Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Selecting patients for osteoporosis therapy.

Stuart L Silverman1

  • 1University of California, Los Angeles, 8641 Wilshire Blvd., Suite 301, Beverly Hills, CA 90211, USA. stuarts@omcresearch.org

Current Osteoporosis Reports
|August 16, 2006
PubMed
Summary

Identifying individuals at risk for osteoporotic fracture is crucial. Integrating clinical risk factors with bone mineral density (BMD) improves fracture risk prediction, aiding targeted treatment strategies.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cost-Effectiveness of Opportunistic Osteoporosis Screening Using Chest Radiographs With Deep Learning in the United States.

Journal of the American College of Radiology : JACR·2025
Same author

Cost-effectiveness of radiofrequency echographic multi-spectrometry for the diagnosis of osteoporosis in the United States.

JBMR plus·2024
Same author

Clinical and demographic factors determining patient fracture risk decision point (FRDP): The improving risk communication in osteoporosis (RICO) project.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA·2024
Same author

Efficacy and safety of candidate biosimilar CT-P41 versus reference denosumab: a double-blind, randomized, active-controlled, Phase 3 trial in postmenopausal women with osteoporosis.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA·2024
Same author

Race-specific FRAX models are evidence-based and support equitable care: a response to the ASBMR Task Force report on Clinical Algorithms for Fracture Risk.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA·2024
Same author

Comparison of the cost-effectiveness of sequential treatment with abaloparatide in US men and women at very high risk of fractures.

Aging clinical and experimental research·2024

Area of Science:

  • Orthopedics
  • Gerontology
  • Public Health

Background:

  • Osteoporotic fractures pose a significant global health challenge, necessitating accurate risk identification for effective intervention.
  • Current bone mineral density (BMD) criteria are insufficient for identifying all high-risk individuals, as many with fractures do not meet osteoporosis definitions.
  • BMD assessment is not universally accessible, limiting its utility in global fracture risk assessment.

Purpose of the Study:

  • To highlight the limitations of BMD alone in identifying individuals at risk for osteoporotic fractures.
  • To emphasize the importance of incorporating clinical risk factors for improved fracture risk prediction.
  • To propose a framework for predicting 10-year absolute fracture risk using integrated data.

Main Methods:

  • Reviewing the limitations of existing bone mineral density (BMD) criteria for fracture risk assessment.
  • Evaluating the utility of clinical risk factors, alone and in conjunction with BMD, for predicting osteoporotic fractures.
  • Developing a model to integrate clinical risk factors for calculating 10-year absolute fracture risk.

Main Results:

  • Bone mineral density (BMD) alone inadequately identifies individuals at high risk for osteoporotic fractures.
  • Clinical risk factors, when combined with BMD, significantly enhance the accuracy of fracture risk prediction.
  • A 10-year absolute fracture risk can be reliably predicted by integrating various clinical risk factors.

Conclusions:

  • Integrating clinical risk factors with BMD offers a superior approach to identifying individuals needing treatment for osteoporotic fracture risk.
  • Predictive models for absolute fracture risk allow for more precise intervention strategies, avoiding overtreatment in low-risk populations.
  • Regional intervention thresholds, based on healthcare economics, are essential for implementing effective, population-specific fracture prevention programs.

Related Experiment Videos