Using DCE evidence in HTA submissions

Patient preference evidence from DCE studies is increasingly expected in HTA submissions - but how you prepare and present it determines whether it influences the decision.

This article explains how to structure patient preference DCE evidence for NICE, FDA, and EMA submissions, what decision-makers look for, and how SurveyEngine supports regulatory-grade evidence packages.

Ben White, 07.07.2026

What HTA bodies want from patient preference studies

NICE, the FDA, and the EMA have all published guidance on patient preference evidence, and all three reference discrete choice experiments as appropriate methods. But submitting a well-designed DCE study is not sufficient - the evidence must be presented in a way that directly addresses the decision the HTA body is making, and that links patient preferences to the specific benefit-risk trade-offs under consideration.

The most common failure in patient preference HTA submissions is the disconnect between the DCE results and the regulatory question. WTP estimates that show patients value efficacy over side effects are not useful without knowing the magnitudes of the efficacy improvements and side effect risks in the clinical trial.

How different HTA bodies use patient preference evidence

The FDA uses patient preference information primarily in benefit-risk frameworks. The FDA's 2019 PPI guidance describes how patient preference evidence can be used to inform structured benefit-risk assessment - specifically, to quantify how patients weigh treatment benefits against risks. WTP trade-off estimates from DCE studies map directly onto the benefit-risk framework's evidence requirements.

NICE uses patient preference evidence in multiple ways: as direct input to quality-adjusted life year (QALY) calculations (EQ-5D-based utility weights are themselves a form of preference measurement); as evidence about patient priorities in committee deliberations; and increasingly in cost-effectiveness analysis through NICE's Highly Specialised Technologies pathway.

The EMA's 2016 reflection paper on patient preferences acknowledges DCEs as appropriate methods for quantifying patient preferences and describes how this evidence can inform the benefit-risk assessment process at the time of regulatory review.

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Preparing the patient preference evidence package

Step 1: Link the DCE design explicitly to the regulatory decision. Before designing the study, identify the specific benefit-risk trade-off the HTA body needs to make. Design the DCE attributes around those specific trade-offs - not around what is clinically interesting or scientifically novel.

Step 2: Map WTP estimates to clinical trial data. Present WTP estimates alongside the clinical trial estimates of benefit and risk. For example: patients are willing to accept a 2 percentage point increase in serious infection risk for a 15% improvement in ACR50 response - and the clinical trial shows the drug delivers a 19% ACR50 improvement with a 1.4 pp increase in serious infection risk.

Step 3: Prepare a summary of evidence table. Create a concise table summarising: study design, target population, sample size, key WTP estimates, and how those estimates relate to the observed clinical data. This table should be immediately interpretable by a non-specialist reviewer.

Step 4: Document data quality and study validity. Include the full PREFS checklist assessment, consistency check results, and sensitivity analyses. Regulatory reviewers are increasingly sophisticated about DCE methodology and will scrutinise data quality.

Step 5: Engage SurveyEngine's regulatory affairs support. For FDA submissions and NICE dossiers, SurveyEngine's team has experience preparing patient preference evidence packages that meet the specific format and evidence requirements of each body.

Worked example - FDA benefit-risk framework submission

A DCE study for an FDA 510(k) submission produces the following key finding: patients with moderate-to-severe plaque psoriasis are willing to accept a 3.2 percentage point increase in the risk of serious adverse events for a 20 percentage point improvement in PASI75 response (complete or near-complete skin clearance).

The clinical data shows the device delivers 18.4 pp PASI75 improvement with a 1.9 pp increase in SAE risk. The patient preference evidence shows the delivered clinical profile is within the patients' acceptable trade-off range. The FDA accepts the patient preference evidence as meeting the PPI guidance standards and references it in the 510(k) decision summary.