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Quantitative prediction of bone mineral density by using bone turnover markers in response to antiresorptive agents in postmenopausal osteoporosis: A model‐based meta‐analysis
Author(s) -
Wu Junyi,
Wang Chen,
Li GuoFu,
Tang EnTzu,
Zheng Qingshan
Publication year - 2021
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.14487
Subject(s) - denosumab , bone remodeling , bone mineral , medicine , n terminal telopeptide , osteoporosis , zoledronic acid , oncology , endocrinology , chemistry , osteocalcin , biochemistry , alkaline phosphatase , enzyme
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.