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

• DOI: 10.1007/s00198-019-05154-9
• Publication Date: 2019-10-12T07:48:51Z
• Authors: D. Cornelissen; A. Boonen; S. Bours; S. Evers; C. Dirksen; M. Hiligsmann
• Keywords: Mixed logit

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