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Age-dependent FRAX-based assessment and intervention thresholds for therapeutic decision making in osteoporosis in the Malaysian population

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Abstract

Summary

Fracture risk stratification is crucial in countries with limited access to bone density measurement. 24.8% women were in the high-risk category while 30.4% were in the low-risk category. In the intermediate risk group, after recalculation of fracture risk with bone density, 38.3% required treatment. In more than half, treatment decisions can be made without bone density.

Purpose

We aimed to examine the role of age-dependent intervention thresholds (ITs) applied to the Fracture Risk Assessment (FRAX) tool in therapeutic decision making for osteoporosis in the Malaysian population.

Methods

Data were collated from 1380 treatment-naïve postmenopausal women aged 40–85 years who underwent bone mineral density (BMD) measurements for clinical reasons. Age-dependent ITs, for both major osteoporotic fracture (MOF) and hip fracture (HF), were calculated considering a woman with a BMI of 25 kg/m2, aged between 40 and 85years, with a prior fragility fracture, sans other clinical risk factors. Those with fracture probabilities equal to or above upper assessment thresholds (UATs) were considered to have high fracture risk. Those below the lower assessment thresholds (LATs) were considered to have low fracture risk.

Results

The ITs of MOF and HF ranged from 0.7 to 18% and 0.2 to 8%, between 40 and 85years. The LATs of MOF ranged from 0.3 to 11%, while those of HF ranged from 0.1 to 5.2%. The UATs of MOF and HF were 0.8 to 21.6% and 0.2 to 9.6%, respectively. In this study, 24.8% women were in the high-risk category while 30.4% were in the low-risk category. Of the 44.8% (n=618) in the intermediate risk group, after recalculation of fracture risk with BMD input, 38.3% (237/618) were above the ITs while the rest (n=381, 61.7%) were below the ITs. Judged by the Youden Index, 11.5% MOF probability which was associated with a sensitivity of 0.62 and specificity of 0.83 and 4.0% HF probability associated with a sensitivity of 0.63 and a specificity 0.82 were found to be the most appropriate fixed ITs in this analysis.

Conclusion

Less than half of the study population (44.8%) required BMD for osteoporosis management when age-specific assessment thresholds were applied. Therefore, in more than half, therapeutic decisions can be made without BMD based on these assessment thresholds.

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Data will be provided upon request.

References

  1. Subramaniam S, Chan C-Y, Soelaiman I-N, Mohamed N, Muhammad N, Ahmad F, Abd Manaf MR, Ng P-Y, Jamil NA, Chin K-Y (2019) Prevalence and predictors of osteoporosis among the Chinese population in Klang Valley, Malaysia. App Sci 9(9):1820. https://doi.org/10.3390/app9091820

    Article  Google Scholar 

  2. Pietschmann P, Rauner M, Sipos W, Kerschan-Schindl K (2009) Osteoporosis: an age-related and gender-specific disease--a mini-review. Gerontology 55(1):3–12. https://doi.org/10.1159/000166209. (Epub 2008 Oct 24)

    Article  PubMed  Google Scholar 

  3. Salari N, Darvishi N, Bartina Y, Larti M, Kiaei A, Hemmati M, Shohaimi S, Mohammadi M (2021) Global prevalence of osteoporosis among the world older adults: a comprehensive systematic review and meta-analysis. J Orthop Surg Res 16(1):669. https://doi.org/10.1186/s13018-021-02821-8. (PMID: 34774085; PMCID: PMC8590304)

    Article  PubMed  PubMed Central  Google Scholar 

  4. Barnsley J, Buckland G, Chan PE, Ong A, Ramos AS, Baxter M, Laskou F, Dennison EM, Cooper C, Patel HP (2021) Pathophysiology and treatment of osteoporosis: challenges for clinical practice in older people. Aging Clin Exp Res 33(4):759–773. https://doi.org/10.1007/s40520-021-01817-y. (Epub 2021 Mar 20. PMID: 33742387; PMCID: PMC8084810)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S, Lindsay R (2014) National Osteoporosis Foundation. Clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int 25(10):2359–2381. https://doi.org/10.1007/s00198-014-2794-2. (Epub 2014 Aug 15. Erratum in: Osteoporos Int. 2015 Jul;26(7):2045-7. PMID: 25182228; PMCID: PMC4176573)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Cooper C, Cole ZA, Holroyd CR, Earl SC, Harvey NC, Dennison EM, Melton LJ, Cummings SR, Kanis JA (2011) IOF CSA Working Group on Fracture Epidemiology. Secular trends in the incidence of hip and other osteoporotic fractures. Osteoporos Int 22(5):1277–1288. https://doi.org/10.1007/s00198-011-1601-6. (Epub 2011 Apr 2. PMID: 21461721; PMCID: PMC3546313)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Johnell O, Kanis JA (2006) An estimate of the worldwide prevalence and disability associated with osteoporotic fractures. Osteoporos Int 17(12):1726–1733. https://doi.org/10.1007/s00198-006-0172-4. (Epub 2006 Sep 16)

