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Can TBS reference values be a valid indicator for clinical vertebral fracture? A cross-sectional study

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Journal of Bone and Mineral Metabolism Aims and scope Submit manuscript

Abstract

Introduction

Trabecular bone score (TBS) is partially independent of fracture risk. Reference values for TBS have not been established in official guidelines, and thus clinicians often have difficulty interpreting TBS results. This study aimed to investigate whether reference values for TBS could be a valid indicator for clinical vertebral fracture (CVF).

Materials and methods

This cross-sectional study involved 231 women with CVF and 563 women without CVF aged 60–90 years who underwent dual-energy X-ray absorptiometry during 2019–2023. They were divided into osteoporosis, osteopenia, and normal groups according to bone mineral density of the lumbar spine. Reference values for TBS were defined as low (≤ 1.23), intermediate (1.23–1.31), and high (≥ 1.31).

Results

Among patients without anti-osteoporosis treatment (n = 476), the proportion with low TBS was 36.7% in the CVF group and 10.7% in the control group. The proportion with CVF was higher in the low TBS group than in the intermediate and high TBS groups, especially in the osteoporosis group (p < 0.001). The odds ratio for CVF was higher in the low TBS group than in the intermediate and high especially in patients with normal BMD and osteoporosis. The TBS cut-off values for incidence of CVF in the osteoporosis, osteopenia, and normal groups were 1.224, 1.319, and 1.322, respectively.

Conclusions

The reference value for low TBS (≤ 1.23) was useful as an indicator for CVF, especially in patients with osteoporosis. It is expected that reference values for TBS will be established in official guidelines in the future.

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Abbreviations

AUC:

Area under the curve

BMD:

Bone mineral density

BMI:

Body mass index

CVF:

Clinical vertebral fracture

DXA:

Dual-energy X-ray absorptiometry

FRAX:

Fracture Risk Assessment Tool

ICC:

Intraclass correlation coefficient

ISCD:

International Society for Clinical Densitometry

SD:

Standard deviation

SERM:

Selective estrogen receptor modulator

TBS:

Trabecular bone score

WHO:

World Health Organization

References

  1. (2001) Osteoporosis prevention, diagnosis, and therapy. Jama 285:785–795

  2. Brown JP, Engelke K, Keaveny TM, Chines A, Chapurlat R, Foldes AJ, Nogues X, Civitelli R, De Villiers T, Massari F, Zerbini CAF, Wang Z, Oates MK, Recknor C, Libanati C (2021) Romosozumab improves lumbar spine bone mass and bone strength parameters relative to alendronate in postmenopausal women: results from the Active-Controlled Fracture Study in Postmenopausal Women With Osteoporosis at High Risk (ARCH) trial. J Bone Miner Res 36:2139–2152

    Article  CAS  PubMed  Google Scholar 

  3. Kanis JA (1994) Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: synopsis of a WHO report. WHO Study Group Osteoporos Int 4:368–381

    Article  CAS  Google Scholar 

  4. Johnell O, Kanis JA, Oden A, Johansson H, De Laet C, Delmas P, Eisman JA, Fujiwara S, Kroger H, Mellstrom D, Meunier PJ, Melton LJ 3rd, O’Neill T, Pols H, Reeve J, Silman A, Tenenhouse A (2005) Predictive value of BMD for hip and other fractures. J Bone Miner Res 20:1185–1194

    Article  PubMed  Google Scholar 

  5. Kadri A, Binkley N, Daffner SD, Anderson PA (2023) Fracture in patients with normal bone mineral density: an evaluation of the american orthopaedic association’s own the bone registry. J Bone Joint Surg Am 105:128–136

    Article  PubMed  Google Scholar 

  6. Hans D, Goertzen AL, Krieg MA, Leslie WD (2011) Bone microarchitecture assessed by TBS predicts osteoporotic fractures independent of bone density: the Manitoba study. J Bone Miner Res 26:2762–2769

    Article  PubMed  Google Scholar 

  7. Richards C, Leslie WD (2022) Trabecular Bone Score in Rheumatic Disease. Curr Rheumatol Rep 24:81–87

    Article  PubMed  Google Scholar 

  8. Silva BC, Leslie WD, Resch H, Lamy O, Lesnyak O, Binkley N, McCloskey EV, Kanis JA, Bilezikian JP (2014) Trabecular bone score: a noninvasive analytical method based upon the DXA image. J Bone Miner Res 29:518–530

