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Published in: Orphanet Journal of Rare Diseases 1/2016

Open Access 01-12-2016 | Research

Quantifying benefit-risk preferences for new medicines in rare disease patients and caregivers

Authors: T. Morel, S. Aymé, D. Cassiman, S. Simoens, M. Morgan, M. Vandebroek

Published in: Orphanet Journal of Rare Diseases | Issue 1/2016

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Abstract

Background

Rare disease patients and caregivers face uncommon, serious, debilitating conditions often characterised by poor prognosis and limited treatment options. This study aimed to explore what they consider of value when choosing between hypothetical therapeutic options and to quantify both their benefit-risk preferences and the influence of disease context.

Methods

A mixed-methods survey with patients and caregivers was conducted in the United Kingdom across a range of rare diseases. Discrete-choice experiments that compared hypothetical treatment profiles of benefits and risks were used to measure respondent preferences across a set of seven attributes related to health outcomes, safety, and process of care. Bespoke questions on current disease management and the joint use of the 12-item WHODAS 2.0 questionnaire and of two Likert scales capturing self- and proxy-assessed disease-induced threat to life and impairment were implemented to describe disease context. Additionally, qualitative insights on the definitions of value and risk were collected from respondents.

Results

Final study sample included 721 patients and 152 informal caregivers, across 52 rare diseases. When choosing between hypothetical novel treatments for rare diseases, respondents attributed most importance to drug response, risk of serious side effects, and the ability to conduct usual activities while on treatment. In contrast, attributes related to treatment modalities were the least important. Respondents expressed a willingness to accept risks in hopes of finding some benefit, such as a higher chance of drug response or greater health improvement potential. Increasing disease severity, impairment or disability, and the lack of effective therapeutic options were shown to raise significantly the willingness to gain benefit through increased risk.

