Ilene L Hollin1, Holly L Peay, John F P Bridges. 1. Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, 624 N. Broadway, Rm 689, Baltimore, MD, 21205, USA, ihollin1@jhu.edu.
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.
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.
Authors: Susan dosReis; Xinyi Ng; Emily Frosch; Gloria Reeves; Charles Cunningham; John F P Bridges Journal: Patient Date: 2015-10 Impact factor: 3.883
Authors: Keren Ladin; Joanna Emerson; Zeeshan Butt; Elisa J Gordon; Douglas W Hanto; Jennifer Perloff; Norman Daniels; Tara A Lavelle Journal: J Med Ethics Date: 2018-06-28 Impact factor: 2.903
Authors: Xinyi Ng; John F P Bridges; Melissa M Ross; Emily Frosch; Gloria Reeves; Charles E Cunningham; Susan dosReis Journal: Patient Date: 2017-04 Impact factor: 3.883