SHOULD WE COLLECT PATIENT PREFERENCE INSIGHTS IN REGISTRIES? FINDINGS FROM THE PPD COREVITAS OBESITY REGISTRY (OBR)
Author(s)
Hui Lu, PhD1, Kevin Patrick Marsh, PhD1, Sebastian Heidenreich, BSc, MSc, PhD1, Jennifer Whitty, PhD1, Anup Das, PhD1, Nicolas Krucien, PhD1, Heather Chubb, MS2.
1Thermo Fisher Scientific, London, United Kingdom, 2Thermo Fisher Scientific, Waltham, MA, USA.
1Thermo Fisher Scientific, London, United Kingdom, 2Thermo Fisher Scientific, Waltham, MA, USA.
OBJECTIVES: As investment in obesity management medications (OMMs) grows, meaningful weight loss and a tolerable safety profile are table stakes. Differentiation depends on patient preferences for speed, durability and type of weight loss, treatment burden and cost. However, these insights are often unavailable early enough to inform evidence generation and product positioning. To address this challenge and to test alternative ways to increase access to patient preference insights, the PPD CorEvitas OBR is the first registry to collect patient preference data.
METHODS: Launched in December 2025, the OBR is a prospective, observational registry of adults with overweight or obesity. Data include treatment history, comorbidities, laboratory values, adverse events, and patient-reported outcomes. Patient preference measures include ACCEPT, BSW, MARS-5, and discrete choice experiment (DCE) with the following attributes: weight-loss outcomes, composition of weight loss, metabolic benefits, administration, safety, access, and out-of-pocket costs.
RESULTS: At the time of writing, preference data were available for 399 respondents. Early findings suggest: demand for OMMs is high but not guaranteed (medication was selected over no treatment in 69.5% of cases); expectations for treatment benefit are high but heterogeneous (34.3% expected 11-20% weight loss, 20.6% expected >30% weight loss); and patients attach more importance to attributes other than weight loss (collectively, changes in weight-loss magnitude (at 6, 12, and 24 months) accounted for 16.7% of the OMM treatment preferences.). At ISPOR Europe, we will present data from >500 patients, addressing: (i) how sponsors can optimize uptake and adherence; and (ii) the implications for using registries to collect reliable patient preference data.
CONCLUSIONS: Early findings illustrate the importance of patient preferences to OMM uptake and adherence. The OBR illustrates a novel means for generating early and rigorous patient preference insight.
METHODS: Launched in December 2025, the OBR is a prospective, observational registry of adults with overweight or obesity. Data include treatment history, comorbidities, laboratory values, adverse events, and patient-reported outcomes. Patient preference measures include ACCEPT, BSW, MARS-5, and discrete choice experiment (DCE) with the following attributes: weight-loss outcomes, composition of weight loss, metabolic benefits, administration, safety, access, and out-of-pocket costs.
RESULTS: At the time of writing, preference data were available for 399 respondents. Early findings suggest: demand for OMMs is high but not guaranteed (medication was selected over no treatment in 69.5% of cases); expectations for treatment benefit are high but heterogeneous (34.3% expected 11-20% weight loss, 20.6% expected >30% weight loss); and patients attach more importance to attributes other than weight loss (collectively, changes in weight-loss magnitude (at 6, 12, and 24 months) accounted for 16.7% of the OMM treatment preferences.). At ISPOR Europe, we will present data from >500 patients, addressing: (i) how sponsors can optimize uptake and adherence; and (ii) the implications for using registries to collect reliable patient preference data.
CONCLUSIONS: Early findings illustrate the importance of patient preferences to OMM uptake and adherence. The OBR illustrates a novel means for generating early and rigorous patient preference insight.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
PCR162
Topic
Methodological & Statistical Research, Patient-Centered Research, Real World Data & Information Systems
Topic Subcategory
Patient Behavior and Incentives
Disease
Diabetes/Endocrine/Metabolic Disorders (including obesity)