Patient Preference Studies in HTA Decision Making: A NICE to Have?

PP data quantifies how patients make trade-offs involved in treatment decisions. Decision makers are increasingly interested in using quantitative PP data to support their decisions. For instance, the US Food and Drug Administration’s (FDA) Center for Devices and Radiological Health (CDRH) encourages manufacturers to submit PP data to support its benefit-risk assessment.² Health technology assessment (HTA) often also involves the use of quantitative preference data. However, HTA agencies have tended to use general population preferences to estimate utility inputs for cost-effectiveness analysis.³ While patient input is sought, it has often been in the form of qualitative insights on the burden of the disease, submissions from patient advocacy groups, or patient representatives being members of decision-making committees.⁴ There has traditionally been little or no role in HTA for quantitative PP data.

However, agencies such as Sweden’s Dental and Pharmaceutical Benefits Agency (TLV) and Germany’s Institute for Quality and Efficiency in Health Care (IQWiG) have identified formal roles for PP data in their methods guides. Other HTA agencies have more recently also shown an interest in PP data, initiating consultations and pilots to explore how this data might support their decision making.^5,6 Notably, in 2019 NICE provided its first scientific advice on PP study design, specifically on how PP data might support the selection of endpoints in a COPD clinical study.^5,6 However, questions still remain about how PP data can be used in HTA. In its recent publication,¹ NICE begins to answer some of those questions and confirms that the use of PP data is one of NICE’s nine priority research topics. Three main uses of PP studies are identified:

1. Clinical trial endpoint selection
2. Informing benefit-risk assessments for regulatory approval
3. Supporting reimbursement decisions

This article focuses on the use of PP data to support clinical trial endpoint selection and reimbursement decisions. What does NICE’s article say about this use of PP data? What questions still remain? And what does this mean for sponsors’ evidence generation strategies?

Understanding How Patients Make Trade-Offs

Where therapies have quite different profiles, in terms of efficacy, safety, and convenience, PP data can help committees understand how patients make trade-offs when choosing between such treatments. NICE illustrates this with an example of cancer treatments, where chemotherapy, radiation therapy, and immunotherapy differ in modes and ease of administration, effectiveness, and the risk of serious side effects. In such cases, a PP study could provide important insights to a committee on how patients with cancer would make trade-offs between the different treatment options and the probability that patients would prefer one treatment over another.

Justifying Endpoint Selection

PP studies can identify the endpoints that matter most to people living with the condition and therefore should be included in clinical trials. NICE’s scientific advice team produced its first ever guidance on a COPD PP study in February 2019. Input was received to improve the design of the COPD patient preference study, inform evidence generation strategy, and collect certain outcome data alongside PP to help in correlating the PP results with current NICE processes for evaluating new treatments.¹

NICE’s publication confirms the importance of PP data to their committees. This is encouraging for sponsors who see patients’ preferences as an important part of their value messages and provides support for them to include PP studies in their evidence generation strategy. However, inevitably there are still questions about precisely how this data will impact reimbursement decisions. Given this uncertainty, it is important that sponsors seek scientific advice from NICE on methods for collecting PP data and the proposed use of the data.