Skip to main content

Advertisement

Log in

Fracture risk prediction using FRAX®: a 10-year follow-up survey of the Japanese Population-Based Osteoporosis (JPOS) Cohort Study

  • Original Article
  • Published:
Osteoporosis International Aims and scope Submit manuscript

Abstract

Summary

We evaluated the predictive ability of FRAX® in a cohort of 815 Japanese women. The observed 10-year fracture rate did not differ significantly from that predicted by FRAX®. The predictive ability of FRAX® without femoral neck bone mineral density (BMD) was similar to that with femoral neck BMD.

Introduction

We evaluated the ability of the Japanese version of FRAX®, a World Health Organization fracture risk assessment tool, to predict the 10-year probability of osteoporotic fracture.

Methods

Self-reported major osteoporotic fracture (N = 43) and hip fracture (N = 4) events were ascertained in the 10-year follow-up survey of the Japanese Population-Based Osteoporosis Cohort Study. Participants were 815 women aged 40–74 years at the baseline survey. Receiver operating characteristic curve analysis compared FRAX® with multiple logistic models based on age, body weight, and femoral neck BMD.

Results

The number of observed major osteoporotic or hip fracture events did not differ significantly from the number of events predicted by the FRAX® model (with or without BMD). The area under the curve (AUC) value for FRAX® with BMD for predicting major osteoporotic fractures was similar to that of a logistic model with age, body weight, and BMD (0.69 vs. 0.71, respectively; p = 0.198); the AUC of FRAX® with BMD for predicting hip fractures was similar to that of a model based on age and BMD (0.88 vs. 0.89, respectively; p = 0.164). The AUCs of FRAX® without BMD for predicting major osteoporotic and hip fractures were similar to those with BMD (0.69 vs. 0.67, respectively; p = 0.121; 0.88 vs. 0.86, respectively; p = 0.445).

Conclusions

The Japanese version of FRAX® without BMD estimated the 10-year probability of osteoporotic fracture in this population with few clinical risk factors as similar to that of FRAX® with BMD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Gullberg B, Johnell O, Kanis JA (1997) World-wide projections for hip fracture. Osteoporos Int 7:407–413

    Article  PubMed  CAS  Google Scholar 

  2. Report of a WHO Scientific Group (2003) Prevention and management of osteoporosis. WHO technical report series 921. World Health Organization, Geneva, p 37

    Google Scholar 

  3. National Institute of Population and Social Security Research (2010) Population Projections for Japan—A Supplement to the 2006 Revision-, Health and Welfare Statistics Association. Tokyo, p 105

  4. Kanis JA, Oden A, Johnell O, Johansson H, De Laet C, Brown J, Burckhardt P, Cooper C, Christiansen C, Cummings S, Eisman JA, Fujiwara S, Glüer C, Goltzman D, Hans D, Krieg MA, La Croix A, McCloskey E, Mellstrom D, Melton LJ 3rd, Pols H, Reeve J, Sanders K, Schott AM, Silman A, Torgerson D, van Staa T, Watts NB, Yoshimura N (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

    Article  PubMed  CAS  Google Scholar 

  5. Kanis JA on behalf of the World Health Organization Scientific Group (2007) Assessment of osteoporosis at the primary health-care level. Technical Report. World Health Organization Collaborating Centre for Metabolic Bone Diseases, University of Sheffield, UK, p189-217. http://www.shef.ac.uk/FRAX/pdf/WHO_Technical_Report.pdf

  6. Fujiwara S, Kagasi F, Masunari N, Naito K, Suzuki G, Fukunage M (2003) Fracture prediction from bone mineral density in Japanese men and women. J Bone Min Res 18:1547–1553

    Article  Google Scholar 

  7. Yoshimura N, Takijiri T, Kinoshita H, Danjoh S, Kasamatsu I, Morioka S, Sakato K, Hashimoto T, Takeshita T (2004) Characteristics and cause of bone mineral densities among fast bone losers in a rural Japanese community: the Miyama Study. Osteoporos Int 15:139–144

    Article  PubMed  Google Scholar 

  8. Pluskiewicz W, Adamczyk P, Franek E, Leszczynski P, Sewerynek E, Wichrowska H, Napiorkowska L, Kostyk T, Stuss M, Stepien-Klos W, Golba KS, Drozdzowska B (2010) Ten-year probability of osteoporotic fracture in 2012 Polish women assessed by FRAX and nomogram by Nguyen et al.—conformity between methods and their clinical utility. Bone 46:1661–1667

    Article  PubMed  CAS  Google Scholar 

  9. Sandhu SK, Nguyen ND, Center JR, Pocock NA, Eisman JA, Nguyen TV (2010) Prognosis of fracture: evaluation of predictive accuracy of the FRAX algorithm and Garvan nomogram. Osteoporos Int 21:863–871

    Article  PubMed  CAS  Google Scholar 

  10. Iki M, Kagamimori S, Kagawa Y, Matsuzaki T, Yoneshima H, Marumo F (2001) Bone mineral density of the spine, hip and distal forearm in representative samples of the Japanese female population: Japanese Population-Based Osteoporosis (JPOS) Study. Osteoporps Int 12:529–537

    Article  CAS  Google Scholar 

  11. Iki M, Morita A, Ikeda Y, Sato Y, Akiba T, Matsumoto T, Nishino H, Kagamimori S, Kagawa Y, Yoneshima H, JPOS Study Group (2006) Biochemical markers of bone turnover predict bone loss in perimenopausal women but not in postmenopausal women—the Japanese Population-Based Osteoporosis (JPOS) Cohort Study. Osteoporos Int 17:1086–1095

