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.