Literature DB >> 18297369

Assessment of 10-year absolute fracture risk: a new paradigm with worldwide application.

E Siris, P D Delmas.   

Abstract

Entities:  

Mesh:

Year:  2008        PMID: 18297369      PMCID: PMC2267482          DOI: 10.1007/s00198-008-0564-8

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


× No keyword cloud information.
In this issue of Osteoporosis International we present several papers representing common approaches to the evaluation of fracture risk [1-5]. This represents a considerable change for the field, moving from descriptions of risk as “relative risk,” as occurs on the output of DXA equipment, to what might be called “absolute risk” or “real risk,” neither of which is an adequate description. The model allows an assessment of the likelihood of hip or major osteoporosis-related fracture within a specific time frame (10 years) for individual patients. These analyses result from a “mega-analysis” conducted by a team of investigators on behalf of the World Health Organization, led by Dr John Kanis. In this study Kanis and colleagues took data from epidemiological studies from the USA, Europe, Australia and Asia and determined the factors that were common to all that independently increased the risk of fractures in the aging population. They then modeled overall fracture risk using these factors, making the model generally usable throughout the world. In order to apply the model, each country simply would have to know the epidemiology of osteoporosis-related fractures, their outcomes, and mortality rates, and risk models could be calculated. Where country-specific fracture data are not available, data from other countries with similar ethnic make-up can be substituted, with the realization that risk calculations made in this way are more prone to error. Using these risk assessments a health economic strategy can be formulated for each country, based on acceptable levels of resource utilization, to determine at what level of risk it would be cost effective to intervene. To do this requires more information than fracture epidemiology, including costs and the efficacy of the intervention strategies to reduce the risk of the fractures considered in the model, something that has to be derived from clinical trial data, which may or may not address these specific fractures. From these data intervention strategies can be developed, which will vary from country to country. This methodology brings this field somewhat into line with cardiovascular disease and breast cancer risk reduction, where data from Framingham have been used in this fashion in clinical decision making, as has the Gail model for the latter. Clearly, however, this does not change the concept of osteoporosis defined as a bone mineral density (at the hip) 2.5 SD below the average value for young adults. In at least some countries this will, by itself, convey a risk of sufficient magnitude to require intervention. The model does allow the identification of those in the low BMD range (T-score –1 to –2.5) who have the highest risk of fracture and would benefit for treatment. This is an important advance, since overall in this population the risk of fracture is low, but by virtue of numbers, total fractures exceed those occurring in persons with osteoporosis. Two other features of the model are clinically important. It allows for risk stratification in men, and across race. Finally, it aids in identifying persons with co-morbid conditions that increase fracture risk, and allows targeting of the high-risk populations here for intervention. The concept and the model development have been supported by the IOF and NOF, and both organizations strongly advocate its use in clinical decision making. The National Osteoporosis Foundation in the USA will be releasing a new Physician’s Guide applying the WHO algorithm to postmenopausal women and older men in the US population (www.nof.org) that is based upon the data in the papers in this issue from the NOF Guide Committee. Other support from the UK and Japan is indicated by inclusion of papers reflecting the adaptation of the model to those populations. Data for other countries such as Sweden have already been published, and we hope that others will follow. Finally, this issue contains European guidelines on the diagnosis and management of osteoporosis from the scientific committee of the European Society for the Clinical and Economic Evaluation of Osteoporosis (ESCEO) that review the most recent evidence on clinical efficacy/safety of treatments and integrate the recent developments described above [6].
  6 in total

1.  Absolute fracture risk reporting in clinical practice: a physician-centered survey.

Authors:  W D Leslie
Journal:  Osteoporos Int       Date:  2008-02-01       Impact factor: 4.507

2.  Implications of absolute fracture risk assessment for osteoporosis practice guidelines in the USA.

Authors:  B Dawson-Hughes; A N A Tosteson; L J Melton; S Baim; M J Favus; S Khosla; R L Lindsay
Journal:  Osteoporos Int       Date:  2008-02-22       Impact factor: 4.507