    Article  PubMed  Google Scholar 

  9. Cozadd AJ, Schroder LK, Switzer JA (2021) Fracture Risk Assessment: An Update. J Bone Joint Surg Am 103:1238–1246

    Article  PubMed  Google Scholar 

  10. Cianferotti L, Cipriani C, Corbetta S, Corona G, Defeudis G, Lania AG, Messina C, Napoli N, Mazziotti G (2023) Bone quality in endocrine diseases: determinants and clinical relevance. J Endocrinol Invest

  11. Shevroja E, Cafarelli FP, Guglielmi G, Hans D (2021) DXA parameters, Trabecular Bone Score (TBS) and Bone Mineral Density (BMD), in fracture risk prediction in endocrine-mediated secondary osteoporosis. Endocrine 74:20–28

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Fujimaki H, Tomioka M, Kanoshima Y, Morita A, Yamori T, Inaba Y (2022) Accuracy of the Fracture Risk Assessment Tool for judging pharmacotherapy initiation for primary osteoporosis. J Bone Miner Metab 40:860–868

    Article  CAS  PubMed  Google Scholar 

  13. Silva BC, Broy SB, Boutroy S, Schousboe JT, Shepherd JA, Leslie WD (2015) Fracture Risk Prediction by Non-BMD DXA Measures: the 2015 ISCD Official Positions Part 2: Trabecular Bone Score. J Clin Densitom 18:309–330

    Article  PubMed  Google Scholar 

  14. Leslie WD, Shevroja E, Johansson H, McCloskey EV, Harvey NC, Kanis JA, Hans D (2018) Risk-equivalent T-score adjustment for using lumbar spine trabecular bone score (TBS): the Manitoba BMD registry. Osteoporos Int 29:751–758

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Camacho PM, Petak SM, Binkley N, Diab DL, Eldeiry LS, Farooki A, Harris ST, Hurley DL, Kelly J, Lewiecki EM, Pessah-Pollack R, McClung M, Wimalawansa SJ, Watts NB (2020) American Association Of Clinical Endocrinologists/American College Of Endocrinology Clinical Practice guidelines for the diagnosis and treatment of postmenopausal osteoporosis-2020 update. Endocr Pract 26:1–46

    Article  PubMed  Google Scholar 

  16. McCloskey EV, Odén A, Harvey NC, Leslie WD, Hans D et al (2016) A Meta-Analysis of Trabecular Bone Score in Fracture Risk Prediction and Its Relationship to FRAX. J Bone Miner Res 31:940–948

    Article  PubMed  Google Scholar 

  17. Goel H, Binkley N, Hans D, Leslie WD (2023) Bone density and trabecular bone score to predict fractures in adults aged 20–39 years: a registry-based study. Osteoporos Int

  18. Khan MA, Jennings JW, Baker JC, Smolock AR, Shah LM et al (2023) ACR Appropriateness Criteria® Management of Vertebral Compression Fractures: 2022 Update. J Am Coll Radiol 20:S102-s124

    Article  PubMed  Google Scholar 

  19. Genant HK, Wu CY, van Kuijk C, Nevitt MC (1993) Vertebral fracture assessment using a semiquantitative technique. J Bone Miner Res 8:1137–1148

    Article  CAS  PubMed  Google Scholar 

  20. Shuhart CR, Yeap SS, Anderson PA, Jankowski LG, Lewiecki EM, Morse LR, Rosen HN, Weber DR, Zemel BS, Shepherd JA (2019) Executive Summary of the 2019 ISCD Position Development Conference on Monitoring Treatment, DXA Cross-calibration and Least Significant Change, Spinal Cord Injury, Peri-prosthetic and Orthopedic Bone Health, Transgender Medicine, and Pediatrics. J Clin Densitom 22:453–471

  21. Borgen TT, Bjørnerem Å, Solberg LB, Andreasen C, Brunborg C et al (2019) High prevalence of vertebral fractures and low trabecular bone score in patients with fragility fractures: A cross-sectional sub-study of NoFRACT. Bone 122:14–21

    Article  PubMed  Google Scholar 

  22. Fluss R, Faraggi D, Reiser B (2005) Estimation of the Youden Index and its associated cutoff point. Biom J 47:458–472

    Article  MathSciNet  PubMed  Google Scholar 

  23. Agarwal K, Cherian KE, Kapoor N, Paul TV (2022) OSTA as a screening tool to predict osteoporosis in Indian postmenopausal women - a nationwide study. Arch Osteoporos 17:121

