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

Patient

Volumn 8, Issue 1, 2015, Pages 19-27

  Hollin, Ilene L ^a   Peay, Holly L ^a,b   Bridges, John F P ^a  

^a JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^b Parent Project Muscular Dystrophy   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; BLEEDING; CAREGIVER; CHILD; DUCHENNE MUSCULAR DYSTROPHY; FEMALE; HEALTH SURVEY; HEART ARRHYTHMIA; HUMAN; INTENTION TO TREAT ANALYSIS; KNOWLEDGE; LIFESPAN; MAJOR CLINICAL STUDY; MALE; MOTHER; MUSCLE FUNCTION; MUSCLE WEAKNESS; NAUSEA; PRIORITY JOURNAL; SCORING SYSTEM; SIMULATION; ATTITUDE TO HEALTH; COMPARATIVE STUDY; CONSENSUS; DECISION MAKING; MIDDLE AGED; MUSCULAR DYSTROPHY, DUCHENNE; PATIENT ADVOCACY; PSYCHOLOGY; QUESTIONNAIRE; RISK ASSESSMENT; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA; UNITED STATES;

ADULT; ATTITUDE TO HEALTH; CAREGIVERS; CHILD; CHOICE BEHAVIOR; CONSENSUS; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; MALE; MIDDLE AGED; MUSCULAR DYSTROPHY, DUCHENNE; PATIENT ADVOCACY; RISK ASSESSMENT; SURVEYS AND QUESTIONNAIRES; UNITED STATES;

EID: 84925507572     PISSN: 11781653     EISSN: 11781661     Source Type: Journal    
DOI: 10.1007/s40271-014-0104-x     Document Type: Article

References (47)

