Literature DB >> 19551449

Population-based fracture risk assessment and osteoporosis treatment disparities by race and gender.

Jeffrey R Curtis1, Leslie A McClure, Elizabeth Delzell, Virginia J Howard, Eric Orwoll, Kenneth G Saag, Monika Safford, George Howard.   

Abstract

BACKGROUND: Undertreatment of osteoporosis has been recognized as a common problem in selected patient subgroups. However, primary prevention has been hampered by limited risk assessment tools that can be applied to large populations.
OBJECTIVES: Using clinical risk factors with a new tool from the World Health Organization (FRAX) and recommendations from the National Osteoporosis Foundation (NOF), we evaluated fracture risk and osteoporosis treatment in a US cohort. PARTICIPANTS: African Americans and Caucasians recruited from 2003-7 across the US as part of a longitudinal study.
DESIGN: Cross-sectional. MEASURES: The number of persons receiving prescription osteoporosis medications was assessed by race, sex, and fracture risk. Multivariable logistic regression evaluated the association between receipt of osteoporosis medications and fracture risk after controlling for potential confounders.
RESULTS: Among 24,783 participants, estimated fracture risk was highest for Caucasian women. After multivariable adjustment for fracture-related risk factors, the likelihood of receipt of osteoporosis medications among African Americans was lower than among Caucasians [odds ratio (OR) = 0.44, 95% confidence interval (CI) 0.37, 0.53] and for men compared to women (OR = 0.08, 95% CI 0.06-0.10). Even for the highest risk group, Caucasian women with 10-year hip fracture risk > or = 3% (n = 3,025, 39.7%), only 26% were receiving treatment.
CONCLUSIONS: A substantial gap exists between 2008 NOF treatment guidelines based on fracture risk and the receipt of prescription osteoporosis medications. This gap was particularly notable for African Americans and men. FRAX is likely to be useful to assess risk at a population level and identify high-risk persons in need of additional evaluation.

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Year:  2009        PMID: 19551449      PMCID: PMC2710475          DOI: 10.1007/s11606-009-1031-8

Source DB:  PubMed          Journal:  J Gen Intern Med        ISSN: 0884-8734            Impact factor:   5.128


  34 in total

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2.  Recalculation of the NHANES database SD improves T-score agreement and reduces osteoporosis prevalence.

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3.  A review of goodness of fit statistics for use in the development of logistic regression models.

Authors:  S Lemeshow; D W Hosmer
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4.  Race and sex differences in mortality following fracture of the hip.

Authors:  S J Jacobsen; J Goldberg; T P Miles; J A Brody; W Stiers; A A Rimm
Journal:  Am J Public Health       Date:  1992-08       Impact factor: 9.308

5.  Proximal femur bone mineral levels of US adults.

Authors:  A C Looker; H W Wahner; W L Dunn; M S Calvo; T B Harris; S P Heyse; C C Johnston; R L Lindsay
Journal:  Osteoporos Int       Date:  1995       Impact factor: 4.507

6.  Hip fracture incidence among the old and very old: a population-based study of 745,435 cases.

Authors:  S J Jacobsen; J Goldberg; T P Miles; J A Brody; W Stiers; A A Rimm
Journal:  Am J Public Health       Date:  1990-07       Impact factor: 9.308

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Review 8.  Patterns of bone mineral density testing: current guidelines, testing rates, and interventions.

Authors:  Charles A Morris; Danielle Cabral; Hailu Cheng; Jeffrey N Katz; Joel S Finkelstein; Jerry Avorn; Daniel H Solomon
Journal:  J Gen Intern Med       Date:  2004-07       Impact factor: 5.128

9.  Updated data on proximal femur bone mineral levels of US adults.

Authors:  A C Looker; H W Wahner; W L Dunn; M S Calvo; T B Harris; S P Heyse; C C Johnston; R Lindsay
Journal:  Osteoporos Int       Date:  1998       Impact factor: 4.507

10.  Sex-specific and race-specific hip fracture rates.

Authors:  S E Kellie; J A Brody
Journal:  Am J Public Health       Date:  1990-03       Impact factor: 9.308

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Review 2.  A critical review of racial/ethnic variables in osteoporosis and bone density research.

Authors:  M S Megyesi; L M Hunt; H Brody
Journal:  Osteoporos Int       Date:  2011-01-05       Impact factor: 4.507

3.  Predicting hip and major osteoporotic fractures using administrative data.

Authors:  Huifeng Yun; Elizabeth Delzell; Kristine E Ensrud; Meredith L Kilgore; David Becker; Michael A Morrisey; Jeffrey R Curtis
Journal:  Arch Intern Med       Date:  2010-11-22

4.  Cost-effectiveness of Virtual Bone Strength Testing in Osteoporosis Screening Programs for Postmenopausal Women in the United States.

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5.  Nurse case-manager vs multifaceted intervention to improve quality of osteoporosis care after wrist fracture: randomized controlled pilot study.

Authors:  S R Majumdar; J A Johnson; D Bellerose; F A McAlister; A S Russell; D A Hanley; S Garg; D A Lier; W P Maksymowych; D W Morrish; B H Rowe
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Review 6.  Male osteoporosis.

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7.  Race Plays a Role in the Knowledge, Attitudes, and Beliefs of Women with Osteoporosis.

Authors:  Nicole C Wright; Mary E Melton; Maira Sohail; Ivan Herbey; Susan Davies; Emily B Levitan; Kenneth G Saag; Natalia V Ivankova
Journal:  J Racial Ethn Health Disparities       Date:  2019-02-11

8.  Exploring Racial, Gender, and Insurance Disparities in Patients with Osteoporotic Fractures.

Authors:  Sarah C DeShields; Cynthia C Romero; Tina D Cunningham
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9.  Health disparities in endocrine disorders: biological, clinical, and nonclinical factors--an Endocrine Society scientific statement.

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Journal:  J Clin Endocrinol Metab       Date:  2012-06-22       Impact factor: 5.958

10.  Recent advances in managing osteoporosis.

Authors:  Claudia Gagnon; Peter R Ebeling
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