Exploring Patient Preference Heterogeneity for Pharmacological Treatments for Chronic Pain: A Latent Class Analysis

Background

Several pharmaceutical treatments for chronic pain caused by osteoarthritis (OA) and chronic low back pain (CLBP) are available or currently under development, each associated with different adverse events (AEs) and efficacy profiles. It is therefore important to understand what trade-offs patients are willing to make when choosing between treatments.

Methods

A discrete-choice experiment (DCE) was conducted with 437 adults with chronic pain caused by OA and/or CLBP. Respondents were presented with a series of scenarios and asked to choose between pairs of hypothetical treatments, each defined by 6 attributes: level of symptom control; risks of heart attack, rapidly progressive osteoarthritis, and dependency; frequency and mode of administration; and cost. Attributes were based on known profiles of oral nonsteroidal anti-inflammatory drugs, opioids, and injected nerve growth factor inhibitors, the last of which were under clinical development at the time of the study. Data were analyzed using a latent class (LC) model to explore preference heterogeneity.

Results

Overall, respondents considered improving symptom control and reducing risk of physical dependency to be the most important attributes. The LC analysis identified 4 participant classes: an “efficacy-focused” class (33.7%), a “cost-averse” class (29.4%), a “physical-dependence–averse” class (19.6%), and a “needle-averse” class (17.3%). Subgroup membership was incompletely predicted by participant age and their responses to comprehension questions.

Conclusions

Preference heterogeneity across respondents indicates a need for a personalized approach to offering treatment options. Symptom improvement, cost, physical dependence and route of administration might be important to different patients.

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