Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Whom to treat? The contribution of vertebral X-rays to risk-based algorithms for fracture prediction. Results from the European Prospective Osteoporosis Study

Kaptoge, S. ; Armbrecht, G. ; Felsenberg, D. ; Lunt, M. ; Weber, K. ; Boonen, S. ; Jajic, I. ; Stepan, J. J. ; Banzer, D. and Reisinger, W. , et al. (2006) In Osteoporosis International 17(9). p.1369-1381
Abstract
Introduction: Vertebral fracture is a strong risk factor for future spine and hip fractures; yet recent data suggest that only 5-20% of subjects with a spine fracture are identified in primary care. We aimed to develop easily applicable algorithms predicting a high risk of future spine fracture in men and women over 50 years of age. Methods: Data was analysed from 5,561 men and women aged 50+ years participating in the European Prospective Osteoporosis Study (EPOS). Lateral thoracic and lumbar spine radiographs were taken at baseline and at an average of 3.8 years later. These were evaluated by an experienced radiologist. The risk of a new (incident) vertebral fracture was modelled as a function of age, number of prevalent vertebral... (More)
Introduction: Vertebral fracture is a strong risk factor for future spine and hip fractures; yet recent data suggest that only 5-20% of subjects with a spine fracture are identified in primary care. We aimed to develop easily applicable algorithms predicting a high risk of future spine fracture in men and women over 50 years of age. Methods: Data was analysed from 5,561 men and women aged 50+ years participating in the European Prospective Osteoporosis Study (EPOS). Lateral thoracic and lumbar spine radiographs were taken at baseline and at an average of 3.8 years later. These were evaluated by an experienced radiologist. The risk of a new (incident) vertebral fracture was modelled as a function of age, number of prevalent vertebral fractures, height loss, sex and other fracture history reported by the subject, including limb fractures occurring between X-rays. Receiver Operating Characteristic (ROC) curves were used to compare the predictive ability of models. Results: In a negative binomial regression model without baseline X-ray data, the risk of incident vertebral fracture significantly increased with age [RR 1.74, 95% CI (1.44, 2.10) per decade], height loss [1.08 (1.04, 1.12) per cm decrease], female sex [1.48 (1.05, 2.09)], and recalled fracture history; [1.65 (1.15, 2.38) to 3.03 (1.66, 5.54)] according to fracture site. Baseline radiological assessment of prevalent vertebral fracture significantly improved the areas subtended by ROC curves from 0.71 (0.67, 0.74) to 0.74 (0.70, 0.77) P=0.013 for predicting 1+ incident fracture; and from 0.74 (0.67, 0.81) to 0.83 (0.76, 0.90) P=0.001 for 2+ incident fractures. Age, sex and height loss remained independently predictive. The relative risk of a new vertebral fracture increased with the number of prevalent vertebral fractures present from 3.08 (2.10, 4.52) for 1 fracture to 9.36 (5.72, 15.32) for 3+. At a specificity of 90%, the model including X-ray data improved the sensitivity for predicting 2+ and 1+ incident fractures by 6 and 4 fold respectively compared with random guessing. At 75% specificity the improvements were 3.2 and 2.4 fold respectively. With the modelling restricted to the subjects who had BMD measurements (n=2,409), the AUC for predicting 1+ vs. 0 incident vertebral fractures improved from 0.72 (0.66, 0.79) to 0.76 (0.71, 0.82) upon adding femoral neck BMD (P=0.010). Conclusion: We conclude that for those with existing vertebral fractures, an accurately read spine X-ray will form a central component in future algorithms for targeting treatment, especially to the most vulnerable. The sensitivity of this approach to identifying vertebral fracture cases requiring anti-osteoporosis treatment, even when X-rays are ordered highly selectively, exceeds by a large margin the current standard of practice as recorded anywhere in the world. (Less)
Please use this url to cite or link to this publication:
author
; ; ; ; ; ; ; ; and , et al. (More)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; and (Less)
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
vertebral fracture, spine X-ray, radiograph, osteoporosis treatment, algorithm, osteoporosis diagnosis
in
Osteoporosis International
volume
17
issue
9
pages
1369 - 1381
publisher
Springer
external identifiers
  • wos:000239300400007
  • scopus:33746419629
  • pmid:16821002
ISSN
1433-2965
DOI
10.1007/s00198-005-0067-9
language
English
LU publication?
