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在整个监管决策过程中推动患者意见纳入科学。

Advancing the science of patient input throughout the regulatory decision-making process.

作者信息

Tegenge Million A, Moncur Megan M, Sokolic Robert, Forshee Richard A, Irony Telba

机构信息

Office of Biostatistics and Epidemiology Center for Biologics Evaluation and Research (CBER) US Food and Drug Administration Silver Spring Maryland.

Office of Tissues and Advanced Therapies CBER, US Food and Drug Administration Silver Spring Maryland.

出版信息

Learn Health Syst. 2017 Jun 14;1(3):e10032. doi: 10.1002/lrh2.10032. eCollection 2017 Jul.

Abstract

The US Food and Drug Administration (FDA) understands the value of patient input in the regulatory decision-making process and has worked to enhance meaningful engagement. In recent years, there has been an increased scientific demand for more systematic and quantitative approaches to incorporate patient input throughout the medical product lifecycle, including to inform regulatory benefit-risk assessments. The use of patient preference information (PPI), elicited using established scientific methods, is a promising strategy for accomplishing this. Although much of the science behind PPI is not new, its application in a regulatory setting will require adapting and advancing the science of identifying, collecting, and evaluating patient input for informing regulatory decision making. Patient input and empowerment are foundational to a learning healthcare system. A learning healthcare system paradigm can also help us better understand and continuously improve the incorporation of the patient perspective in regulatory decision making. In this article, we highlight the Food and Drug Administration's Center for Biologics Evaluation and Research experience and current initiatives on advancing the science of patient input in a regulatory setting, in particular, PPI. We provide a use case that explores how the principles and benefits of PPI applied in shared clinical decision making can be realized and leveraged to enhance regulatory evaluation of innovative therapies. To further advance the application of the science of patient input in our regulatory framework, we compiled a list of example resources that support stakeholders in designing and conducting PPI studies. More collaborative research among stakeholders is needed to establish best practice approaches, ensure scientific validity, and continuously learn and improve the systematic incorporation of scientific patient input throughout the regulatory decision-making process.

摘要

美国食品药品监督管理局(FDA)认识到患者意见在监管决策过程中的价值,并一直致力于加强有意义的参与。近年来,对于在医疗产品整个生命周期中纳入患者意见采用更系统和定量方法的科学需求不断增加,包括为监管的效益-风险评估提供信息。使用通过既定科学方法得出的患者偏好信息(PPI)是实现这一目标的一种有前景的策略。尽管PPI背后的许多科学并非新事物,但其在监管环境中的应用将需要调整和推进识别、收集和评估患者意见以用于监管决策的科学。患者意见和赋权是学习型医疗系统的基础。学习型医疗系统范式也可以帮助我们更好地理解并不断改进在监管决策中纳入患者视角的情况。在本文中,我们重点介绍了美国食品药品监督管理局生物制品评估和研究中心在推进监管环境中患者意见科学方面的经验和当前举措,特别是PPI。我们提供了一个用例,探讨如何在共享临床决策中实现和利用PPI的原则及益处,以加强对创新疗法的监管评估。为了在我们的监管框架中进一步推进患者意见科学的应用,我们编制了一份示例资源清单,以支持利益相关者设计和开展PPI研究。利益相关者之间需要开展更多合作研究,以建立最佳实践方法,确保科学有效性,并不断学习和改进在整个监管决策过程中系统纳入科学的患者意见。

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本文引用的文献

1
Structured Approaches to Benefit-Risk Assessment: A Case Study and the Patient Perspective.
Ther Innov Regul Sci. 2014 Sep;48(5):564-573. doi: 10.1177/2168479014536500.
3
Quantifying benefit-risk preferences for new medicines in rare disease patients and caregivers.
Orphanet J Rare Dis. 2016 May 26;11(1):70. doi: 10.1186/s13023-016-0444-9.
6
From passengers to co-pilots: Patient roles expand.
Sci Transl Med. 2015 Jun 10;7(291):291fs25. doi: 10.1126/scitranslmed.aac6023.
7
Update of hematopoietic cell transplantation for sickle cell disease.
Curr Opin Hematol. 2015 May;22(3):227-33. doi: 10.1097/MOH.0000000000000136.
8
Incorporating patient-preference evidence into regulatory decision making.
Surg Endosc. 2015 Oct;29(10):2984-93. doi: 10.1007/s00464-014-4044-2. Epub 2015 Jan 1.
9
Mortality rates and age at death from sickle cell disease: U.S., 1979-2005.
Public Health Rep. 2013 Mar-Apr;128(2):110-6. doi: 10.1177/003335491312800206.
10

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