Guidance Breakdown: FDA Finalizes Updated Guidance on Patient Preference Information
The agency's new guidance expands the role of voluntary patient preference data across the entire device lifecycle. Here are the 12 key points we pulled out.
This guidance breakdown is available in full to paid subscribers. Only paid subscribers get regular full access to our guidance breakdowns and other analyses. If you’re not already a paid subscriber, you can upgrade here.
The FDA just issued its final guidance, Incorporating Voluntary Patient Preference Information over the Total Product Life Cycle, replacing the original 2016 guidance on patient preference information (PPI) for medical devices.
The draft was issued back in September 2024, and this final version fulfills a commitment the FDA made under MDUFA V (Section V.E., in case you’re interested).
If you work in medical device regulatory strategy, clinical affairs, or quality (or if you’re a sponsor weighing whether to invest in patient preference studies) this document deserves your attention. We pulled out a few of the key takeaways that were most salient to us.
The scope expanded well beyond PMAs, HDEs, and De Novos!
The 2016 guidance focused on PPI submitted in support of premarket approval applications (PMAs), humanitarian device exemption (HDE) applications, and De Novo classification requests. The new guidance explicitly extends the FDA’s consideration of PPI across the total product life cycle, including:
Investigational device exemption (IDE) applications
Requests for Breakthrough Device designation
PMAs, HDEs, and De Novo requests (carried over from 2016)
Premarket notifications (510(k)s)
Administrative, enforcement, and other FDA actions
That last bullet is notable! The FDA is now saying that patient preference data can be a factor in compliance and enforcement decisions, not just marketing authorization.
PPI remains entirely voluntary (no new burden on sponsors)
The guidance is clear here: submission of PPI is not required. The FDA is not changing any standards for marketing authorization or premarket review, and the document explicitly states it does not create any new burden on device sponsors.
That said, the guidance strongly encourages sponsors and other interested parties (patient groups, academia) to consider collecting and submitting PPI where it may be relevant, particularly for devices where patient decisions are “preference sensitive.”
The FDA defines when PPI is most useful
The guidance identifies several characteristics that make a device a strong candidate for PPI:
Devices with a direct patient interface
Devices intended to yield significant health or appearance benefits
Devices that directly affect health-related quality of life
Life-saving but high-risk devices
Devices developed for unmet medical needs or rare diseases
Devices offering alternative benefits to those already marketed
Devices with novel technology
Devices where key endpoint experiences are subjective
The guidance also flags situations where its own staff may find PPI particularly valuable, for example, when patients may value benefits and risks differently from healthcare professionals, when population-level differences in patient perspectives aren’t well understood, or when there is a significant public health impact.
“Preference sensitive” decisions get a clearer definition
The guidance articulates when patient decisions are considered preference sensitive:
Multiple treatment options exist, and none is clearly superior for all patients.
Evidence supporting one option over others is considerably uncertain,
Patients’ views about the most important benefits and acceptable risks vary considerably or differ from those of healthcare professionals,
This framing matters because it signals where the FDA sees PPI adding the most value to its own benefit-risk assessment.
Section V gives detailed study quality recommendations
Section V outlines 12 qualities the FDA considers when reviewing PPI studies. These aren’t new regulatory requirements, but they represent the FDA’s clearest articulation to date of what makes a PPI study credible for decision-making purposes.
To run through them quickly:
Patient-centeredness — the patient, not the clinician, should be the central focus.
Relevance to patients — benefits, risks, and uncertainty should be clinically relevant and align with clinical study endpoints.
Study conduct — trained administration or adequate self-administration with tutorials and comprehension quizzes.
Appropriate methods — qualitative, quantitative, or both, matched to the research question and product life cycle stage.
Representative study population — enrollment should reflect the full spectrum of the intended use population.
Heterogeneity — studies should account for the variability of patient preferences across disease severity, experience, demographics, etc..
Appropriate attribute and level selection — attributes should be relevant to FDA decision-making, mutually exclusive, and not include attributes (like cost) that could skew results.
Effective communication of benefit, risk, and uncertainty — with specific recommendations on numeracy, format, and framing.
Study comprehension with minimal cognitive bias — design should minimize framing, anchoring, and ordering effects.
Logical soundness — internal validity tests for logic and consistency.
Robustness of analysis — statistical rigor, confidence intervals, sensitivity analyses.
Adherence to good research practices — following guidelines from recognized professional organizations like ISPOR.
The FDA strongly encourages early engagement via Q-Subs
One of the most practical messages in this guidance is to engage with the FDA early and often during PPI study development. The guidance recommends seeking FDA alignment via Q-Sub on a few particular points:
The scientific research question(s) and study objectives.
The intended patient sample and enrollment criteria.
Proposed attributes and attribute levels (including submitting an attribute table).
The survey instrument before it’s finalized.
Recruitment and sampling strategies.
Identification of clinically relevant subgroups.
The FDA frames this as an iterative process, not a single checkpoint. Sponsors are encouraged to submit draft protocols, pre-field test survey instruments, and pre-testing results for review.
PPI can support subset approvals
The guidance makes clear that PPI may help identify a subset of patients for whom probable benefits outweigh probable risks (even when the data doesn’t support that conclusion for the broader study population).
One hypothetical example in the guidance describes a knee implant where overall study data showed smaller-than-expected improvement, but pre-specified subgroup analysis showed greater benefit for patients with the highest pain and functional limitation. PPI confirmed that those patients found the benefits acceptable given the risks. The FDA could approve the device with the indication limited to that subgroup.
This is a meaningful signal about how the FDA views PPI as a tool for enabling access (not just for broad population approvals, but for targeted ones).
PPI won’t override a negative benefit-risk determination
The guidance includes a clear counterexample, too: a scenario where PPI shows some patients would accept higher risks, but FDA concludes the device poses an unreasonable risk that could be addressed through design and manufacturing improvements. In that case, the FDA may decline to approve despite a favorable PPI.
The point is that PPI is one input among the totality of evidence. It doesn’t function as a patient-demand override of the FDA’s safety determination.