Conclusions

This is the first study performing a quantitative discrete choice experiment amongst patients and caregivers across 52 rare conditions. It enables a more detailed understanding of the relationship between disease context, treatment attributes and the degree of risk respondents are willing to take to gain a specific degree of benefit. Researchers of novel therapeutics for rare diseases should be encouraged to invest in preference elicitation studies to generate rigorous patient evidence and specific regulatory guidance should be issued to acknowledge their importance and their use in marketing authorisations.
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Literature
2.
go back to reference Eichler HG, Bloechl-Daum B, Brasseur D, Breckenridge A, Leufkens H, Raine J, et al. The risks of risk aversion in drug regulation. Nat Rev Drug Discov. 2013;12:907–16.CrossRefPubMed Eichler HG, Bloechl-Daum B, Brasseur D, Breckenridge A, Leufkens H, Raine J, et al. The risks of risk aversion in drug regulation. Nat Rev Drug Discov. 2013;12:907–16.CrossRefPubMed
3.
go back to reference Chakradhar S. Training on trials: patients taught the language of drug development. Nat Med. 2015;21:209–10.CrossRefPubMed Chakradhar S. Training on trials: patients taught the language of drug development. Nat Med. 2015;21:209–10.CrossRefPubMed
4.
go back to reference Pushparajah DS, Geissler J, Westergaard N. EUPATI: collaboration between patients, academia and industry to champion the infromed patient in the research and development of medicines. J Med DevSci. 2015;1:74–80. Pushparajah DS, Geissler J, Westergaard N. EUPATI: collaboration between patients, academia and industry to champion the infromed patient in the research and development of medicines. J Med DevSci. 2015;1:74–80.
5.
go back to reference Barry MJ, Edgman-Levitan S. Shared decision making--pinnacle of patient-centered care. N Engl J Med. 2012;366:780–1.CrossRefPubMed Barry MJ, Edgman-Levitan S. Shared decision making--pinnacle of patient-centered care. N Engl J Med. 2012;366:780–1.CrossRefPubMed
6.
go back to reference Stacey D, Legare F, Col NF, Bennett CL, Barry MJ, Eden KB, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;1:CD001431.PubMed Stacey D, Legare F, Col NF, Bennett CL, Barry MJ, Eden KB, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;1:CD001431.PubMed
7.
go back to reference Minvielle E, Waelli M, Sicotte C, Kimberly JR. Managing customization in health care: a framework derived from the services sector literature. Health Policy. 2014;117:216–27.CrossRefPubMed Minvielle E, Waelli M, Sicotte C, Kimberly JR. Managing customization in health care: a framework derived from the services sector literature. Health Policy. 2014;117:216–27.CrossRefPubMed
8.
go back to reference Eaton S, Collins A, Coulter A, Elwyn G, Grazin N, Roberts S. Putting patients first. BMJ. 2012;344:e2006.CrossRefPubMed Eaton S, Collins A, Coulter A, Elwyn G, Grazin N, Roberts S. Putting patients first. BMJ. 2012;344:e2006.CrossRefPubMed
9.
go back to reference Coulter A, Collins A. Making shared decision-making a reality: no decision about me, without me. London: The King’s Fund; 2011. Coulter A, Collins A. Making shared decision-making a reality: no decision about me, without me. London: The King’s Fund; 2011.
10.
go back to reference Health Technology Assessment international (HTAi). Completing a Patient Group Submission Template: Guidance for Patient Organisations for Health Technology Assessment and Appraisal of Medicines. 2015. Health Technology Assessment international (HTAi). Health Technology Assessment international (HTAi). Completing a Patient Group Submission Template: Guidance for Patient Organisations for Health Technology Assessment and Appraisal of Medicines. 2015. Health Technology Assessment international (HTAi).
11.
go back to reference European Medicines Agency (EMA). Road map to 2015. The european medicines Agency’s contribution to science, medicines and health. London: European Medicines Agency (EMA); 2010. European Medicines Agency (EMA). Road map to 2015. The european medicines Agency’s contribution to science, medicines and health. London: European Medicines Agency (EMA); 2010.
12.
