FDA Patient Preference Guide Addresses 510(k) Applicability
FDA’s updated guidance on incorporating patient preference information (PPI) into regulatory decision-making for medical devices and biologics signals a constructive shift for the 510(k) pathway. By explicitly acknowledging the relevance of PPI in these submissions, the agency is opening the door to a more patient-centered evidentiary framework. This represents a notable evolution, as the 510(k) process has historically placed limited emphasis on comprehensive benefit–risk assessments.
A new Hogan Lovells legal analysis notes that in the updated guidance, FDA has indicated that PPI “may be an informative and helpful factor when FDA considers the risk profile (relative to a predicate) of the new device.” The agency also included real-world examples illustrating how PPI has influenced regulatory outcomes. In one case, patient data supported clearance of a device for solo home hemodialysis by demonstrating willingness among patients to accept higher risks in exchange for improved access, according to the analysis. In another, parent preference data helped define the primary effectiveness endpoint in a clinical study supporting premarket approval of a pediatric ear tube system.
Beyond premarket decisions, FDA said PPI may also inform enforcement and compliance actions — for example, in assessing whether patients understand device risks or are willing to accept availability of nonconforming products, the legal analysis says. However, the guidance stops short of establishing a formal role for PPI in postmarket surveillance requirements or recall decisions, it notes.
The revised guidance also introduces significantly more granular recommendations on how sponsors should design and conduct PPI studies. The analysis says FDA emphasizes that studies should be “fit-for-purpose,” with clearly defined research questions, endpoints, and preference attributes aligned with regulatory decision-making needs. Sponsors are encouraged to engage early with the agency — such as through the Q-Submission program — to ensure study designs will be meaningful.
The document cautions that poorly constructed studies — such as those omitting key risks or benefits — may carry little regulatory weight. It also advises against including irrelevant factors like cost in studies intended to inform FDA decisions and warns that extrapolating beyond studied preference levels is generally invalid.
A new appendix also outlines quantitative methods for eliciting patient preferences, including discrete choice experiments, threshold techniques, and swing weighting, along with considerations for selecting methodologies and determining sample sizes.