Understanding patients’ preferences for osteoporosis treatment: the impact of patients’ characteristics on subgroups and latent classes

SUMMARY: This study revealed patterns in osteoporosis patients’ treatment preferences, which cannot be related to socio-demographic or clinical characteristics, implicating unknown underlying reasons. Therefore, to improve quality of care and treatment, patients should have an active role in treatment choice, irrespective of their characteristics. INTRODUCTION: Patient centeredness is important to improve the quality of care. Accounting for patient preferences is a key element of patient centeredness, and understanding preferences are important for successful and adherent treatment. This study was designed to identify different preferences profiles and to investigate how patient characteristics influence treatment preferences of patients for anti-osteoporosis drugs. METHODS: Data from a discrete choice experiment among 188 osteoporotic patients were used. The hypothetical treatment options were characterized by three attributes: treatment efficacy, side effects, and mode/frequency of administration. A mixed logit model was used to measure heterogeneity across the sample. Subgroup analyses were conducted to identify potential effect of patient characteristics. Latent class modeling (LCM) was applied. Associations between patients’ characteristics and the identified latent classes were explored with chi-square. RESULTS: All treatment options were important for patients’ decision regarding osteoporotic treatment. Significant heterogeneity was observed for most attributes. Subgroup analyses revealed that patients with a previous fracture valued efficacy most, and patients with a fear of needles or aged > 65 years preferred oral tablets. Elderly patients disliked intravenous medication. Three latent classes were identified, in which 6-month subcutaneous injection was preferred in two classes (86%), while oral tablets were preferred in the third class (14%). No statistically significant associations between the profiles regarding socio-demographic or clinical characteristics could be found. CONCLUSIONS: This study revealed patterns in patients’ preferences for osteoporosis treatment, which cannot be related to specific socio-demographic or clinical characteristics. Therefore, patients should be involved in clinical decision-making to reveal their preferences.