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Bone Quality Project
Proposal
1321
Title of Proposed Research
Bone Quality Project
Lead Researcher
Dennis M. Black
Affiliation
University of California, San Francisco
Funding Source
Foundation for NIH (FNIH) will directly raise funds and distribute the funds to UCSF, collaborators, consultants and service vendors. FNIH will execute contracts with each entity that will include multiple payment installments based on achieved milestones described in the Project Plan (see section 4). FNIH will ensure that all contracts include appropriate stipulations regarding data sharing and intellectual property and are consistent with the aims of the project and The Biomarkers Consortium policies.
Potential Conflicts of Interest
none
Data Sharing Agreement Date
16 November 2016
Lay Summary
Great progress has been made in both the treatment and diagnosis of osteoporosis. Many large randomized trials have shown that osteoporosis treatments can reduce fracture risk and may be one of the factors contributing to the decrease seen in hip fracture incidence. Despite
these advances, there are important limitations to the diagnosis and treatment of osteoporosis,
including limited efficacy for non-spine fractures, limited evidence that anti-osteoporosis drugs prevent fractures among those who do not yet have osteoporosis and lack of data supporting the efficacy of a given treatment beyond 3-4 years. Currently, significant obstacles exist for the
development of new osteoporotic medications. It is challenging, from an ethical standpoint, to
conduct placebo-controlled trials with control subjects who are not taking any osteoporotic drugs. Such ethical problems are circumvented by designing active-control trials and equivalent studies, and also by enrolling lower risk patients. These alternative CT designs require enormous sample sizes for endpoint trials, resulting in infeasibility due to excessive
cost and time required for trial execution. There is an urgent need to develop alternative trial
strategies and/or outcomes that are more efficient than the current ones. The proposed projects will take advantage of the thousands of patients who have already been studied in randomized trials (academic and industry setting) by examining potential biomarkers that reflect the changes in bone strength and fracture risk by utilizing data from: 1) 3D Quantitative
Computed Tomography and 2) biochemical markers of bone turnover, which we expect to
prove useful as endpoints in clinical trials, to aid clinical development generally and, to eventually be adopted in clinical practice. We will pool data from the QCT and BTM sub-studies from a substantial number of these trials. Furthermore, we will apply state-of-the-art methods
to obtain standardized assessments from the QCT scans of bone strength across these multiple
studies. Our overall goal is to maximize the potential of these biomarkers for use in drug development and patient management, using previously collected measurements, and at the same time provide guidance for maximizing their usefulness in future studies. The overall project will be carried out through the execution of two related, but scientifically distinct
projects: 1) Critical evaluation of imaging-derived bone strength measurements for use in drug
development; and
2) Critical evaluation of the utility of serum or urine bone biochemical markers for use in patient management and understanding antifracture efficacy of osteoporosis therapies.
While each of these projects has distinct specific aims, they are inextricably linked. The overarching project will make recommendations for the process of qualification of these biomarkers for use in drug development and/or clinical practice.
Study Data Provided
[{ "PostingID": 3441, "Title": "GSK-BON103593", "Description": "A one year, parallel, placebo-controlled, double-blind, randomized study to assess the effect of monthly 150mg oral ibandronate dosing versus placebo on bone quality and strength at the proximal femur in women with osteoporosis
Medicine: ibandronic acid, Condition: Osteoporosis, Phase: 4, Clinical Study ID: BON103593, Sponsor: GSK" }]
Statistical Analysis Plan
The statistical analysis plan will be added after the research is published.
Publication Citation
The publication citation will be added after the research is published.
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