    Article  CAS  PubMed  Google Scholar 

  8. Choksi P, Jepsen KJ, Clines GA (2018) The challenges of diagnosing osteoporosis and the limitations of currently available tools. Clin Diabetes Endocrinol 29(4):12. https://doi.org/10.1186/s40842-018-0062-7. (PMID: 29862042; PMCID: PMC5975657)

    Article  Google Scholar 

  9. Lewiecki EM, Silverman SL (2006) Redefining osteoporosis treatment: who to treat and how long to treat. Arq Bras Endocrinol Metabol 50(4):694–704. https://doi.org/10.1590/s0004-27302006000400015

    Article  PubMed  Google Scholar 

  10. Cummings SR, Nevitt MC, Browner WS, Stone K, Fox KM, Ensrud KE, Cauley J, Black D, Vogt TM (1995) Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. N Engl J Med 332(12):767–773. https://doi.org/10.1056/NEJM199503233321202

    Article  CAS  PubMed  Google Scholar 

  11. Chen SJ, Chen YJ, Cheng CH, Hwang HF, Chen CY, Lin MR (2016) Comparisons of different screening tools for identifying fracture/osteoporosis risk among community-dwelling older people. Medicine (Baltimore) 95(20):e3415. https://doi.org/10.1097/MD.0000000000003415. (Erratum in: Medicine (Baltimore). 2016 Aug 26;95(34):e0553. PMID: 27196447; PMCID: PMC4902389)

    Article  PubMed  Google Scholar 

  12. Kanis JA, Harvey NC, Johansson H, Odén A, McCloskey EV, Leslie WD (2017) Overview of fracture prediction tools. J Clin Densitom 20(3):444–450. https://doi.org/10.1016/j.jocd.2017.06.013. (Epub 2017 Jul 14. PMID: 28716500; PMCID: PMC5663341)

    Article  PubMed  PubMed Central  Google Scholar 

  13. Rubin KH, Friis-Holmberg T, Hermann AP, Abrahamsen B, Brixen K (2013) Risk assessment tools to identify women with increased risk of osteoporotic fracture: complexity or simplicity? A systematic review. J Bone Miner Res 28(8):1701–1717. https://doi.org/10.1002/jbmr.1956

    Article  PubMed  Google Scholar 

  14. Lim LS, Hoeksema LJ (2009) Sherin K; ACPM Prevention Practice Committee. Screening for osteoporosis in the adult U.S. population: ACPM position statement on preventive practice. Am J Prev Med 36(4):366–375. https://doi.org/10.1016/j.amepre.2009.01.013

    Article  PubMed  Google Scholar 

  15. Kanis JA, Hans D, Cooper C, Baim S, Bilezikian JP, Binkley N, Cauley JA, Compston JE, Dawson-Hughes B, El-Hajj Fuleihan G, Johansson H, Leslie WD, Lewiecki EM, Luckey M, Oden A, Papapoulos SE, Poiana C, Rizzoli R, Wahl DA (2011) McCloskey EV; Task Force of the FRAX Initiative. Interpretation and use of FRAX in clinical practice. Osteoporos Int 22(9):2395–2411. https://doi.org/10.1007/s00198-011-1713-z. (Epub 2011 Jul 21)

    Article  CAS  PubMed  Google Scholar 

  16. Johansson H, Kanis JA, Oden A, Johnell O, McCloskey E (2009) BMD, clinical risk factors and their combination for hip fracture prevention. Osteoporos Int 20(10):1675–1682. https://doi.org/10.1007/s00198-009-0845-x. (Epub 2009 Mar 17. PMID: 19291344)

    Article  CAS  PubMed  Google Scholar 

  17. Lekamwasam S, Abeygunasekara T, Rathnayake N, Liyanage G, Subasinghe S (2022) Age-dependent assessment thresholds to optimize patient care in a resource-limited setting: an analysis based on the Sri Lankan FRAX model. Arch Osteoporos 17(1):77. https://doi.org/10.1007/s11657-022-01118-5. (PMID: 35553258)

    Article  PubMed  Google Scholar 

  18. Kebaetse M, Nkhwa S, Mogodi M et al (2021) A country specific FRAX model for Botswana. Arch Osteoporos 16(1):90. https://doi.org/10.1007/s11657-021-00965-y. (PMID: 34100118; PMCID: PMC8184541)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Naureen G, Johansson H, Iqbal R, Jafri L, Khan AH, Umer M, Liu E, Vandenput L, Lorentzon M, Harvey NC, McCloskey EV, Kanis JA (2021) A surrogate FRAX model for Pakistan. Arch Osteoporos 16(1):34. https://doi.org/10.1007/s11657-021-00894-w. (PMID: 33595723; PMCID: PMC7889560)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Chandran M, Kwee A (2022) Treatment indications and thresholds of intervention: consensus and controversies in osteoporosis. Climacteric 25(1):29–36. https://doi.org/10.1080/13697137.2021.1951205. (Epub 2021 Jul 27)