    Article  PubMed  Google Scholar 

  24. Kuriakose C, Cherian KE, Jebasingh F, Kapoor N, Asha HS, Jose A, Thomas N, Paul TV (2022) The prevalence of vertebral fractures among Indian perimenopausal women and its association with ovarian biomarkers. J Bone Miner Metab 40:142–149

    Article  CAS  PubMed  Google Scholar 

  25. Vinolas H, Grouthier V, Mehsen-Cetre N, Boisson A, Winzenrieth R, Schaeverbeke T, Mesguich C, Bordenave L, Tabarin A (2018) Assessment of vertebral microarchitecture in overt and mild Cushing’s syndrome using trabecular bone score. Clin Endocrinol (Oxf) 89:148–154

    Article  PubMed  Google Scholar 

  26. Pothuaud L, Carceller P, Hans D (2008) Correlations between grey-level variations in 2D projection images (TBS) and 3D microarchitecture: applications in the study of human trabecular bone microarchitecture. Bone 42:775–787

    Article  PubMed  Google Scholar 

  27. Palomo T, Muszkat P, Weiler FG, Dreyer P, Brandão CMA, Silva BC (2022) Update on trabecular bone score. Arch Endocrinol Metab 66:694–706

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kužma M, Hans D, Koller T, Némethová E, Jackuliak P, Killinger Z, Resch H, Payer J (2018) Less strict intervention thresholds for the FRAX and TBS-adjusted FRAX predict clinical fractures in osteopenic postmenopausal women with no prior fractures. J Bone Miner Metab 36:580–588

    Article  PubMed  Google Scholar 

  29. Goel H, Binkley N, Hans D, Leslie WD (2023) Fracture risk gradient assessed by categories of bone mineral density and trabecular bone score: the Manitoba BMD Registry. Arch Osteoporos 18:73

    Article  PubMed  Google Scholar 

  30. Iki M, Tamaki J, Kadowaki E, Sato Y, Dongmei N, Winzenrieth R, Kagamimori S, Kagawa Y, Yoneshima H (2014) Trabecular bone score (TBS) predicts vertebral fractures in Japanese women over 10 years independently of bone density and prevalent vertebral deformity: the Japanese Population-Based Osteoporosis (JPOS) cohort study. J Bone Miner Res 29:399–407

    Article  PubMed  Google Scholar 

  31. Popp AW, Meer S, Krieg MA, Perrelet R, Hans D, Lippuner K (2016) Bone mineral density (BMD) and vertebral trabecular bone score (TBS) for the identification of elderly women at high risk for fracture: the SEMOF cohort study. Eur Spine J 25:3432–3438

    Article  PubMed  Google Scholar 

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Acknowledgements

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Orthopedics, Tokushima Municipal Hospital, 2-34 Kitajousanjima, Tokushima, 770-0812, Japan

    Yasuyuki Omichi & Tomohiro Goto

  2. Department of Orthopedics, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan

    Yasuyuki Omichi, Keizo Wada, Yasuaki Tamaki, Daisuke Hamada, Masatoshi Morimoto & Koichi Sairyo

  3. Department of Orthopedics, Mima Hospital, Yoshinogawa, Japan

    Yasuyuki Omichi & Noriaki Mima

  4. Department of Orthopedics, Tokushima Prefectural Central Hospital, Tokushima, Japan

    Ryo Okada

  5. Department of Radiology, Mima Hospital, Yoshinogawa, Japan

    Tsutomu Enomoto & Hiroki Hayashi

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  1. Yasuyuki Omichi
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  2. Noriaki Mima
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Contributions

YO: conceptualization, data curation, formal analysis, writing – original draft. NM: data curation. KW: formal analysis. RO: data curation. YT: data curation. DH: data curation. TG: formal analysis. MM: conceptualization. TE: data curation. HH: data curation. KS: conceptualization, supervision. All authors have reviewed and approved the final manuscript.

Corresponding author

Correspondence to Yasuyuki Omichi.

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Informed consent was obtained from all individual participants included in the study.

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Omichi, Y., Mima, N., Wada, K. et al. Can TBS reference values be a valid indicator for clinical vertebral fracture? A cross-sectional study. J Bone Miner Metab 42, 60–68 (2024). https://doi.org/10.1007/s00774-023-01476-1

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  • DOI: https://doi.org/10.1007/s00774-023-01476-1

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