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Cross-sectional Versus Longitudinal Change in a Prospective HR-pQCT Study

Burt, Lauren A, Hanley, David A, Boyd, Steven K·2017·Journal of Bone and Mineral Research
DOI 10.1002/jbmr.3129
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Abstract

Longitudinal studies assessing age-related changes using high-resolution peripheral quantitative computed tomography (HR-pQCT) provide novel insight compared with cross-sectional analyses. The purpose of this cohort study was 1) to determine individuals’ change in HR-pQCT parameters over 5 years relative to least significant change (LSC), and 2) to evaluate if predicted rate of change from cross-sectional data is comparable to actual change from longitudinal investigation. A cohort of 466 (162 male, 304 female) participants completed two HR-pQCT scans with 5 years between assessments. After image registration, standard and cortical morphological analyses were conducted. Rate of bone microarchitectural change was compared between cross-sectional models and actual change calculated from longitudinal analyses. At the young end of the life span, we observed gains in total bone density of +0.2% to +2.9% per year, whereas the older participants (aged >50 years) lost total bone density at a rate of –0.3% to –1.3% per year. Declines in total bone density begin at age 40 years in females and 60 years in males, and significant adaptation was found at both ends of the age spectrum with respect to the LSC. Models predicting rate of change from cross-sectional data were similar to the actual change reported in this longitudinal study for total density and cortical thickness at the radius and cortical density at the tibia, but we found that changes in comparison to our 5-year longitudinal results were often overestimated from cross-sectional data. Studies aimed at observing age-related changes in a normative cohort, especially in a follow-up period of less than 5 years, are better to focus on the tibia rather than the radius because of the increased sensitivity to change at the tibia. © 2017 American Society for Bone and Mineral Research.

