Caregiver Preferences for Emerging Duchenne Muscular Dystrophy Treatments: A Comparison of Best-Worst Scaling and Conjoint Analysis

Ilene L. Hollin; Holly L. Peay; John F.P. Bridges

doi:10.1007/s40271-014-0104-x

Caregiver Preferences for Emerging Duchenne Muscular Dystrophy Treatments: A Comparison of Best-Worst Scaling and Conjoint Analysis

Ilene L. Hollin, Holly L. Peay, John F.P. Bridges

Research output: Contribution to journal › Article › peer-review

37 Scopus citations

Abstract

Background: Through Patient-Focused Drug Development, the US Food and Drug Administration (FDA) documents the perspective of patients and caregivers and are currently conducting 20 public meetings on a limited number of disease areas. Parent Project Muscular Dystrophy (PPMD), an advocacy organization for Duchenne muscular dystrophy (DMD), has demonstrated a community-engaged program of preference research that would complement the FDA’s approach.

Objective: Our objective was to compare two stated-preference methods, best-worst scaling (BWS) and conjoint analysis, within a study measuring caregivers’ DMD-treatment preferences.

Methods: Within one survey, two preference-elicitation methods were applied to 18 potential treatments incorporating six attributes and three levels. For each treatment profile, caregivers identified the best and worst feature and intention to use the treatment. We conducted three analyses to compare the elicitation methods using parameter estimates, conditional attribute importance and policy simulations focused on the 18 treatment profiles. For each, concordance between the results was compared using Spearman’s rho.

Results: BWS and conjoint analysis produced similar parameter estimates (p < 0.01); conditional attribute importance (p < 0.01); and policy simulations (p < 0.01). Greatest concordance was observed for the benefit and risk parameters, with differences observed for nausea and knowledge about the drug—where a lack of monotonicity was observed when using conjoint analysis.

Conclusions: The observed concordance between approaches demonstrates the reliability of the stated-preference methods. Given the simplicity of combining BWS and conjoint analysis on single profiles, a combination approach is easily adopted. Minor irregularities for the conjoint-analysis results could not be explained by additional analyses and needs to be the focus of future research.

Original language	English (US)
Pages (from-to)	19-27
Number of pages	9
Journal	Patient
Volume	8
Issue number	1
DOIs	https://doi.org/10.1007/s40271-014-0104-x
State	Published - Feb 2014
Externally published	Yes

ASJC Scopus subject areas

Nursing (miscellaneous)

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title = "Caregiver Preferences for Emerging Duchenne Muscular Dystrophy Treatments: A Comparison of Best-Worst Scaling and Conjoint Analysis",

abstract = "Background: Through Patient-Focused Drug Development, the US Food and Drug Administration (FDA) documents the perspective of patients and caregivers and are currently conducting 20 public meetings on a limited number of disease areas. Parent Project Muscular Dystrophy (PPMD), an advocacy organization for Duchenne muscular dystrophy (DMD), has demonstrated a community-engaged program of preference research that would complement the FDA{\textquoteright}s approach.Objective: Our objective was to compare two stated-preference methods, best-worst scaling (BWS) and conjoint analysis, within a study measuring caregivers{\textquoteright} DMD-treatment preferences.Methods: Within one survey, two preference-elicitation methods were applied to 18 potential treatments incorporating six attributes and three levels. For each treatment profile, caregivers identified the best and worst feature and intention to use the treatment. We conducted three analyses to compare the elicitation methods using parameter estimates, conditional attribute importance and policy simulations focused on the 18 treatment profiles. For each, concordance between the results was compared using Spearman{\textquoteright}s rho.Results: BWS and conjoint analysis produced similar parameter estimates (p < 0.01); conditional attribute importance (p < 0.01); and policy simulations (p < 0.01). Greatest concordance was observed for the benefit and risk parameters, with differences observed for nausea and knowledge about the drug—where a lack of monotonicity was observed when using conjoint analysis.Conclusions: The observed concordance between approaches demonstrates the reliability of the stated-preference methods. Given the simplicity of combining BWS and conjoint analysis on single profiles, a combination approach is easily adopted. Minor irregularities for the conjoint-analysis results could not be explained by additional analyses and needs to be the focus of future research.",

author = "Hollin, {Ilene L.} and Peay, {Holly L.} and Bridges, {John F.P.}",

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doi = "10.1007/s40271-014-0104-x",

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AU - Peay, Holly L.

AU - Bridges, John F.P.

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Y1 - 2014/2

N2 - Background: Through Patient-Focused Drug Development, the US Food and Drug Administration (FDA) documents the perspective of patients and caregivers and are currently conducting 20 public meetings on a limited number of disease areas. Parent Project Muscular Dystrophy (PPMD), an advocacy organization for Duchenne muscular dystrophy (DMD), has demonstrated a community-engaged program of preference research that would complement the FDA’s approach.Objective: Our objective was to compare two stated-preference methods, best-worst scaling (BWS) and conjoint analysis, within a study measuring caregivers’ DMD-treatment preferences.Methods: Within one survey, two preference-elicitation methods were applied to 18 potential treatments incorporating six attributes and three levels. For each treatment profile, caregivers identified the best and worst feature and intention to use the treatment. We conducted three analyses to compare the elicitation methods using parameter estimates, conditional attribute importance and policy simulations focused on the 18 treatment profiles. For each, concordance between the results was compared using Spearman’s rho.Results: BWS and conjoint analysis produced similar parameter estimates (p < 0.01); conditional attribute importance (p < 0.01); and policy simulations (p < 0.01). Greatest concordance was observed for the benefit and risk parameters, with differences observed for nausea and knowledge about the drug—where a lack of monotonicity was observed when using conjoint analysis.Conclusions: The observed concordance between approaches demonstrates the reliability of the stated-preference methods. Given the simplicity of combining BWS and conjoint analysis on single profiles, a combination approach is easily adopted. Minor irregularities for the conjoint-analysis results could not be explained by additional analyses and needs to be the focus of future research.

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Caregiver Preferences for Emerging Duchenne Muscular Dystrophy Treatments: A Comparison of Best-Worst Scaling and Conjoint Analysis

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