go back to reference European Medicines Agency (EMA). Incorporating patients’ views during evaluation of benefit-risk by the EMA scientific committees. EMA/413422/2013. London: European Medicines Agency (EMA); 2014. European Medicines Agency (EMA). Incorporating patients’ views during evaluation of benefit-risk by the EMA scientific committees. EMA/413422/2013. London: European Medicines Agency (EMA); 2014.
13.
go back to reference European Medicines Agency (EMA). Pilot phase to involve patients in benefit/risk discussions at CHMP meetings. EMA/372554/2014. London: European Medicines Agency (EMA); 2014. European Medicines Agency (EMA). Pilot phase to involve patients in benefit/risk discussions at CHMP meetings. EMA/372554/2014. London: European Medicines Agency (EMA); 2014.
14.
go back to reference European Medicines Agency (EMA). Final CHMP work programme for 2011–2013 . EMA/CHMP/65166/2011. London: European Medicines Agency (EMA); 2011. European Medicines Agency (EMA). Final CHMP work programme for 2011–2013 . EMA/CHMP/65166/2011. London: European Medicines Agency (EMA); 2011.
15.
go back to reference US Department of Health and Human Services FaDAF. Structured approach to benefit-risk assessment in drug regulatory decision-making. Draft PDUFA V implementation plan. Washington: Food and Drug Administration (FDA); 2013. 16-1-2015. US Department of Health and Human Services FaDAF. Structured approach to benefit-risk assessment in drug regulatory decision-making. Draft PDUFA V implementation plan. Washington: Food and Drug Administration (FDA); 2013. 16-1-2015.
16.
go back to reference US Department of Health and Human Services FaDAF. Prescription drug user Fee Act patient-focused drug development; announcement of disease areas for meetings conducted in fiscal years 2013–2015. Vol. 78, No. 70. 11-4-2013. Washington: Federal Register; 2015. US Department of Health and Human Services FaDAF. Prescription drug user Fee Act patient-focused drug development; announcement of disease areas for meetings conducted in fiscal years 2013–2015. Vol. 78, No. 70. 11-4-2013. Washington: Federal Register; 2015.
17.
go back to reference European Medicines Agency (EMA). Regulatory and methodological standards to improve benefit-risk evaluation of medicines. Workshop report, EMA/141854/2014. London: European Medicines Agency (EMA); 2014. European Medicines Agency (EMA). Regulatory and methodological standards to improve benefit-risk evaluation of medicines. Workshop report, EMA/141854/2014. London: European Medicines Agency (EMA); 2014.
18.
go back to reference Genetic Alliance UK. New medicines for serious conditions: weighing the risks and benefits. The verdict of a jury of patients. London: Genetic Alliance UK; 2012. 16-1-2015. Genetic Alliance UK. New medicines for serious conditions: weighing the risks and benefits. The verdict of a jury of patients. London: Genetic Alliance UK; 2012. 16-1-2015.
19.
go back to reference Parent Project Muscular Dystrophy. The Duchenne community imperatives for the guidance for industry on Duchenne muscular dystrophy: developing drugs for treatment over the spectrum of disease. Hackensak: Parent Project Muscular Dystrophy; 2014. 16-1-2015. Parent Project Muscular Dystrophy. The Duchenne community imperatives for the guidance for industry on Duchenne muscular dystrophy: developing drugs for treatment over the spectrum of disease. Hackensak: Parent Project Muscular Dystrophy; 2014. 16-1-2015.
20.
go back to reference US Department of Health and Human Services FaDAF. Report: complex issues in developing drugs and biological products for rare diseases and accelerating the development of therapies for pediatric rare diseases, including strategic plan: accelerating the development of therapies for pediatric rare diseases. Washington: Food and Drug Administration (FDA); 2014. US Department of Health and Human Services FaDAF. Report: complex issues in developing drugs and biological products for rare diseases and accelerating the development of therapies for pediatric rare diseases, including strategic plan: accelerating the development of therapies for pediatric rare diseases. Washington: Food and Drug Administration (FDA); 2014.
21.
