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Patient and Physician Preferences Differ for Multidimensional Chronic Pain Outcomes: A Discrete Choice Experiment
Lisa Goudman1, Anuj Bhatia2, Jan Vollert3
1STIMULUS research group, Vrije Universiteit Brussel, Brussels, Belgium; Research Foundation-Flanders (FWO), Brussels, Belgium; Department of Neurosurgery, Universitair Ziekenhuis Brussel, Brussels, Belgium; Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium; Pain in Motion (PAIN) Research Group, Department of Physiotherapy, Human Physiology and Anatomy, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium.
Background:
Chronic pain research increasingly recognizes treatment benefit as multidimensional, spanning pain intensity, medication use, functioning, quality of life, and psychological well-being. However, composite endpoints often combine such domains using implicit, expert-driven, or statistically convenient weights rather than explicitly elicited stakeholder values.
Main Text:
This Commentary argues that composite endpoints in chronic pain should be understood as preference-sensitive constructs. Preference-informed endpoint development can make explicit how much each outcome domain contributes to overall treatment benefit. Drawing on empirical data from a discrete choice experiment among 351 respondents, including 137 patients with chronic pain and 214 physicians or other healthcare professionals involved in pain management, we illustrate how stakeholder preferences can generate different weighting structures for multidimensional endpoints. Patients assigned 55.0% of total weight to pain reduction, compared with 34.5% among physicians, whereas physicians assigned higher relative weights to medication reduction and quality-of-life outcomes.
Conclusion:
Preference-informed weighting can improve the transparency, interpretability, and stakeholder relevance of composite endpoints in chronic pain research. Future work should validate preference-weighted endpoints prospectively, evaluate their responsiveness in clinical trials, and develop practical tools to support their use in shared decision-making and comparative effectiveness research.