1. Bushby K, Finkel R, Birnkrant DJ, Case LE, Clemens PR, Cripe L, et al. Diagnosis and management of Duchenne muscular dystrophy, part 1: diagnosis, and pharmacological and psychosocial management. Lancet Neurol. 2010;9(1):77–93.
2. Eagle M, Baudouin SV, Chandler C, Giddings DR, Bullock R, Bushby K. Survival in Duchenne muscular dystrophy: improvements in life expectancy since 1967 and the impact of home nocturnal ventilation. Neuromuscul Disord. 2002;12(10):926–9.
3. Center for Disease Control and Prevention (CDC). Prevalence of Duchenne/Becker muscular dystrophy among males aged 5–24 years—Four states, 2007. MMWR Morb Wkly Rep. 2009; 58:1119–22.
4. Emery AE. Population frequencies of inherited neuromuscular diseases—a world survey. Neuromuscul Disord. 1991;1(1):19–29.
5. Pangalila RF, van den Bos GA, Stam HJ, van Exel NJA, Brouwer WB, Roebroeck ME. Subjective caregiver burden of parents of adults with Duchenne muscular dystrophy. Disabil Rehabil. 2012;34(12):988–96.
6. Kenneson A, Bobo JK. The effect of caregiving on women in families with Duchenne/Becker muscular dystrophy. Health Soc Care Commun. 2010;18(5):520–8.
7. Larkindale J, Yang W, Hogan PF, Simon CJ, Zhang Y, Jain A, et al. Cost of illness for neuromuscular diseases in the United States. Muscle Nerve. 2014;49(3):431–8.
8. Ouyang L, Grosse SD, Kenneson A. Health care utilization and expenditures for children and young adults with muscular dystrophy in a privately insured population. J Child Neurol. 2008;23(8):883-8.
9. Ouyang L, Grosse SD, Fox MH, Bolen J. A national profile of health care and family impacts of children with muscular dystrophy and special health care needs in the United States. J Child Neurol. 2012;27(5):569–76.
10. Angelini C. The role of corticosteroids in muscular dystrophy: a critical appraisal. Muscle Nerve. 2007;36(4):424–35.
11. Bushby K, Muntoni F, Urtizberea A, Hughes R, Griggs R. Report on the 124th ENMC International Workshop. Treatment of Duchenne muscular dystrophy; defining the gold standards of management in the use of corticosteroids 2–4 April 2004, Naarden, The Netherlands. Neuromuscul Disord. 2004;14(8):526–34.
12. Biggar W, Harris V, Eliasoph L, Alman B. Long-term benefits of deflazacort treatment for boys with Duchenne muscular dystrophy in their second decade. Neuromuscular Disord. 2006;16(4):249–55.
13. Govoni A, Magri F, Brajkovic S, Zanetta C, Faravelli I, Corti S, et al. Ongoing therapeutic trials and outcome measures for Duchenne muscular dystrophy. Cell Mol Life Sci. 2013;70(23):4585–602.
14. Parent Project Muscular Dystrophy. Putting Patients First: Recommendations to speed responsible access to new therapies for Duchenne muscular dystrophy and other rare, serious and life-threatening neurologic disorders. Hackensack; 2013.
15. Parent Project Muscular Dystrophy. Guidance for Industry: Duchenne Muscular Dystrophy Developing Drugs for Treatment over the Spectrum of Disease. Hackensack; 2014.
16. U.S. Food and Drug Administration. Enhancing Benefit-Risk Assessment in Regulatory Decision-Making. Silver Spring; 2014. http://www.fda.gov/ForIndustry/UserFees/PrescriptionDrugUserFee/ucm326192.htm. Accessed June 26 2014.
17. Mullard A. Patient-focused drug development programme takes first steps. Nat Rev Drug Discov. 2013;12(9):651–2.
18. “Prescription Drug User Fee Act Patient-Focused Drug Development; Announcement of Disease Areas for Meetings Conducted in Fiscal Years 2013–2015”. Federal Register 2013; 78:21613–4.
19. Peay HL, Hollin I, Fischer R, Bridges JF. A community-engaged approach to quantifying caregiver preferences for the benefits and risks of emerging therapies for Duchenne muscular dystrophy. Clin Ther. 2014;36(5):624–37.
20. Louviere JJ, Flynn TN. Using best-worst scaling choice experiments to measure public perceptions and preferences for healthcare reform in Australia. Patient. 2010;3(4):275–83.
21. Molassiotis A, Emsley R, Ashcroft D, Caress A, Ellis J, Wagland R, et al. Applying best-worst scaling methodology to establish delivery preferences of a symptom supportive care intervention in patients with lung cancer. Lung Cancer. 2012;77(1):199–204.
22. Marti J. A best-worst scaling survey of adolescents’ level of concern for health and non-health consequences of smoking. Soc Sci Med. 2012;75(1):87–97.
23. Flynn TN, Louviere JJ, Peters TJ, Coast J. Estimating preferences for a dermatology consultation using best-worst scaling: comparison of various methods of analysis. BMC Med Res Methodol. 2008;8(1):76.
24. Swancutt DR, Greenfield SM, Wilson S. Women’s colposcopy experience and preferences: a mixed methods study. BMC Womens Health. 2008;8(1):2.
25. Coast J, Salisbury C, De Berker D, Noble A, Horrocks S, Peters T, et al. Preferences for aspects of a dermatology consultation. Br J Dermatol. 2006;155(2):387–92.
26. Gallego G, Bridges JFP, Flynn T, Blauvelt BM, Niessen LW. Using best-worst scaling in horizon scanning for hepatocellular carcinoma technologies. Int J Technol Assess Health Care. 2012;28(03):339–46. doi:10.1017/S026646231200027X.
27. Finn A, Louviere JJ. Determining the appropriate response to evidence of public concern: the case of food safety. J Public Policy Market. 1992:12–25.
28. Marley AA, Louviere JJ. Some probabilistic models of best, worst, and best-worst choices. J Math Psychol. 2005;49(6):464–80.
29. Bridges J, Kinter E, Kidane L, Heinzen R, McCormick C. Things are looking up since we started listening to patients: recent trends in the application of conjoint analysis in health 1970–2007. Patient. 2008;1(4):273–82.
30. Flynn TN. Valuing citizen and patient preferences in health: recent developments in three types of best-worst scaling. Expert Rev Pharmacoecon Outcomes Res. 2010;10(3):259–67.
31. Ryan M, Watson V, Amaya-Amaya M. Methodological issues in the monetary valuation of benefits in healthcare. Expert Rev Pharmacoecon Outcomes Res. 2003;3(6):717–27.
32. Louviere JJ, Islam T. A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling. J Bus Res. 2008;61(9):903–11.
33. Klose T. The contingent valuation method in health care. Health Policy. 1999;47(2):97–123.
34. Srinivasan V. A conjunctive-compensatory approach to the self-explication of multiattributed preferences. Dec Sci. 1988;19(2):295–305.
35. Jaeger SR, Jørgensen AS, Aaslyng MD, Bredie WL. Best–worst scaling: an introduction and initial comparison with monadic rating for preference elicitation with food products. Food Qual Prefer. 2008;19(6):579–88.
36. Cohen S, Orme B. What’s your preference? Market Res. 2004;16(2):32–7.
37. Cohen S, editor. Maximum difference scaling: improved measures of importance and preference for segmentation. Sawtooth Software Conference Proceedings, Sawtooth Software, Inc; 2003.
38. Potoglou D, Burge P, Flynn T, Netten A, Malley J, Forder J, et al. Best–worst scaling vs. discrete choice experiments: an empirical comparison using social care data. Soc Sci Med. 2011;72(10):1717–27.
39. Flynn TN, Louviere JJ, Peters TJ, Coast J. Best–worst scaling: what it can do for health care research and how to do it. J Health Econ. 2007;26(1):171–89.
40. Bridges JF, Kinter ET, Schmeding A, Rudolph I, Mühlbacher A. Can patients diagnosed with schizophrenia complete choice-based conjoint analysis tasks? Patient. 2011;4(4):267–75.
41. Kuhfeld W. Orthogonal arrays [TS-723]. Cary: SAS [online]. 2010.
42. Kinter ET, Prior TJ, Carswell CI, Bridges JF. A comparison of two experimental design approaches in applying conjoint analysis in patient-centered outcomes research. Patient. 2012;5(4):279–94.
43. Bridges JF, Kinter ET, Kidane L, Heinzen RR, McCormick C. Things are looking up since we started listening to patients. Patient. 2008;1(4):273–82.
44. Reed Johnson F, Lancsar E, Marshall D, Kilambi V, Mühlbacher A, Regier DA et al. Constructing experimental designs for discrete-choice experiments: report of the ISPOR conjoint analysis experimental design good research practices task force. Value Health. 2013;16(1):3–13.
45. Carson RT, Hanemann WM, Kopp RJ, Jon AK, Robert Cameron M, Presser S et al. Referendum design and contingent valuation: the NOAA panel’s no-vote recommendation. Rev Econ Stat. 1998;80(2):335–8.
46. Groothuis PA, Whitehead JC. Does don’t know mean no? Analysis of “don’t know” responses in dichotomous choice contingent valuation questions. Appl Econ. 2002;34(15):1935–40.
47. McFadden D. Conditional logit analysis of qualitative choice behavior. In: Zarembka P, editor. Frontiers in econometrics. New York: Academic Press; 1974. p. 105–42.