ideasIdea
Quantitative patient preference studies set the benefit-risk bar before phase 3
Before a big trial starts, ask hundreds of patients how much extra survival they would trade for a given side-effect, so the trial is designed to test something patients would actually want.
Discrete choice experiments and best-worst scaling quantify how patients trade benefits against harms and burdens. Regulators (FDA CDRH, EMA) have accepted such data in medical devices and some drugs. The proposal is that for each new indication, a preference study defines the minimum clinically important benefit and acceptable toxicity profile, which is then written into the phase 3 design and the regulatory review.
Hypothesis
Preference-informed designs produce approvals with higher patient-relevant value and fewer post-approval label restrictions, and shift phase 3 endpoints towards those with the highest patient weights.
Rationale
Minimum clinically important differences are currently set by convention and statistics; patients have measurable and heterogeneous preferences that should anchor them.
What would test it
Run preference studies in three tumour types with upcoming phase 3 programmes; compare the preference-derived benefit thresholds with those in current protocols and with eventual approval decisions.
Maturity
early clinical
Who has to act
regulator
Cost to try
Medium ($1M to $50M)
Years to first evidence
4
Bottlenecks it attacks
- Patients lack understanding, navigation and agency · Most patients cannot understand their options, find trials, or push back, so decisions are made for them.
- Trial design, endpoints and cost · A phase 3 trial takes years and hundreds of millions of dollars, and often answers a question that has already moved on.