go back to reference de Bekker-Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ. 2012;21:145–72.CrossRefPubMed de Bekker-Grob EW, Ryan M, Gerard K. Discrete choice experiments in health economics: a review of the literature. Health Econ. 2012;21:145–72.CrossRefPubMed
22.
go back to reference Bridges JF, Hauber AB, Marshall D, Lloyd A, Prosser LA, Regier DA, et al. Conjoint analysis applications in health--a checklist: a report of the ISPOR good research practices for conjoint analysis task force. Value Health. 2011;14:403–13.CrossRefPubMed Bridges JF, Hauber AB, Marshall D, Lloyd A, Prosser LA, Regier DA, et al. Conjoint analysis applications in health--a checklist: a report of the ISPOR good research practices for conjoint analysis task force. Value Health. 2011;14:403–13.CrossRefPubMed
23.
go back to reference Ryan M, Gerard K. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl Health Econ Health Policy. 2003;2:55–64.PubMed Ryan M, Gerard K. Using discrete choice experiments to value health care programmes: current practice and future research reflections. Appl Health Econ Health Policy. 2003;2:55–64.PubMed
24.
go back to reference Marshall D, Bridges JF, Hauber B, Cameron R, Donnalley L, Fyie K, et al. Conjoint analysis applications in health - How are studies being designed and reported?: an update on current practice in the published literature between 2005 and 2008. Patient. 2010;3:249–56.CrossRefPubMed Marshall D, Bridges JF, Hauber B, Cameron R, Donnalley L, Fyie K, et al. Conjoint analysis applications in health - How are studies being designed and reported?: an update on current practice in the published literature between 2005 and 2008. Patient. 2010;3:249–56.CrossRefPubMed
26.
go back to reference Johnson FR. Why not ask?: measuring patient preferences for healthcare decision making. Patient. 2008;1:245–8.CrossRefPubMed Johnson FR. Why not ask?: measuring patient preferences for healthcare decision making. Patient. 2008;1:245–8.CrossRefPubMed
27.
go back to reference Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making: a user’s guide. Pharmacoecon. 2008;26:661–77.CrossRef Lancsar E, Louviere J. Conducting discrete choice experiments to inform healthcare decision making: a user’s guide. Pharmacoecon. 2008;26:661–77.CrossRef
28.
go back to reference Bridges JF, Kinter ET, Kidane L, Heinzen RR, McCormick C. Things are looking up since we started listening to patients: trends in the application of conjoint analysis in health 1982–2007. Patient. 2008;1:273–82.CrossRefPubMed Bridges JF, Kinter ET, Kidane L, Heinzen RR, McCormick C. Things are looking up since we started listening to patients: trends in the application of conjoint analysis in health 1982–2007. Patient. 2008;1:273–82.CrossRefPubMed
29.
go back to reference Harrison M, Rigby D, Vass C, Flynn T, Louviere J, Payne K. Risk as an attribute in discrete choice experiments: a systematic review of the literature. Patient. 2014;7:151–70.CrossRefPubMed Harrison M, Rigby D, Vass C, Flynn T, Louviere J, Payne K. Risk as an attribute in discrete choice experiments: a systematic review of the literature. Patient. 2014;7:151–70.CrossRefPubMed
30.
go back to reference Hauber AB, Fairchild AO, Reed J. Quantifying benefit-risk preferences for medical interventions: an overview of a growing empirical literature. Appl Health Econ Health Policy. 2013;11:319–29.CrossRef Hauber AB, Fairchild AO, Reed J. Quantifying benefit-risk preferences for medical interventions: an overview of a growing empirical literature. Appl Health Econ Health Policy. 2013;11:319–29.CrossRef
31.
go back to reference Train K. Discrete choice methods with simulation. Cambridge: Cambridge University Press; 2009.CrossRef Train K. Discrete choice methods with simulation. Cambridge: Cambridge University Press; 2009.CrossRef
32.
go back to reference Hensher DA, Greene WH. The Mixed Logit model: the state of practice. Transportation. 2003;30:133–76.CrossRef Hensher DA, Greene WH. The Mixed Logit model: the state of practice. Transportation. 2003;30:133–76.CrossRef
33.
go back to reference Ryan M, Gerard K, Amaya-Amaya M. Using discrete choice experiments to value health and health care. Dordrecht: Springer; 2008.CrossRef Ryan M, Gerard K, Amaya-Amaya M. Using discrete choice experiments to value health and health care. Dordrecht: Springer; 2008.CrossRef
34.
