Application of a Systems Pharmacology‐Based Placebo Population Model to Analyze Long‐Term Data of Postmenopausal Osteoporosis

Osteoporosis is a progressive bone disease characterized by decreased bone mass resulting in increased fracture risk. The objective of this investigation was to test whether a recently developed disease systems analysis model for osteoporosis could describe disease progression in a placebo‐treated p...

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Bibliographic Details
Published in:CPT: pharmacometrics and systems pharmacology 2015-09, Vol.4 (9), p.516-526
Main Authors: Berkhout, J, Stone, JA, Verhamme, KM, Stricker, BH, Sturkenboom, MC, Danhof, M, Post, TM
Format: Article
Language:English
Subjects:
Biomarkers
Clinical trials
Fractures
Homeostasis
Menopause
Original
Osteoporosis
Pharmacology
Physiology
Population
Systems analysis
Womens health
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Summary:Osteoporosis is a progressive bone disease characterized by decreased bone mass resulting in increased fracture risk. The objective of this investigation was to test whether a recently developed disease systems analysis model for osteoporosis could describe disease progression in a placebo‐treated population from the Early Postmenopausal Intervention Cohort (EPIC) study. First, we qualified the model using a subset from the placebo arm of the EPIC study of 222 women who had similar demographic characteristics as the 149 women from the placebo arm of the original population. Second, we applied the model to all 470 women. Bone mineral density (BMD) dynamics were changed to an indirect response model to describe lumbar spine and total hip BMD in this second population. This updated disease systems analysis placebo model describes the dynamics of all biomarkers in the corresponding datasets to a very good approximation; a good description of an individual placebo response will be valuable for evaluating treatments for osteoporosis.
ISSN:2163-8306
2163-8306
DOI:10.1002/psp4.12006