In short, ‘yes’. Barry Linden (2024) provides a nice overview of FDA’s approach to patient preference information (PPI):
FDA is very open to doing this and they’re encouraging sponsors to use this kind of data to help them. The FDA’s desire to incorporate patient perspectives into their risk-benefit decision-making process started during the HIV/AIDS crisis, where they met considerable criticism from the HIV/AIDS patient community that they were being too risk-averse. FDA has experimented with different techniques for gathering patient input, but those have mostly yielded qualitative responses. FDA faced a difficult challenge: how can they incorporate patient input in the regulatory context when they have to be evaluating clinical trial data?
The Center for Devices and Radiological Health (CDRH) went on the journey to figure out how that input can be quantified, and since then, CDER and CBER have adopted those approaches. The EMA has also adopted similar guidelines for drug makers. It is a growing experience though. When the industry works with reviewers who have never seen or dealt with patient preference data, it requires some education and coaching on behalf of some of the leadership within the agency to help reviewers better understand it. When regulators do understand, they’re grateful for the insights and the unique applicability of patient preference data in regulatory decision-making.
FDA’s Center for Devices and Radiological Health (CDRH) provided some guidance for patient preference studies in their 2016 Guidance.
Patient Centeredness: Studies should focus on patient–not healthcare professional preferences and focus on tradeoffs of benefits and risk. If necessary, input could include care-partner or healthcare professional preferences, but the focus should be on the patient.Representativeness of the Sample and Generalizability of Results: The study be both representative in terms of how patients are recruited as well be of sufficient sample size that the results can be generalized to the population of interest.Capturing Heterogeneity of Patients’ Preferences. Researchers should look at variability by common factors (e.g., sex, age, race/ethnicity, socioeconomic, cultural background), tolerability of risk, as well as disease-specific subgroups.Established Good Research Practices by Recognized Professional Organizations. FDA recommends following ISPOR Good Practice guidelines.Effective Communication of Benefit, Harm, Risk, and Uncertainty. The benefit and risk need to be communicated to patients in a language that patients can understand, but also should be clinically accurate. Some general tips including benefits and risk numerically, using multiple formats (e.g., verbal and graphical), give positive and negative framing (e.g., 20% chance of adverse events or 80% chance of no adverse events) to avoid cognitive bias, and conduct pilot tests before rolling out the full survey. Minimize cognitive bias. Researchers should beware of biases due to framing, anchoring, simplifying heuristics, or ordering effects.Logical Soundness: The data should include internal-validity tests of logic and consistency and should be verified for conformity with logic and consistency.Relevance. All critical aspects of harm, risk, benefit, and uncertainty should be included in the elicitation of preferences; any omission of a key harm, risk or benefit should be well justifiedRobustness of Analysis of Results. Statistical analyses should be conducted with a variety of scenario/sensitivity analysesStudy conduct. A patient preference study should be administered by trained research staff. If the preference study is self-administered by patients, they should go through a tutorial and a quiz before answering questions, to help to ensure adequate comprehension and compliance with the study protocol.Comprehension by Study Participants: Efforts should be made to ensure that study participants fully understand the harm, risk, benefit, uncertainty and other medical information being communicated to them.
Some examples of FDA using PPI are described in a paper by Johnson and Zhou (2016).
CDER encouraged a patient advocacy group to propose draft guidance on engaging patient and caregiver stakeholders in regulatory decision making for Duchenne muscular dystrophy. CDRH sponsored a discrete-choice experiment case study to quantify obese respondents’ perspectives on “meaningful benefits.”
FDA’s CDER recently has gone further with their Patient-Focused Drug Development (PFDD) program. This was in part due to Section 3002(c)(5) of the 21st Century Cures Act which mandated that FDA allow for the submission of patient experience data. The 8 steps recommended for researchers to follow when conducting patient experience studies include:
Define the research objective(s) and questionsDetermine the target patient population from whom to collect informationDetermine the study design and research setting, including instrumentsDetermine which analyses are required to achieve the research objectivesConstruct the study sampleCollect the data and perform data management tasksAnalyze and interpret the dataReport study results
There is much more literature on patient preference study and FDA decisionmaking, but hopefully this is a useful overview to get you started!
