Patient Preferences for Osteoarthritis Pain and Chronic Low Back Pain Treatments in the United States: A Discrete-Choice Experiment

Abstract

Objective: To quantify preferences for attributes of potential analgesic treatments for moderate-to-severe pain associated with osteoarthritis (OA) and/or chronic low back pain (CLBP) as relevant to injectable nerve growth factor (NGF)-inhibitors, nonsteroidal anti-inflammatory drugs (NSAIDs), and opioids. Methods: We used a discrete-choice experiment (DCE) to elicit preferences for attributes of OA and CLBP pharmaceutical treatments, and a best-worst scaling (BWS) exercise to further characterize the relative importance of treatment-related side-effect risks. The survey was completed online by 602 US residents with self-reported chronic, moderate-to-severe OA pain and/or CLBP who had tried, had contraindications for, or were unwilling to take currently available pharmaceutical therapies. In the DCE, respondents repeatedly chose between two hypothetical treatments defined by six attributes (symptom control; treatment-related risks of (1) severe joint problems, (2) heart attack, and (3) physical dependence; mode/frequency of administration; and cost). In the BWS exercise, respondents evaluated ten side-effect risks. Random-parameters logit models were estimated; conditional relative attribute importance, maximum acceptable risks, and willingness to pay were calculated. Results: The most important DCE attributes were improving symptom control (scaled conditional relative importance, 10.00) and reducing risk of physical dependence (6.99). The three most important BWS attributes were, in rank order, risks of stroke, physical dependence, and heart attack. Respondents were willing to accept a > 4% treatment-related risk of severe joint problems for even modest symptom improvement. Conclusion: A pharmaceutical treatment with a risk of severe joint problems was viewed as an acceptable alternative to other treatments with comparable efficacy but risks associated with NSAIDs or opioids.