Literature DB >> 15241584

The impact of the use of multiple risk indicators for fracture on case-finding strategies: a mathematical approach.

Chris De Laet1, Anders Odén, Helena Johansson, Olof Johnell, Bengt Jönsson, John A Kanis.   

Abstract

The value of bone mineral density (BMD) measurements to stratify fracture probability can be enhanced in a case-finding strategy that combines BMD measurement with independent clinical risk indicators. Putative risk indicators include age and gender, BMI or weight, prior fracture, the use of corticosteroids, and possibly others. The aim of the present study was to develop a mathematical framework to quantify the impact of using combinations of risk indicators with BMD in case finding. Fracture probability can be expressed as a risk gradient, i.e. a relative risk (RR) of fracture per standard deviation (SD) change in BMD. With the addition of other continuous or categorical risk indicators a continuous distribution of risk indicators is obtained that approaches a normal distribution. It is then possible to calculate the risk of individuals compared with the average risk in the population, stratified by age and gender. A risk indicator with a gradient of fracture risk of 2 per SD identified 36% of the population as having a higher than average fracture risk. In individuals so selected, the risk was on average 1.7 times that of the general population. Where, through the combination of several risk indicators, the gradient of risk of the test increased to 4 per SD, a smaller proportion (24%) was identified as having a higher than average risk, but the average risk in this group was 3.1 times that of the population, which is a much better performance. At higher thresholds of risk, similar phenomena were found. We conclude that, whereas the change of the proportion of the population detected to be at high risk is small, the performance of a test is improved when the RR per SD is higher, indicated by the higher average risk in those identified to be at risk. Case-finding strategies that combine clinical risk indicators with BMD have increased efficiency, while having a modest impact on the number of individuals requiring treatment. Therefore, the cost-effectiveness is enhanced.

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Year:  2004        PMID: 15241584     DOI: 10.1007/s00198-004-1689-z

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


  17 in total

1.  The burden of osteoporotic fractures: a method for setting intervention thresholds.

Authors:  J A Kanis; A Oden; O Johnell; B Jonsson; C de Laet; A Dawson
Journal:  Osteoporos Int       Date:  2001       Impact factor: 4.507

2.  Evaluation of the simple calculated osteoporosis risk estimation (SCORE) in older Caucasian women: the Rancho Bernardo study.

Authors:  D Von Mühlen; A Visby Lunde; E Barrett-Connor; R Bettencourt
Journal:  Osteoporos Int       Date:  1999       Impact factor: 4.507

3.  Guidelines for diagnosis and management of osteoporosis. The European Foundation for Osteoporosis and Bone Disease.

Authors:  J A Kanis; P Delmas; P Burckhardt; C Cooper; D Torgerson
Journal:  Osteoporos Int       Date:  1997       Impact factor: 4.507

Review 4.  Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group.

Authors: 
Journal:  World Health Organ Tech Rep Ser       Date:  1994

5.  Added value of bone mineral density in hip fracture risk scores.

Authors:  H Burger; C E de Laet; A E Weel; A Hofman; H A Pols
Journal:  Bone       Date:  1999-09       Impact factor: 4.398

6.  Performance of risk indices for identifying low bone density in postmenopausal women.

Authors:  Piet Geusens; Marc C Hochberg; Danny J M van der Voort; Huibert Pols; Marjolein van der Klift; Ethel Siris; Mary E Melton; Jennifer Turpin; Christine Byrnes; Philip Ross
Journal:  Mayo Clin Proc       Date:  2002-07       Impact factor: 7.616

7.  Hip fracture prediction in elderly men and women: validation in the Rotterdam study.

Authors:  C E De Laet; B A Van Hout; H Burger; A E Weel; A Hofman; H A Pols
Journal:  J Bone Miner Res       Date:  1998-10       Impact factor: 6.741

Review 8.  Diagnosis of osteoporosis and assessment of fracture risk.

Authors:  John A Kanis
Journal:  Lancet       Date:  2002-06-01       Impact factor: 79.321

9.  Fall-related factors and risk of hip fracture: the EPIDOS prospective study.

Authors:  P Dargent-Molina; F Favier; H Grandjean; C Baudoin; A M Schott; E Hausherr; P J Meunier; G Bréart
Journal:  Lancet       Date:  1996-07-20       Impact factor: 79.321

10.  Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures.

Authors:  D Marshall; O Johnell; H Wedel
Journal:  BMJ       Date:  1996-05-18
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  37 in total

1.  My mother was saved from hip fracture by treatment for osteoporosis, but will I be?--Implications on risk estimates from successful osteoporosis treatment.

Authors:  B E Rosengren; M K Karlsson
Journal:  Osteoporos Int       Date:  2012-06-16       Impact factor: 4.507

Review 2.  The role of DXA bone density scans in the diagnosis and treatment of osteoporosis.

Authors:  Glen M Blake; Ignac Fogelman
Journal:  Postgrad Med J       Date:  2007-08       Impact factor: 2.401

3.  BMD, clinical risk factors and their combination for hip fracture prevention.

Authors:  H Johansson; J A Kanis; A Oden; O Johnell; E McCloskey
Journal:  Osteoporos Int       Date:  2009-03-17       Impact factor: 4.507

Review 4.  Bone health and prostate cancer.

Authors:  P J Saylor; M R Smith
Journal:  Prostate Cancer Prostatic Dis       Date:  2009-11-10       Impact factor: 5.554

5.  Development and validation of a population-based prediction scale for osteoporotic fracture in the region of Valencia, Spain: the ESOSVAL-R study.

Authors:  José Sanfélix-Genovés; Salvador Peiró; Gabriel Sanfélix-Gimeno; Vicente Giner; Vicente Gil; Manuel Pascual; Carlos Fluixá; Antonio Fuertes; Isabel Hurtado; Inmaculada Ferreros
Journal:  BMC Public Health       Date:  2010-03-24       Impact factor: 3.295

6.  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

7.  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

8.  Estimation of absolute fracture risk among middle-aged and older men and women: the EPIC-Norfolk population cohort study.

Authors:  Alireza Moayyeri; Stephen Kaptoge; Robert N Luben; Nicholas J Wareham; Sheila Bingham; Jonathan Reeve; Kay Tee Khaw
Journal:  Eur J Epidemiol       Date:  2009-04-07       Impact factor: 8.082

9.  Updated fracture incidence rates for the US version of FRAX.

Authors:  B Ettinger; D M Black; B Dawson-Hughes; A R Pressman; L J Melton
Journal:  Osteoporos Int       Date:  2009-08-25       Impact factor: 4.507

Review 10.  Prostate cancer survivorship: prevention and treatment of the adverse effects of androgen deprivation therapy.

Authors:  Philip J Saylor; Nancy L Keating; Matthew R Smith
Journal:  J Gen Intern Med       Date:  2009-11       Impact factor: 5.128

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