Published in:
01-01-2014 | Original Article
An algorithm using the early changes in PINP to predict the future BMD response for patients treated with daily teriparatide
Authors:
R. Niimi, T. Kono, A. Nishihara, M. Hasegawa, A. Matsumine, T. Nakamura, T. Kono, A. Sudo
Published in:
Osteoporosis International
|
Issue 1/2014
Login to get access
Abstract
Summary
About two thirds of patients with a procollagen type I N-terminal propeptide (PINP) increase of >80 μg/l at 1 month after starting teriparatide therapy showed a ≥10 % increase in lumbar spine (LS) bone mineral density (BMD) from baseline at 12 months. We recommend this algorithm as an aid in the clinical management of patients treated with daily teriparatide.
Introduction
An algorithm using PINP is provided in osteoporotic patients with teriparatide treatment. The correlations between the early changes in PINP and the subsequent BMD changes after daily teriparatide therapy were studied to develop an algorithm to monitor patients.
Methods
We evaluated whether early changes in PINP correlated with the changes in BMD at 12 months and developed an algorithm using the early changes in PINP to predict the upcoming BMD increases.
Results
The highest correlation coefficient for the relationship between PINP and LS BMD response was determined for the absolute change in PINP at 1 month and the percent change in LS BMD at 12 months (r = 0.36, p <0.01). Using a receiver operator curve analysis, we determined that an 80 μg/l increase in PINP was the most convenient predictor of a 10 % increase in LS BMD from baseline (area under curve = 0.72). Using a cut-off value of 80 μg/l, the positive predictive value for predicting a 10 % increase in LS BMD from baseline to 12 months was 65 %.
Conclusion
Greater short-term changes in PINP with teriparatide therapy are associated with greater 12-month increases in LS BMD. About two thirds of patients with a PINP increase of >80 μg/l at 1 month after starting treatment showed a ≥10 % increase in LS BMD from baseline at 12 months. We recommend this algorithm as an aid in the clinical management of patients treated with teriparatide.