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  1. Boutroy, 2005, In vivo assessment of trabecular bone microarchitecture by high-resolution peripheral quantitative computed tomography, J Clin Endocrinol Metab, 90, 6508, 10.1210/jc.2005-1258 · DOI · Paper page
  2. Burghardt, 2010, Age- and gender-related differences in the geometric properties and biomechanical significance of intracortical porosity in the distal radius and tibia, J Bone Miner Res, 25, 983, 10.1359/jbmr.091104 · DOI · Paper page
  3. Burrows, 2010, Bone microstructure at the distal tibia provides a strength advantage to males in late puberty: an HR-pQCT study, J Bone Miner Res, 25, 1423, 10.1359/jbmr.091034 · DOI
  4. Burt, 2014, Bone microarchitecture and strength of the radius and tibia in a reference population of young adults: an HR-pQCT study, Arch Osteoporos, 9, 183, 10.1007/s11657-014-0183-2 · DOI
  5. Dalzell, 2009, Bone micro-architecture and determinants of strength in the radius and tibia: age-related changes in a population-based study of normal adults measured with high-resolution pQCT, Osteoporos Int, 20, 1683, 10.1007/s00198-008-0833-6 · DOI
  6. Hansen, 2014, Bone microarchitecture and estimated strength in 499 adult Danish women and men: a cross-sectional, population-based high-resolution peripheral quantitative computed tomographic study on peak bone structure, Calcif Tissue Int, 94, 269, 10.1007/s00223-013-9808-5 · DOI
  7. Hung, 2015, Age-related differences in volumetric bone mineral density, microarchitecture, and bone strength of distal radius and tibia in Chinese women: a high-resolution pQCT reference database study, Osteoporos Int, 26, 1691, 10.1007/s00198-015-3045-x · DOI
  8. Khosla, 2006, Effects of sex and age on bone microstructure at the ultradistal radius: a population-based noninvasive in vivo assessment, J Bone Miner Res, 21, 124, 10.1359/JBMR.050916 · DOI · Paper page
  9. Liu, 2010, Site specificity of bone architecture between the distal radius and distal tibia in children and adolescents: an HR-pQCT study, Calcif Tissue Int, 87, 314, 10.1007/s00223-010-9405-9 · DOI
  10. Macdonald, 2011, Age-related patterns of trabecular and cortical bone loss differ between sexes and skeletal sites: a population-based HR-pQCT study, J Bone Miner Res, 26, 50, 10.1002/jbmr.171 · DOI · Paper page
  11. Burt, 2016, Sex- and site-specific normative data curves for HR-pQCT, J Bone Miner Res, 31, 2041, 10.1002/jbmr.2873 · DOI
  12. Kawalilak, 2014, Characterizing microarchitectural changes at the distal radius and tibia in postmenopausal women using HR-pQCT, Osteoporos Int, 25, 2057, 10.1007/s00198-014-2719-0 · DOI
  13. Shanbhogue, 2016, Age- and sex-related changes in bone microarchitecture and estimated strength. A three-year prospective study using HRpQCT, J Bone Miner Res, 31, 1541, 10.1002/jbmr.2817 · DOI
  14. Laib, 1998, In vivo high-resolution 3D-QCT of the human forearm, Technol Health Care, 6, 329, 10.3233/THC-1998-65-606 · DOI · Paper page
  15. Lauretani, 2008, Longitudinal changes in BMD and bone geometry in a population-based study, J Bone Miner Res, 23, 400, 10.1359/jbmr.071103 · DOI · Paper page
  16. Melton, 2000, Cross-sectional versus longitudinal evaluation of bone loss in men and women, Osteoporos Int, 11, 592, 10.1007/s001980070080 · DOI
  17. Warming, 2002, Changes in bone mineral density with age in men and women: a longitudinal study, Osteoporos Int, 13, 105, 10.1007/s001980200001 · DOI · Paper page
  18. Burghardt, 2010, Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT, Bone, 47, 519, 10.1016/j.bone.2010.05.034 · DOI · Paper page
  19. Wong, 2015, A trimodality comparison of volumetric bone imaging technologies. Part II: 1-yr change, long-term precision, and least significant change, J Clin Densitom, 18, 260, 10.1016/j.jocd.2014.07.004 · DOI
  20. Kawalilak, 2014, Comparison of short-term in vivo precision of bone density and microarchitecture at the distal radius and tibia between postmenopausal women and young adults, J Clin Densitom, 17, 510, 10.1016/j.jocd.2013.09.014 · DOI
  21. Kawalilak, 2015, Least significant changes and monitoring time intervals for high-resolution pQCT-derived bone outcomes in postmenopausal women, J Musculoskelet Neuronal Interact, 15, 190
  22. Burghardt, 2013, Multicenter precision of cortical and trabecular bone quality measures assessed by high-resolution peripheral quantitative computed tomography, J Bone Miner Res, 28, 524, 10.1002/jbmr.1795 · DOI
  23. MacNeil, 2008, Improved reproducibility of high-resolution peripheral quantitative computed tomography for measurement of bone quality, Med Eng Phys, 30, 792, 10.1016/j.medengphy.2007.11.003 · DOI
  24. Manske, 2017, The estimation of second-generation HR-pQCT from first-generation HR-pQCT using in vivo cross-calibration, J Bone Miner Res. Epub, 15
  25. Pauchard, 2012, Quality control for bone quality parameters affected by subject motion in high-resolution peripheral quantitative computed tomography, Bone, 50, 1304, 10.1016/j.bone.2012.03.003 · DOI
  26. Buie, 2007, Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo micro-CT bone analysis, Bone, 41, 505, 10.1016/j.bone.2007.07.007 · DOI · Paper page
  27. Orwoll, 1991, Longitudinal precision of dual-energy X-ray absorptiometry in a multicenter study, J Bone Miner Res, 6, 191, 10.1002/jbmr.5650060213 · DOI
  28. Burt, 2017, Cortical porosity exhibits accelerated rate of change in peri- compared with post-menopausal women, Osteoporos Int, 28, 1423, 10.1007/s00198-016-3900-4 · DOI
  29. MacNeil, 2008, Bone strength at the distal radius can be estimated from high-resolution peripheral quantitative computed tomography and the finite element method, Bone, 42, 1203, 10.1016/j.bone.2008.01.017 · DOI · Paper page
  30. Pistoia, 2002, Estimation of distal radius failure load with micro-finite element analysis models based on three-dimensional peripheral quantitative computed tomography images, Bone, 30, 842, 10.1016/S8756-3282(02)00736-6 · DOI · Paper page
  31. Ross, 2011, The 2011 report on dietary reference intakes for calcium and vitamin D from the Institute of Medicine: what clinicians need to know, J Clin Endocrinol Metab, 96, 53, 10.1210/jc.2010-2704 · DOI · Paper page
  32. Pye, 2016, Bone turnover predicts change in volumetric bone density and bone geometry at the radius in men, Osteoporos Int, 28, 1
  33. Nelson, 2010, Is a fixed value for the least significant change appropriate, J Clin Densitom, 13, 18, 10.1016/j.jocd.2009.10.001 · DOI · Paper page
  34. Leslie, 2015, Why does rate of bone density loss not predict fracture risk, J Clin Endocrinol Metab, 100, 679, 10.1210/jc.2014-3777 · DOI
  35. Wey, 2011, pecker BL, Cross-sectional versus longitudinal associations of lean and fat mass with pQCT bone outcomes in children. J Clin Endocrinol Metab, 96, 106

Cited by

Metadata

Authors
Burt, L. A., Hanley, D. A., & Boyd, S. K.
Affiliations
  • McCaig Institute for Bone and Joint HealthUniversity of CalgaryCalgaryCanada
  • Departments of MedicineCommunity Health Sciences, and Oncology, University of CalgaryCalgaryCanada
ORCID
Venue
Journal of Bone and Mineral Research
Publisher
Oxford University Press (OUP)
Published
2017-03-15
Volume
32
Issue
7
Pages
1505-1513
ISSN
  • 0884-0431
  • 1523-4681
DOI
10.1002/jbmr.3129
Cited by
47
References
2
Language
en
Licence
academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)

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