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Eliciting benefit-risk preferences and probability-weighted utility using choice-format conjoint analysis.

Publication ,  Journal Article
Van Houtven, G; Johnson, FR; Kilambi, V; Hauber, AB
Published in: Med Decis Making
2011

This study applies conjoint analysis to estimate health-related benefit-risk tradeoffs in a non-expected-utility framework. We demonstrate how this method can be used to test for and estimate nonlinear weighting of adverse-event probabilities and we explore the implications of nonlinear weighting on maximum acceptable risk (MAR) measures of risk tolerance. We obtained preference data from 570 Crohn's disease patients using a web-enabled conjoint survey. Respondents were presented with choice tasks involving treatment options that involve different efficacy benefits and different mortality risks for 3 possible side effects. Using conditional logit maximum likelihood estimation, we estimate preference parameters using 3 models that allow for nonlinear preference weighting of risks--a categorical model, a simple-weighting model, and a rank dependent utility (RDU) model. For the second 2 models we specify and jointly estimate 1- and 2-parameter probability weighting functions. Although the 2-parameter functions are more flexible, estimation of the 1-parameter functions generally performed better. Despite well-known conceptual limitations, the simple-weighting model allows us to estimate weighting function parameters that vary across 3 risk types, and we find some evidence of statistically significant differences across risks. The parameter estimates from RDU model with the single-parameter weighting function provide the most robust estimates of MAR. For an improvement in Crohn's symptom severity from moderate and mild, we estimate maximum 10-year mortality risk tolerances ranging from 2.6% to 7.1%. Our results provide further the evidence that quantitative benefit-risk analysis used to evaluate medical interventions should account explicitly for the nonlinear probability weighting of preferences.

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Published In

Med Decis Making

DOI

EISSN

1552-681X

Publication Date

2011

Volume

31

Issue

3

Start / End Page

469 / 480

Location

United States

Related Subject Headings

  • Uncertainty
  • Survival Analysis
  • Severity of Illness Index
  • Risk Assessment
  • Probability
  • Patient Satisfaction
  • Nonlinear Dynamics
  • Models, Statistical
  • Humans
  • Health Status Indicators
 

Citation

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Van Houtven, G., Johnson, F. R., Kilambi, V., & Hauber, A. B. (2011). Eliciting benefit-risk preferences and probability-weighted utility using choice-format conjoint analysis. Med Decis Making, 31(3), 469–480. https://doi.org/10.1177/0272989X10386116
Van Houtven, George, F Reed Johnson, Vikram Kilambi, and A Brett Hauber. “Eliciting benefit-risk preferences and probability-weighted utility using choice-format conjoint analysis.Med Decis Making 31, no. 3 (2011): 469–80. https://doi.org/10.1177/0272989X10386116.
Van Houtven G, Johnson FR, Kilambi V, Hauber AB. Eliciting benefit-risk preferences and probability-weighted utility using choice-format conjoint analysis. Med Decis Making. 2011;31(3):469–80.
Van Houtven, George, et al. “Eliciting benefit-risk preferences and probability-weighted utility using choice-format conjoint analysis.Med Decis Making, vol. 31, no. 3, 2011, pp. 469–80. Pubmed, doi:10.1177/0272989X10386116.
Van Houtven G, Johnson FR, Kilambi V, Hauber AB. Eliciting benefit-risk preferences and probability-weighted utility using choice-format conjoint analysis. Med Decis Making. 2011;31(3):469–480.
Journal cover image

Published In

Med Decis Making

DOI

EISSN

1552-681X

Publication Date

2011

Volume

31

Issue

3

Start / End Page

469 / 480

Location

United States

Related Subject Headings

  • Uncertainty
  • Survival Analysis
  • Severity of Illness Index
  • Risk Assessment
  • Probability
  • Patient Satisfaction
  • Nonlinear Dynamics
  • Models, Statistical
  • Humans
  • Health Status Indicators