go back to reference Louviere J, Hensher D, Swait J. Stated choice methods: analysis and applications. Cambridge: Cambridge University Press; 2000.CrossRef Louviere J, Hensher D, Swait J. Stated choice methods: analysis and applications. Cambridge: Cambridge University Press; 2000.CrossRef
35.
go back to reference Hensher DA, Rose J, Greene W. Applied choice analysis: a primer. Cambridge: Cambridge University Press; 2005.CrossRef Hensher DA, Rose J, Greene W. Applied choice analysis: a primer. Cambridge: Cambridge University Press; 2005.CrossRef
36.
go back to reference Pickard AS, Knight SJ. Proxy evaluation of health-related quality of life: a conceptual framework for understanding multiple proxy perspectives. Med Care. 2005;43:493–9.CrossRefPubMedPubMedCentral Pickard AS, Knight SJ. Proxy evaluation of health-related quality of life: a conceptual framework for understanding multiple proxy perspectives. Med Care. 2005;43:493–9.CrossRefPubMedPubMedCentral
37.
go back to reference Ustun TB, Chatterji S, Kostanjsek N, Rehm J, Kennedy C, Epping-Jordan J, et al. Developing the world health organization disability assessment schedule 2.0. Bull World Health Organ. 2010;88:815–23.CrossRefPubMedPubMedCentral Ustun TB, Chatterji S, Kostanjsek N, Rehm J, Kennedy C, Epping-Jordan J, et al. Developing the world health organization disability assessment schedule 2.0. Bull World Health Organ. 2010;88:815–23.CrossRefPubMedPubMedCentral
38.
go back to reference Ustun TB, Kastanjsek N, Chatterji S, Rehm J. Measuring health and disability. Manual for the WHO disability assessment schedule. WHODAS 2.0. Geneva: World Health Organisation; 2010. Ustun TB, Kastanjsek N, Chatterji S, Rehm J. Measuring health and disability. Manual for the WHO disability assessment schedule. WHODAS 2.0. Geneva: World Health Organisation; 2010.
39.
go back to reference Bliemer MCJ, Rose JM. Construction of experimental designs for mixed logit models allowing for correlation across choice observations. Transp Res B. 2010;44:720–34.CrossRef Bliemer MCJ, Rose JM. Construction of experimental designs for mixed logit models allowing for correlation across choice observations. Transp Res B. 2010;44:720–34.CrossRef
40.
go back to reference Kessels R, Goos P, Vandebroek M. A comparison of criteria to design efficient choice experiments. J Mark Res. 2006;43:419.CrossRef Kessels R, Goos P, Vandebroek M. A comparison of criteria to design efficient choice experiments. J Mark Res. 2006;43:419.CrossRef
41.
go back to reference Orme J. Getting started with conjoint analysis: strategies for product design and pricing research. Madison: Research Publishers LLC; 2006. Orme J. Getting started with conjoint analysis: strategies for product design and pricing research. Madison: Research Publishers LLC; 2006.
42.
go back to reference Yu J, Goos P, Vandebroek M. Efficient conjoint choice designs in the presence of respondent heterogeneity. Mark Sci. 2009;28:122–35.CrossRef Yu J, Goos P, Vandebroek M. Efficient conjoint choice designs in the presence of respondent heterogeneity. Mark Sci. 2009;28:122–35.CrossRef
43.
go back to reference Yu J, Goos P, Vandebroek M. Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity. Int J Res Mark. 2011;28:378–88.CrossRef Yu J, Goos P, Vandebroek M. Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity. Int J Res Mark. 2011;28:378–88.CrossRef
44.
go back to reference Yu J, Goos P, Vandebroek M. A comparison of different Bayesian design criteria for setting up stated preference studies. Transp Res B. 2012;46:789–807.CrossRef Yu J, Goos P, Vandebroek M. A comparison of different Bayesian design criteria for setting up stated preference studies. Transp Res B. 2012;46:789–807.CrossRef
45.
46.
go back to reference Kakkis ED, O’Donovan M, Cox G, Hayes M, Goodsaid F, Tandon PK, et al. Recommendations for the development of rare disease drugs using the accelerated approval pathway and for qualifying biomarkers as primary endpoints. Orphanet J Rare Dis. 2015;10:16.CrossRefPubMedPubMedCentral Kakkis ED, O’Donovan M, Cox G, Hayes M, Goodsaid F, Tandon PK, et al. Recommendations for the development of rare disease drugs using the accelerated approval pathway and for qualifying biomarkers as primary endpoints. Orphanet J Rare Dis. 2015;10:16.CrossRefPubMedPubMedCentral
47.
48.