3.  Cost-effective osteoporosis treatment thresholds: the United States perspective.

Authors:  A N A Tosteson; L J Melton; B Dawson-Hughes; S Baim; M J Favus; S Khosla; R L Lindsay
Journal:  Osteoporos Int       Date:  2008-02-22       Impact factor: 4.507

4.  FRAX and the assessment of fracture probability in men and women from the UK.

Authors:  J A Kanis; O Johnell; A Oden; H Johansson; E McCloskey
Journal:  Osteoporos Int       Date:  2008-02-22       Impact factor: 4.507

Review 5.  European guidance for the diagnosis and management of osteoporosis in postmenopausal women.

Authors:  J A Kanis; N Burlet; C Cooper; P D Delmas; J-Y Reginster; F Borgstrom; R Rizzoli
Journal:  Osteoporos Int       Date:  2008-02-12       Impact factor: 4.507

6.  Development and application of a Japanese model of the WHO fracture risk assessment tool (FRAX).

Authors:  S Fujiwara; T Nakamura; H Orimo; T Hosoi; I Gorai; A Oden; H Johansson; J A Kanis
Journal:  Osteoporos Int       Date:  2008-02-22       Impact factor: 4.507

  6 in total
  15 in total

Review 1.  Heel bone mass of a young South Indian population with a Nigerian population residing in a South Indian suburban neighborhood: a comparative study.

Authors:  V Sapthagirivasan; M Anburajan
Journal:  Osteoporos Int       Date:  2012-02-14       Impact factor: 4.507

Review 2.  Development and use of FRAX in osteoporosis.

Authors:  J A Kanis; E V McCloskey; H Johansson; A Oden; O Ström; F Borgström
Journal:  Osteoporos Int       Date:  2010-05-13       Impact factor: 4.507

3.  Opportunities in population-specific osteoporosis research and management.

Authors:  L J Melton; M A Marquez
Journal:  Osteoporos Int       Date:  2008-07-16       Impact factor: 4.507

4.  Frax prediction without BMD for assessment of osteoporotic fracture risk.

Authors:  Ramesh Keerthi Gadam; Karen Schlauch; Kenneth E Izuora
Journal:  Endocr Pract       Date:  2013 Sep-Oct       Impact factor: 3.443

Review 5.  What's in a name revisited: should osteoporosis and sarcopenia be considered components of "dysmobility syndrome?".

Authors:  N Binkley; D Krueger; B Buehring
Journal:  Osteoporos Int       Date:  2013-08-01       Impact factor: 4.507

6.  Treatment thresholds for osteoporosis in men on androgen deprivation therapy: T-score versus FRAX.

Authors:  R A Adler; F W Hastings; V I Petkov
Journal:  Osteoporos Int       Date:  2009-06-17       Impact factor: 4.507

7.  Predictors of bone density testing in patients with rheumatoid arthritis.

Authors:  J Aizer; G Reed; A Onofrei; M J Harrison
Journal:  Rheumatol Int       Date:  2008-12-21       Impact factor: 2.631

Review 8.  Approaches to the targeting of treatment for osteoporosis.

Authors:  John A Kanis; Eugene V McCloskey; Helena Johansson; Anders Oden
Journal:  Nat Rev Rheumatol       Date:  2009-08       Impact factor: 20.543

9.  Epidemiology of fracture risk in the Women's Health Initiative.

Authors:  Rebecca D Jackson; Sirisha Donepudi; Walter Jerry Mysiw
Journal:  Curr Osteoporos Rep       Date:  2008-12       Impact factor: 5.096

10.  How to decide intervention thresholds based on FRAX in central south Chinese postmenopausal women.

Authors:  Zhimin Zhang; Yangna Ou; Zhifeng Sheng; Eryuan Liao
Journal:  Endocrine       Date:  2013-10-22       Impact factor: 3.633

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.