Quantitative prediction of bone mineral density by using bone turnover markers in response to antiresorptive agents in postmenopausal osteoporosis: A model‐based meta‐analysis. Issue 3 (5th August 2020)

• Record Type: Journal Article
• Authors: Wu, Junyi; Wang, Chen; Li, Guo‐Fu; Tang, En‐Tzu; Zheng, Qingshan
• Is Part Of: British journal of clinical pharmacology. Volume 87:Issue 3(2021)
• Page Start: 1175
• Page End: 1186
• Publication Date: 2020-08-05
• Subjects: biomarkers -- modelling and simulation -- osteoporosis -- pharmacodynamics; Pharmacology -- Periodicals; Drugs -- Periodicals; 615.1
• DOI: 10.1111/bcp.14487
• Languages: English
• ISSNs: 0306-5251

Abstract

Abstract : Aims: This study aimed to predict time course of bone mineral density (BMD) by using corresponding response of bone turnover markers (BTMs) in women with postmenopausal osteoporosis under antiresorptive treatments. Methods: Data were extracted from literature searches in accessible public database. Time courses of percent change from baseline in serum C‐telopeptide of type 1 collagen (sCTX) and N‐telopeptide of type 1 collagen were described by complex exponential onset models. The relationship between BTM changes and BMD changes at lumbar spine and total hip was described using a multiscale indirect response model. Results: The dataset included 41 eligible published trials of 5 US‐approved antiresorptive agents (alendronate, ibandronate, risedronate, zoledronic acid and denosumab), containing over 28 800 women with postmenopausal osteoporosis. The time courses of BTM changes for different drugs were differentiated by maximal effect and onset rate in developed model, while sCTX responses to zoledronic acid and denosumab were captured by another model formation. Furthermore, asynchronous relationship between BTMs and BMD was described by a bone remodelling‐based semimechanistic model, including zero‐order production and first‐order elimination induced by N‐telopeptide of type 1 collagen and sCTX, separately. After external and informative validations, the developed models were able to predict BMD increase using 1‐year data. Conclusion: This exploratory analysis built a quantitative framework linking BTMs and BMD among antiresorptive agents, as well as a modelling approach to enhance comprehension of dynamic relationship between early and later endpoints among agents in a certain mechanism of action. Moreover, the developed models can offer predictions of BMD from BTMs supporting early drug development.