go back to reference US Department of Health and Human Services FaDAF. Paving the Way for Personalized Medicine. FDA’s Role in a New Era of Medical Product Development. Washington D.C., USA: U.S. Food and Drug Administration; 2013. US Department of Health and Human Services FaDAF. Paving the Way for Personalized Medicine. FDA’s Role in a New Era of Medical Product Development. Washington D.C., USA: U.S. Food and Drug Administration; 2013.
49.
go back to reference National Organization for Rare Disorders (NORD). Letter to the U.S. Senate HELP Committee in support of the Advancing Targeted Therapies for Rare Diseases Act. 2015. National Organization for Rare Disorders (NORD). Letter to the U.S. Senate HELP Committee in support of the Advancing Targeted Therapies for Rare Diseases Act. 2015.
50.
go back to reference Douglas M, Wildavsky A. Risk and culture: an essay on the selection of technical and environmental dangers. Berkeley: Berkeley: University of California Press; 1982. Douglas M, Wildavsky A. Risk and culture: an essay on the selection of technical and environmental dangers. Berkeley: Berkeley: University of California Press; 1982.
51.
go back to reference Krimsky S, Golding D. Social theories of risk. Westport: Praeger-Greenwood; 1992. Krimsky S, Golding D. Social theories of risk. Westport: Praeger-Greenwood; 1992.
52.
go back to reference Douglas M. Risk as a forensic resource. Daedalus Proc Am Acad Arts Sci. 1990;119:1–16. Douglas M. Risk as a forensic resource. Daedalus Proc Am Acad Arts Sci. 1990;119:1–16.
53.
go back to reference Kesselheim AS, McGraw S, Thompson L, O’Keefe K, Gagne JJ. Development and use of new therapeutics for rare diseases: views from patients, caregivers, and advocates. Patient. 2015;8:75–84.CrossRefPubMed Kesselheim AS, McGraw S, Thompson L, O’Keefe K, Gagne JJ. Development and use of new therapeutics for rare diseases: views from patients, caregivers, and advocates. Patient. 2015;8:75–84.CrossRefPubMed
54.
go back to reference 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;36:624–37.CrossRefPubMed 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;36:624–37.CrossRefPubMed
55.
go back to reference Woodcock J. PDUFA V Clinical Outcome Assessments Public workshop. 2015. Woodcock J. PDUFA V Clinical Outcome Assessments Public workshop. 2015.
56.
go back to reference Walton MK, Powers III JH, Hobart J, Patrick D, Marquis P, Vamvakas S, et al. Clinical outcome assessments: conceptual foundation-report of the ISPOR clinical outcomes assessment - emerging good practices for outcomes research task force. Value Health. 2015;18:741–52.CrossRefPubMed Walton MK, Powers III JH, Hobart J, Patrick D, Marquis P, Vamvakas S, et al. Clinical outcome assessments: conceptual foundation-report of the ISPOR clinical outcomes assessment - emerging good practices for outcomes research task force. Value Health. 2015;18:741–52.CrossRefPubMed
57.
go back to reference Frank L, Basch E, Selby JV. The PCORI perspective on patient-centered outcomes research. JAMA. 2014;312:1513–4.CrossRefPubMed Frank L, Basch E, Selby JV. The PCORI perspective on patient-centered outcomes research. JAMA. 2014;312:1513–4.CrossRefPubMed
58.
go back to reference Bartlett SJ, Barnes T, McIvor RA. Integrating patients into meaningful real-world research. Ann Am Thorac Soc. 2014;11 Suppl 2:S112–7.CrossRefPubMed Bartlett SJ, Barnes T, McIvor RA. Integrating patients into meaningful real-world research. Ann Am Thorac Soc. 2014;11 Suppl 2:S112–7.CrossRefPubMed
59.
go back to reference International Rare Diseases Research Consortium (IRDiRC). Preparatory Document for Workshop on Patient-Centred Outcome Measures Initiatives in the Field of Rare Diseases. 2-10-2015. International Rare Diseases Research Consortium (IRDiRC). Preparatory Document for Workshop on Patient-Centred Outcome Measures Initiatives in the Field of Rare Diseases. 2-10-2015.
Metadata
Title
Quantifying benefit-risk preferences for new medicines in rare disease patients and caregivers
Authors
T. Morel
S. Aymé
D. Cassiman
S. Simoens
M. Morgan
M. Vandebroek
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Orphanet Journal of Rare Diseases / Issue 1/2016
Electronic ISSN: 1750-1172
DOI
https://doi.org/10.1186/s13023-016-0444-9

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