yes
id
067cb3e4-cf8a-435a-b31f-4fc060720cc2 (old id 401258)
date added to LUP
2016-04-01 17:15:20
date last changed
2022-04-06 11:38:11
@article{067cb3e4-cf8a-435a-b31f-4fc060720cc2,
  abstract     = {{Introduction: Vertebral fracture is a strong risk factor for future spine and hip fractures; yet recent data suggest that only 5-20% of subjects with a spine fracture are identified in primary care. We aimed to develop easily applicable algorithms predicting a high risk of future spine fracture in men and women over 50 years of age. Methods: Data was analysed from 5,561 men and women aged 50+ years participating in the European Prospective Osteoporosis Study (EPOS). Lateral thoracic and lumbar spine radiographs were taken at baseline and at an average of 3.8 years later. These were evaluated by an experienced radiologist. The risk of a new (incident) vertebral fracture was modelled as a function of age, number of prevalent vertebral fractures, height loss, sex and other fracture history reported by the subject, including limb fractures occurring between X-rays. Receiver Operating Characteristic (ROC) curves were used to compare the predictive ability of models. Results: In a negative binomial regression model without baseline X-ray data, the risk of incident vertebral fracture significantly increased with age [RR 1.74, 95% CI (1.44, 2.10) per decade], height loss [1.08 (1.04, 1.12) per cm decrease], female sex [1.48 (1.05, 2.09)], and recalled fracture history; [1.65 (1.15, 2.38) to 3.03 (1.66, 5.54)] according to fracture site. Baseline radiological assessment of prevalent vertebral fracture significantly improved the areas subtended by ROC curves from 0.71 (0.67, 0.74) to 0.74 (0.70, 0.77) P=0.013 for predicting 1+ incident fracture; and from 0.74 (0.67, 0.81) to 0.83 (0.76, 0.90) P=0.001 for 2+ incident fractures. Age, sex and height loss remained independently predictive. The relative risk of a new vertebral fracture increased with the number of prevalent vertebral fractures present from 3.08 (2.10, 4.52) for 1 fracture to 9.36 (5.72, 15.32) for 3+. At a specificity of 90%, the model including X-ray data improved the sensitivity for predicting 2+ and 1+ incident fractures by 6 and 4 fold respectively compared with random guessing. At 75% specificity the improvements were 3.2 and 2.4 fold respectively. With the modelling restricted to the subjects who had BMD measurements (n=2,409), the AUC for predicting 1+ vs. 0 incident vertebral fractures improved from 0.72 (0.66, 0.79) to 0.76 (0.71, 0.82) upon adding femoral neck BMD (P=0.010). Conclusion: We conclude that for those with existing vertebral fractures, an accurately read spine X-ray will form a central component in future algorithms for targeting treatment, especially to the most vulnerable. The sensitivity of this approach to identifying vertebral fracture cases requiring anti-osteoporosis treatment, even when X-rays are ordered highly selectively, exceeds by a large margin the current standard of practice as recorded anywhere in the world.}},
  author       = {{Kaptoge, S. and Armbrecht, G. and Felsenberg, D. and Lunt, M. and Weber, K. and Boonen, S. and Jajic, I. and Stepan, J. J. and Banzer, D. and Reisinger, W. and Janott, J. and Kragl, G. and Scheidt-Nave, C. and Felsch, B. and Matthis, C. and Raspe, H. H. and Lyritis, G. and Poor, G. and Nuti, R. and Miazgowski, T. and Hoszowski, K. and Armas, J. B. and Vaz, A. L. and Benevolenskaya, L. I. and Masaryk, P. and Cannata, J. B. and Johnell, Olof and Reid, D. M. and Bhalla, A. and Woolf, A. D. and Todd, C. J. and Cooper, C. and Eastell, R. and Kanis, J. A. and O'Neill, T. W. and Silman, A. J. and Reeve, J.}},
  issn         = {{1433-2965}},
  keywords     = {{vertebral fracture; spine X-ray; radiograph; osteoporosis treatment; algorithm; osteoporosis diagnosis}},
  language     = {{eng}},
  number       = {{9}},
  pages        = {{1369--1381}},
  publisher    = {{Springer}},
  series       = {{Osteoporosis International}},
  title        = {{Whom to treat? The contribution of vertebral X-rays to risk-based algorithms for fracture prediction. Results from the European Prospective Osteoporosis Study}},
  url          = {{http://dx.doi.org/10.1007/s00198-005-0067-9}},
  doi          = {{10.1007/s00198-005-0067-9}},
  volume       = {{17}},
  year         = {{2006}},
}