    Article  PubMed  CAS  Google Scholar 

  12. Fujiwara S, Nakamura T, Orimo H, Hosoi T, Gorai I, Oden A, Johansson H, Kanis JA (2008) Development and application of a Japanese model of the WHO fracture risk assessment tool (FRAXTM). Osteoporos Int 19:429–435

    Article  PubMed  CAS  Google Scholar 

  13. McCloskey EV, Spector TD, Eyres KS, Fern ED, O’Rourke N, Vasikaran S, Kanis JA (1993) The assessment of vertebral deformity: a method for use in population studies and clinical trials. Osteoporos Int 3:138–147

    Article  PubMed  CAS  Google Scholar 

  14. Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petrov BN, Csaki F (eds) Proceedings of the Second International Symposium on Information Theory. Akademiai Kiado, Budapest, pp 267–281

    Google Scholar 

  15. Sakamoto Y, Ishiguro M, Kitagawa G (1986) Akaike information criterion statistics. D. Reidel, Dordrecht, pp 56–85

    Google Scholar 

  16. Delong ER, Delong DM, Charke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845

    Article  PubMed  CAS  Google Scholar 

  17. Obuchowski NC (2002) Prospective studies of diagnostic test accuracy when disease prevalence is low. Biostatistics 3:477–492

    Article  PubMed  Google Scholar 

  18. Ensrud KE, Lui LY, Taylor BC, Schousboe JT, Donaldson MG, Fink HA, Cauley JA, Hillier TA, Browner WS, Cummings SR, Study of Osteoporotic Fractures Research Group (2009) A comparison of prediction models for fractures in older women: is more better? Arch Intern Med 169:2087–2094

    Article  PubMed  Google Scholar 

  19. Orimo H, Yaegashi Y, Onoda T, Fukushima Y, Hosoi T, Sakata K (2009) Hip fracture incidence in Japan: estimates of new patients in 2007 and 20-year trends. Arch Osteoporos 4:71–77

    Article  PubMed  Google Scholar 

  20. Hagino H, Furukawa K, Fujiwara S, Okano T, Katagiri H, Yamamoto K, Teshima R (2009) Recent trends in the incidence and lifetime risk of hip fracture in Tottori, Japan. Osteoporos Int 20:543–548

    Article  PubMed  CAS  Google Scholar 

  21. Ismail AA, O’Neill TW, Cockerill W, Finn JD, Cannata JB, Hoszowski K, Johnell O, Matthis C, Raspe H, Raspe A, Reeve J, Silman AJ (2000) Validity of self-report of fractures: results from a prospective study in men and women across Europe. EPOS Study Group. European Prospective Osteoporosis Study Group. Osteoporos Int 11:248–254

    Article  PubMed  CAS  Google Scholar 

  22. Siggeirsdottir K, Aspelund T, Sigurdsson G, Mogensen B, Chang M, Jonsdottir B, Eiriksdottir G, Launer LJ, Harris TB, Jonsson BY, Gudnason V (2007) Inaccuracy in self-report of fractures may underestimate association with health outcomes when compared with medical record based fracture registry. Eur J Epidemiol 22:631–639

    Article  PubMed  Google Scholar 

  23. Hagino H, Katagiri H, Okano T, Yamamoto K, Teshima R (2005) Increasing incidence of hip fracture in Tottori Prefecture, Japan: trend from 1986 to 2001. Osteoporos Int 16:1963–1968

    Article  PubMed  Google Scholar 

  24. Ministry of Health, Labour and Welfare of Japan (1998) National health and nutrition survey in Japan, 1996. Dai-Ichi shyuppan, Tokyo, p 52

    Google Scholar 

  25. Rea JA, Chen MB, Li J, Blake GM, Steiger P, Genant HK, Fogelman I (2000) Morphometric X-ray absorptiometry and morphometric radiography of the spine: a comparison of prevalent vertebral deformity identification. J Bone Miner Res 15:564–574

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This study was conducted by the JPOS Study Group, comprising Fumiaki Marumo (Chairman of the Study Group, Professor Emeritus, Tokyo Medical and Dental University), Toshihisa Matsuzaki (Co-chairman of the Study Group, Institute of Comprehensive Community Care), Tomoharu Matsukura (Kanazawa University), and Takashi Yamagami (Hokuriku Health Service Association), along with the authors. Financial support for the baseline survey was provided by the Japan Milk Promotion Board and the Japan Dairy Council. The follow-up surveys were supported by Grants-in-aid for Scientific Research (B#10470114, 1998–2000, B #14370147, 2002–2003, B#18390201, 2006–2008, and C#18590619, 2006-9) from the Japanese Society for the Promotion of Science, a grant in 2000–2002 from the Research Society for Metabolic Bone Diseases, Japan, and a Grand-in-Aid to study Milk Nutrition (2006) from the Japan Dairy Association. The authors wish to express special thanks to the personnel of the health departments of Miyako-jima City, Sanuki City, and Nishi-Aizu Town for their excellent support of the study, and to those from SRL, Tokyo, Japan; Toyo Medic, Osaka, Japan; and Toyukai Medical Corporation, Tokyo, Japan, for their technical assistance with the surveys.

Conflicts of interest

None

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Iki.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tamaki, J., Iki, M., Kadowaki, E. et al. Fracture risk prediction using FRAX®: a 10-year follow-up survey of the Japanese Population-Based Osteoporosis (JPOS) Cohort Study. Osteoporos Int 22, 3037–3045 (2011). https://doi.org/10.1007/s00198-011-1537-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00198-011-1537-x

Keywords

Navigation