Developing and piloting an instrument to prioritize the worries of patients with acute myeloid leukemia

John Fp Bridges, Allison H Oakes, Crystal A Reinhart, Ernest Voyard, Bernadette O'Donoghue, John Fp Bridges, Allison H Oakes, Crystal A Reinhart, Ernest Voyard, Bernadette O'Donoghue

Abstract

Background: Acute myeloid leukemia (AML) is a rapidly progressing blood cancer for which new treatments are needed. We sought to promote patient-focused drug development (PFDD) for AML by developing and piloting an instrument to prioritize the worries of patients with AML.

Patients and methods: An innovative community-centered approach was used to engage expert and community stakeholders in the development, pretesting, pilot testing, and dissemination of a novel best-worst scaling instrument. Patient worries were identified through individual interviews (n=15) and group calls. The instrument was developed through rigorous pretesting (n=13) and then piloted among patients and caregivers engaged in this study (n=25). Priorities were assessed using best-worst scores (spanning from +1 to -1) representing the relative number of times that items were endorsed as the most and the least worrying. All findings were presented at a PFDD meeting at the US Food and Drug Administration (FDA) that was attended by >80 stakeholders.

Results: The final instrument included 13 worries spanning issues such as decision making, treatment delivery, physical impacts, and psychosocial effects. Patients and caregivers most prioritized worries about dying from their disease (best minus worst [BW] score=0.73), long-term side effects (BW=0.28), and time in hospital (BW=0.25).

Conclusion: Community-centered approaches are valuable in designing and executing PFDD meetings and associated quantitative surveys to document the experience of patients. Expert and community stakeholders welcomed the opportunity to share their experiences with the FDA and strongly endorsed implementing this survey nationally.

Keywords: acute myeloid leukemia; best–worst scaling; community engagement; patient-focused drug development; stated-preference.

Conflict of interest statement

Disclosure Ernest Voyard and Bernadette O’Donoghue are employees of the LLS. The other authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Project governance.
Figure 2
Figure 2
Key stages of the study. Abbreviation: FDA, US Food and Drug Administration.
Figure 3
Figure 3
Worries about living with AML (best–worst score). Abbreviation: AML, acute myeloid leukemia.
Figure 4
Figure 4
Example of a best–worst scaling choice task.

References

    1. Saultz JN, Ramiro G. Acute myeloid leukemia: a concise review. J Clin Med. 2016;5(3):E33.
    1. Howlader N, Noone AM, Krapcho M, et al. SEER Cancer Statistics Review, 1975–2014. Bethesda, MD, USA: National Cancer Institute; [Accessed February 28, 2018]. Available from:
    1. Dohner H, Weisdorf DJ, Bloomfield CD. Acute myeloid leukemia. N Engl J Med. 2015;373(12):1136–1152.
    1. Vardiman JW, Thiele J, Arber DA, et al. The 2008 revision of the world health organization (WHO) classification of myeloid neoplasms in acute leukemia: rationale and important changes. Blood. 2009;114(5):937–951.
    1. Dohner H, Estey EH, Amadori A, et al. Diagnosis and management of acute myeloid leukemia in adults: recommendations from an international expert panel, on behalf of the European LeukemiaNet. Blood. 2010;115(3):453–474.
    1. Furlong P, Bridges JFP, Charnas L, et al. How a patient advocacy group developed the first proposed graft guidance document for industry for submission to the US Food and Drug Administration. Orphanet J Rare Dis. 2015;10:82.
    1. Perfetto EM, Burke L, Oehrlein EM, Epstein RS. Patient-focused drug development: a new direction for collaboration. Med Care. 2015;53(1):9–17.
    1. Ho MP, Gonzalez JM, Lerner HP, et al. Incorporating patient-preference evidence into regulatory decision making. Surg Endosc. 2015;29:2984–2993.
    1. Hollin IL, Peay HL, Apkon SD, Bridges JF. Patient-centered benefit-risk assessment in duchenne muscular dystrophy. Muscle Nerve. 2017;55(5):626–634.
    1. Food US, Administration Drug. Structured approach to benefit-risk assessment in drug regulatory decision-making: draft PDUFA V implementation plan–February 2013. Fiscal Years 2013-2017. [Accessed February 28, 2018]. Available from: .
    1. Food US, Administration Drug. The voice of the patient. A series of reports from the US Food and Drug Administration’s (FDA’s) Patient-Focused Drug Development Initiative. Lung Cancer. [Accessed February 28, 2018]. Available from: .
    1. Peay HL, Hollin IL, Bridges JFP. Prioritizing parental worry associated with duchenne muscular dystrophy using best-worst scaling. J Genet Counsel. 2016;25:305–313.
    1. van Til JA, Ijzerman MJ. Why should regulators consider using patient preferences in benefit-risk assessment? Pharmacoeconomics. 2014;32(1):1–4.
    1. Hunter NL, O’Callaghan KM, Calif RM. Engaging patients across the spectrum of medical product development: view from the US Food and Drug Administration. JAMA. 2015;314:2499–2500.
    1. Medical Device Innovation Consortium (MDIC) Patient Centered Benefit-Risk Project Report: A Framework for Incorporating Information on Patient Preferences Regarding Benefit Risk into Regulatory Assessments of New Medical Technology. Minneapolis, MN: MDIC; 2015.
    1. Hauber AB, Fairchild AO, Johnson R. Quantifying benefit-risk preferences for medical interventions: an overview of a growing empirical literature. Appl Health Econ Health Policy. 2013;11(4):319–329.
    1. Food US, Administration Drug. The voice of the patient. A series of reports from the US Food and Drug Administration’s (FDA’s) Patient-Focused Drug Development Initiative. Breast Cancer. [Accessed February 28, 2018]. Available from: .
    1. Janssen EM, Segal JB, Bridges JFP. A framework for instrument development of a choice experiment: an application to type 2 diabetes. Patient. 2016;9(5):465–479.
    1. Hollin IL, Young C, Hanson C, Bridges JF, Peay H. Developing a patient-centered benefit-risk survey: a community engaged process. Value Health. 2016;16(6):751–757.
    1. Oakes AH, Garmo VS, Bone LR, Longo DR, Segal JB, Bridges JFP. Identifying and prioritizing the barriers and facilitators to the self- management of type 2 diabetes mellitus: a community-centered approach. Patient. 2017;10(6):773–783.
    1. Janssen EM, Bridges JFP. Art and science of instrument development for stated-preference methods. Patient. 2017;10(4):377–379.
    1. Louviere JJ, Woodworth G. Design and analysis of simulated consumer choice or allocation experiments: an approach based on aggregate data. J Market Res. 1983;20(4):350–367.
    1. dosReis S, Ng X, Frosch E, Reeves G, Cunningham C, Bridges JFP. Using best-worst scaling to measure caregiver preferences for managing their child’s ADHD: a pilot study. Patient. 2015;8(5):423–431.
    1. Potoglou D, Burge P, Flynn T, et al. Best–worst scaling vs. discrete choice experiments: an empirical comparison using social care data. Soc Sci Med. 2011;72(10):1717–1727.
    1. 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;62(8):1891–1901.
    1. Louviere JJ, Flynn TN. Using best-worst scaling choice experiments to measure public perceptions and preferences for healthcare reform in Australia. Patient. 2010;3:275–283.
    1. O’Donoghue B. Bringing the patient voice into drug development. [Accessed February 28, 2018]. Available from: .

Source: PubMed

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