Abstract
Summary
We developed a clinical prediction rule score to predict medication non-adherence for women prescribed osteoporosis treatment. When combined into a summative score, 62% with seven or more points on the score demonstrated very low adherence. This compares with 17% subjects with fewer than seven points (c-statistic = 0.74).
Introduction
Medication non-adherence is extremely common for osteoporosis; however, no clear methods exist for identifying patients at risk of this behavior. We developed a clinical prediction rule to predict medication non-adherence for women prescribed osteoporosis treatment.
Methods
Women undergoing bone mineral density testing and fulfilling WHO criteria for osteoporosis were invited to complete a questionnaire and then followed for 1 year. Adjusted logistic regression models were examined to identify variables associated with very low adherence (medication possession ratio <20%). The weighted variables, based on the logistic regression, were summed, and the score was compared with the proportion of subjects with very low adherence.
Results
One hundred forty two women participated in the questionnaire and were prescribed an osteoporosis medication. After 1 year, 36% (n = 50) had very low adherence. Variables associated with very low adherence included prior non-adherence with chronic medications, agreement that side effects are concerning, agreement that she is taking too many medications, lack of agreement that osteoporosis is a worry, lack of agreement that a fracture will cause disability, lack of agreement that medications help her stay active, and frequent use of alcohol. When combined into a summative score, 36 of the 58 subjects (62%) with seven or more points on the score demonstrated very low adherence. This compares with 14 of the 84 (17%) subjects with fewer than seven points (c-statistic = 0.74).
Conclusion
We developed a brief clinical prediction rule that was able to discriminate between women likely (and unlikely) to experience very low adherence with osteoporosis medications.
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Acknowledgments
This project was supported by a grant to Fallon Clinic from Novartis Pharmaceuticals Corporation. Dr. Solomon receives salary support from Amgen for work on rheumatoid arthritis as well as support from the Arthritis Foundation, AHRQ, and the NIH (AR 055989, AR 047782) on osteoporosis and adherence. Dr. Brookhart is supported by a career development award from the National Institute on Aging (AG27400). He has received grant support from Amgen for unrelated projects and has served on scientific advisory boards for Amgen without receiving compensation.
Conflicts of interest
Dr. Robert Yood has received funding by Novartis Pharmaceuticals Corporation for clinical research, and he is a subinvestigator for a pharmaceutical drug trial funded by Merk.
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Logistic regression for <20% and <80%, odds ratios (95% CI) (DOC 31 kb)
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Solomon, D.H., Brookhart, M.A., Tsao, P. et al. Predictors of very low adherence with medications for osteoporosis: towards development of a clinical prediction rule. Osteoporos Int 22, 1737–1743 (2011). https://doi.org/10.1007/s00198-010-1381-4
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DOI: https://doi.org/10.1007/s00198-010-1381-4