Literature DB >> 16362461

Predicting the risk of fracture at any site in the skeleton: are all bone mineral density measurement sites equally effective?

G M Blake1, K M Knapp, T D Spector, I Fogelman.   

Abstract

The ability to assess a patient's risk of fracture is fundamental to the clinical role of bone densitometry. Fracture discrimination is quantified by the relative risk (RR), defined as the increased risk of fracture for a 1 standard deviation decrease in bone mineral density (BMD). The larger the value of RR, the more effective measurements are at identifying patients at risk of fracture. Epidemiological studies show that RR values for predicting the risk of any fracture are approximately the same for all BMD measurement sites. In this study, we show theoretically that this interesting observation is predictable and a consequence of two related observations: (1) that fracture prediction by BMD measurement sites distant from the fracture site is quantitatively explained by the correlation of BMD measurements and (2) that all correlation coefficients between distant BMD sites are comparable, with values in the range r = 0.55-0.65. The first of these conditions (referred to as the correlation hypothesis) is important because it sets a lower limit on the RR values at distant BMD sites on the assumption that measurements at these sites contain no independent information about fracture risk over and above that provided by their correlation with the fracture site BMD. If the correlation hypothesis is true, the present study points to the importance of the correlation coefficient between BMD sites as a key index that is indicative of the ability of different types of measurement to predict fracture risk. If, on the contrary, the correlation hypothesis is not valid, there is scope to improve bone densitometry by further studies to better identify those measurements that do provide independent information about fracture risk and how best to integrate this information with existing techniques to improve decision making.

Entities:  

Mesh:

Year:  2005        PMID: 16362461     DOI: 10.1007/s00223-005-0127-3

Source DB:  PubMed          Journal:  Calcif Tissue Int        ISSN: 0171-967X            Impact factor:   4.333


  7 in total

1.  Bone mineral densities in individuals with Gilbert's syndrome: a cross-sectional, case-control pilot study.

Authors:  G Y Minuk; R Greenberg; J Uhanova; K Hawkins; W D Leslie
Journal:  Can J Gastroenterol       Date:  2009-06       Impact factor: 3.522

2.  Evolution and predictors of change in total bone mineral density over time in HIV-infected men and women in the nutrition for healthy living study.

Authors:  Denise L Jacobson; Donna Spiegelman; Tamsin K Knox; Ira B Wilson
Journal:  J Acquir Immune Defic Syndr       Date:  2008-11-01       Impact factor: 3.731

3.  Spine-hip T-score difference predicts major osteoporotic fracture risk independent of FRAX(®): a population-based report from CAMOS.

Authors:  William D Leslie; Christopher S Kovacs; Wojciech P Olszynski; Tanveer Towheed; Stephanie M Kaiser; Jerilynn C Prior; Robert G Josse; Sophie A Jamal; Nancy Kreiger; David Goltzman
Journal:  J Clin Densitom       Date:  2011-07-01       Impact factor: 2.617

4.  Osteoporosis Canada 2010 guidelines for the assessment of fracture risk.

Authors:  Brian Lentle; Angela M Cheung; David A Hanley; William D Leslie; David Lyons; Alexandra Papaioannou; Stephanie Atkinson; Jacques P Brown; Sidney Feldman; Anthony B Hodsman; Abida Sophina Jamal; Robert G Josse; Stephanie M Kaiser; Brent Kvern; Suzanne Morin; Kerry Siminoski
Journal:  Can Assoc Radiol J       Date:  2011-11       Impact factor: 2.248

Review 5.  Guidelines for the diagnosis of osteoporosis: T-scores vs fractures.

Authors:  Paul D Miller
Journal:  Rev Endocr Metab Disord       Date:  2006-06       Impact factor: 9.306

6.  Twenty bone-mineral-density loci identified by large-scale meta-analysis of genome-wide association studies.

Authors:  Fernando Rivadeneira; Unnur Styrkársdottir; Karol Estrada; Bjarni V Halldórsson; Yi-Hsiang Hsu; J Brent Richards; M Carola Zillikens; Fotini K Kavvoura; Najaf Amin; Yurii S Aulchenko; L Adrienne Cupples; Panagiotis Deloukas; Serkalem Demissie; Elin Grundberg; Albert Hofman; Augustine Kong; David Karasik; Joyce B van Meurs; Ben Oostra; Tomi Pastinen; Huibert A P Pols; Gunnar Sigurdsson; Nicole Soranzo; Gudmar Thorleifsson; Unnur Thorsteinsdottir; Frances M K Williams; Scott G Wilson; Yanhua Zhou; Stuart H Ralston; Cornelia M van Duijn; Timothy Spector; Douglas P Kiel; Kari Stefansson; John P A Ioannidis; André G Uitterlinden
Journal:  Nat Genet       Date:  2009-10-04       Impact factor: 38.330

7.  Genetic markers of bone and joint health and physical capability in older adults: the HALCyon programme.

Authors:  Tamuno Alfred; Yoav Ben-Shlomo; Rachel Cooper; Rebecca Hardy; Cyrus Cooper; Ian J Deary; David Gunnell; Sarah E Harris; Meena Kumari; Richard M Martin; Avan Aihie Sayer; John M Starr; Diana Kuh; Ian N M Day
Journal:  Bone       Date:  2012-10-13       Impact factor: 4.398

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.