (Duke Clinical Research Institute, Durham, NC, USA)

Abstract

Background Medical decisions require weighing expected benefits of treatment against multiple adverse outcomes under uncertainty (i.e., risks) that must be accepted as a bundle. However, conventional maximum acceptable risk (MAR) estimates derived from discrete-choice experiment benefit-risk studies evaluate the acceptance of individual risks, assuming other risks are fixed, potentially leading decision makers to misinterpret levels of risk acceptance. Design Using simulations and a published discrete-choice experiment, we demonstrate a method for identifying multidimensional risk-tolerance measures given a treatment level of benefit. Results Simultaneous Maximum Acceptable Risk Thresholds (SMART) represents combinations of risks that would be jointly accepted in exchange for specific treatment benefits. The framework shows how the expectation of utility associated with treatments that involve multiple risks are related even when preferences for potential adverse events are independent. We find that the form of the marginal effects of adverse-event probabilities on the expected utility of treatment determines the magnitude of differences between SMART and conventional single-outcome MAR estimates. Limitations Preferences for potential adverse events not considered in a study or preferences for adverse-event attributes held constant in risk-tolerance calculations may affect estimated risk tolerance. Further research is needed to understand the right balance between realistically reflecting clinical treatments with many potential adverse events and the cognitive burden of evaluating risk-risk tradeoffs in research and in practice. Conclusions and Implications SMART analysis should be considered in preference studies evaluating the joint acceptance of multiple potential adverse events. Highlights Conventional approaches to calculate maximum-acceptable risk (MAR) using discrete-choice experiment data account for 1 adverse-event risk at a time, requiring that decision makers infer the acceptability of treatments when patients are exposed to multiple risks simultaneously. The Simultaneous Maximum Acceptable Risk Threshold (SMART) maps combinations of adverse-event risks that would be jointly acceptable given a specific treatment benefit and provides a transparent and precise portrayal of acceptance of multiple risks. Risk levels that would be accepted using individual MAR estimates might not be acceptable when simultaneous risks are considered, especially when marginal expected disutility of risk is decreasing nonlinearly with risk probabilities. Preference researchers should calculate SMARTs in any discrete-choice study in which 2 or more adverse-event risks are presented, particularly if risk preferences are nonlinear.

Suggested Citation

  • Angelyn Otteson Fairchild & Shelby D. Reed & Juan Marcos Gonzalez, 2023. "Method for Calculating the Simultaneous Maximum Acceptable Risk Threshold (SMART) from Discrete-Choice Experiment Benefit-Risk Studies," Medical Decision Making, , vol. 43(2), pages 227-238, February.
    • Handle: RePEc:sae:medema:v:43:y:2023:i:2:p:227-238
    DOI: 10.1177/0272989X221132266
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    References listed on IDEAS

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    1. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    2. A. Brett Hauber & Angelyn Fairchild & F. Reed Johnson, 2013. "Quantifying Benefit–Risk Preferences for Medical Interventions: An Overview of a Growing Empirical Literature," Applied Health Economics and Health Policy, Springer, vol. 11(4), pages 319-329, August.
    3. George Van Houtven & F. Reed Johnson & Vikram Kilambi & A. Brett Hauber, 2011. "Eliciting Benefit–Risk Preferences and Probability-Weighted Utility Using Choice-Format Conjoint Analysis," Medical Decision Making, , vol. 31(3), pages 469-480, May.
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