Abstract
Summary
The FRAX® tool estimates a 10-year probability of fracture based upon multiple clinical risk factors and an optional bone mineral density (BMD) measurement obtained from the femoral neck. We describe a simple procedure for using lumbar spine BMD to enhance fracture risk assessment under the FRAX system.
Introduction
Discordance between lumbar spine (LS) and femoral neck (FN) T-scores is common and a source of clinical confusion since the LS measurement is not an input variable for the FRAX algorithm. The purpose of this study is to develop a procedure for adjusting FRAX probability based upon the T-score difference between the LS and FN (termed offset).
Methods
The Manitoba BMD database was used to identify baseline LS and FN dual-energy X-ray absorptiometry examinations (33,850 women and 2,518 men age 50 and older) with FRAX estimates for a major osteoporotic fracture categorized as low (<10%), moderate (10–20%), and high (>20%). Fracture outcomes were assessed from population-based administrative data. An approach was developed and internally validated using a split-cohort design.
Results
The offset was found to significantly affect fracture risk [HR, 1.12 (95% CI, 1.06–1.18) per SD LS below FN] independent of the FRAX probability. The following rule was formulated: “Increase/decrease FRAX estimate for a major fracture by one tenth for each rounded T-score difference between LS and FN.” In the validation subgroup, there was a significant improvement in the fracture prediction using FRAX with the proposed offset adjustment for major osteoporotic (P = 0.007) and vertebral fracture prediction (P < 0.001). For those at moderate risk under FRAX, 12.6% showed reclassification using the offset to a risk level that more accurately reflected their observed risk (25.2% reclassification for moderate risk discordant cases).
Conclusion
A simple procedure that incorporates the offset between the LS and FN T-scores can enhance fracture risk prediction under the FRAX system.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Kanis JA, Oden A, Johnell O et al (2007) The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women. Osteoporos Int 18:1033–1046
Kanis JA, Borgstrom F, De Laet C et al (2005) Assessment of fracture risk. Osteoporos Int 16:581–589
Kanis JA, Johnell O, Oden A et al (2008) FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int 19:385–397
Kanis JA, McCloskey EV, Johansson H et al (2008) A reference standard for the description of osteoporosis. Bone 42:467–475
Johnell O, Kanis JA, Oden A et al (2005) Predictive value of BMD for hip and other fractures. J Bone Miner Res 20:1185–1194
Marshall D, Johnell O, Wedel H (1996) Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 312:1254–1259
Leslie WD, Lix LM (2010) Absolute fracture risk assessment using lumbar spine and femoral neck bone density measurements: derivation and validation of a hybrid system. J Bone Miner Res (in press)
Leslie WD, MacWilliam L, Lix L et al (2005) A population-based study of osteoporosis testing and treatment following introduction of a new bone densitometry service. Osteoporos Int 16:773–782
Leslie WD, Caetano PA, MacWilliam LR et al (2005) Construction and validation of a population-based bone densitometry database. J Clin Densitom 8:25–30
Binkley N, Kiebzak GM, Lewiecki EM et al (2005) Recalculation of the NHANES Database SD improves T-score agreement and reduces osteoporosis prevalence. J Bone Miner Res 20:195–201
Hansen KE, Binkley N, Christian R et al (2005) Interobserver reproducibility of criteria for vertebral body exclusion. J Bone Miner Res 20:501–508
Leslie WD (2006) The importance of spectrum bias on bone density monitoring in clinical practice. Bone 39:361–368
Roos NP, Shapiro E (1999) Revisiting the Manitoba Centre for Health Policy and Evaluation and its population-based health information system. Med Care 37:JS10–JS14
WHO (2005) Collaborating centre for drug statistics methodology. Guidelines for ATC classification and DDD assignment. WHO, Oslo
Kozyrskyj AL, Mustard CA (1998) Validation of an electronic, population-based prescription database. Ann Pharmacother 32:1152–1157
Leslie WD, Tsang JF, Caetano PA et al (2007) Effectiveness of bone density measurement for predicting osteoporotic fractures in clinical practice. J Clin Endocrinol Metab 92:77–81
Pencina MJ, D’Agostino RB Sr, D’Agostino RB Jr et al (2008) Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 27:157–172
Siminoski K, Leslie WD, Frame H et al (2005) Recommendations for bone mineral density reporting in Canada. Can Assoc Radiol J 56:178–188
Janes H, Pepe MS, Gu W (2008) Assessing the value of risk predictions by using risk stratification tables. Ann Intern Med 149:751–760
Blake GM, Patel R, Knapp KM et al (2003) Does the combination of two BMD measurements improve fracture discrimination? J Bone Miner Res 18:1955–1963
Kanis JA, Johnell O, Oden A et al (2006) The use of multiple sites for the diagnosis of osteoporosis. Osteoporos Int 17:527–534
Leslie WD, Lix LM, Tsang JF et al (2007) Single-site vs multisite bone density measurement for fracture prediction. Arch Intern Med 167:1641–1647
Dawson-Hughes B, Looker AC, Tosteson AN et al (2009) The potential impact of new National Osteoporosis Foundation guidance on treatment patterns. Osteoporos, Int
Kanis JA, McCloskey EV, Johansson H et al (2008) Case finding for the management of osteoporosis with FRAX((R))-assessment and intervention thresholds for the UK. Osteoporos Int 19:1395–1408
Leslie WD, Lix LM (2010) Simplified 10-year absolute fracture risk assessment: a comparison of men and women. J Clin Densitom 13:141–146
Faulkner KG, von Stetten E, Miller P (1999) Discordance in patient classification using T-scores. J Clin Densitom 2:343–350
Curtis JR, Mudano AS, Solomon DH et al (2009) Identification and validation of vertebral compression fractures using administrative claims data. Med Care 47:69–72
Acknowledgments
We are indebted to Manitoba Health for providing data (HIPC file no. 2007/2008–49). The results and conclusions are those of the authors, and no official endorsement by Manitoba Health is intended or should be inferred. This article has been reviewed and approved by the members of the Manitoba Bone Density Program Committee.
Conflicts of interest
William Leslie is part of a speaker bureau and has received unrestricted research grants from Merck Frosst, Canada as well as Novartis and Amgen Pharmaceuticals, Canada; and received research honoraria. He also received unrestricted educational grants from Sanofi-Aventis; Procter & Gamble Pharmaceuticals, Canada; has unrestricted educational grants from Genzyme Canada; and is a member of the following advisory boards: Genzyme, Canada; Novartis; and Amgen Pharmaceuticals, Canada.
Lisa Lix received an unrestricted research grant from Amgen.
In the past 3 years, Eugene McCloskey has received speaker fees and/or unrestricted research grants from Novartis, Amgen, AstraZeneca, Pfizer, Bayer, Procter & Gamble, Lilly, Roche, Servier, and Hologic.
John A. Kanis has nothing to declare for FRAX and the context of this paper, but has numerous ad hoc consultancies for the following industries: Abiogen, Italy; Amgen, USA, Switzerland, and Belgium; Bayer, Germany; Besins-Iscovesco, France; Biosintetica, Brazil; Boehringer Ingelheim, UK; Celtrix, USA; D3A, France; Gador, Argentina; General Electric, USA; GSK, UK, USA; Hologic, Belgium and USA; Kissei, Japan; Leiras, Finland; LEO Pharma, Denmark; Lilly, USA, Canada, Japan, Australia and UK; Merck Research Labs, USA; Merlin Ventures, UK; MRL, China; Novartis, Switzerland and USA; Novo Nordisk, Denmark; Nycomed, Norway; Ono, UK and Japan; Organon, Holland; Parke-Davis, USA; Pfizer, USA; Pharmexa, Denmark; Procter & Gamble, UK, USA; ProStrakan, UK; Roche, Germany, Australia, Switzerland, USA; Rotta Research, Italy; Sanofi-Aventis, USA; Schering, Germany and Finland; Servier, France and UK; Shire, UK; Solvay, France and Germany; Strathmann, Germany; Tethys, USA; Teijin, Japan;Teva, Israel; UBS, Belgium; Unigene, USA; Warburg-Pincus, UK; Warner-Lambert, USA; and Wyeth, USA. He also has numerous ad hoc consultancies for the following governmental and non-governmental organizations: the National Institute for Health and Clinical Excellence (NICE), UK; International Osteoporosis Foundation; INSERM, France; Ministry of Public Health, China; Ministry of Health, Australia; National Osteoporosis Society (UK); and WHO
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Leslie, W.D., Lix, L.M., Johansson, H. et al. Spine–hip discordance and fracture risk assessment: a physician-friendly FRAX enhancement. Osteoporos Int 22, 839–847 (2011). https://doi.org/10.1007/s00198-010-1461-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00198-010-1461-5