    Article  CAS  PubMed  Google Scholar 

  21. Kanis JA, Harvey NC, Cooper C, Johansson H, Odén A, EV MC (2016) Advisory Board of the National Osteoporosis Guideline Group. A systematic review of intervention thresholds based on FRAX: a report prepared for the National Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos 11(1):25. https://doi.org/10.1007/s11657-016-0278-z. (Epub 2016 Jul 27. PMID: 27465509; PMCID: PMC4978487)

    Article  PubMed  PubMed Central  Google Scholar 

  22. Chia KK, Haron J, Nik Malek NFS (2021) Accuracy of computed tomography attenuation value of lumbar vertebra to assess bone mineral density. Malays J Med Sci 28(1):41–50. https://doi.org/10.21315/mjms2021.28.1.6

    Article  PubMed  PubMed Central  Google Scholar 

  23. Ong TIW, Lim LL, Chan SP, Chee WSS, Ch’ng ASH, Chong EGM, Damodaran P, Hew FL, Ibrahim LB, Khor HM, Lai PSM, Lee JK, Lim AL, Lim BP, Paramasivam SS, Ratnasingam J, Siow YS, Tan ATB, Thiagarajan N, Yeap SS (2023) A summary of the Malaysian clinical practice guidelines on the management of postmenopausal osteoporosis. Osteoporosis Sarcopenia 9(2):60–69. https://doi.org/10.1016/j.afos.2023.06.002

  24. Compston J, Cooper A, Cooper C, Francis R, Kanis JA, Marsh D, McCloskey EV, Reid DM, Selby P, Wilkins M (2009) National Osteoporosis Guideline Group (NOGG). Guidelines for the diagnosis and management of osteoporosis in postmenopausal women and men from the age of 50 years in the UK. Maturitas 62(2):105–108. https://doi.org/10.1016/j.maturitas.2008.11.022. (Epub 2009 Jan 8. PMID: 19135323)

    Article  CAS  PubMed  Google Scholar 

  25. Dimai et al (2022) Osteoporosis treatment in Austria-assessment of FRAX-based intervention thresholds for high and very high fracture risk. Arch Osteoporos 17(1):141. https://doi.org/10.1007/s11657-022-01175-w. (PMID: 36357621; PMCID: PMC9649455)

    Article  PubMed  PubMed Central  Google Scholar 

  26. Gavilanez EL, Luis IN, Mario NG, Johansson H, Harvey NC, Lorentzon M, Liu E, Vandenput L, McCloskey EV, Kanis JA (2022) An assessment of intervention thresholds for high fracture risk in Chile. Arch Osteoporos 18(1):11. https://doi.org/10.1007/s11657-022-01198-3

    Article  PubMed  Google Scholar 

  27. Johansson H, Chan SP, Hew FL, Yeap SS, Siri Z, Liu E, Lorentzon M, Vandenput L, Harvey N, Mc Closkey E, Kanis J (2022) A surrogate FRAX model for Malaysia. World Congress on Osteoporosis, Osteoarthritis and Musculoskeletal Disease. Virtual Congress. Abstract Book. pp 337–338. https://virtual.wco-iof-esceo.org/sites/wco_22/pdf/WCO22-AbstractBook.pdf

  28. Kanis JA, Johansson H, Harvey NC, Lorentzon M, Liu E, Vandenput L, McCloskey EV (2021) An assessment of intervention thresholds for very high fracture risk applied to the NOGG guidelines: a report for the National Osteoporosis Guideline Group (NOGG). Osteoporos Int 32(10):1951–1960. https://doi.org/10.1007/s00198-021-05942-2. (Epub 2021 Apr 4)

    Article  CAS  PubMed  Google Scholar 

  29. Gregson CL, Armstrong DJ, Bowden J, Cooper C, Edwards J, Gittoes NJL, Harvey N, Kanis J, Leyland S, Low R, McCloskey E, Moss K, Parker J, Paskins Z, Poole K, Reid DM, Stone M, Thomson J, Vine N, Compston J (2022) UK clinical guideline for the prevention and treatment of osteoporosis. Arch Osteoporos 17(1):58. https://doi.org/10.1007/s11657-022-01061-5. (Erratum in: Arch Osteoporos. 2022 May 19;17(1):80. PMID: 35378630; PMCID: PMC8979902)

    Article  PubMed  PubMed Central  Google Scholar 

  30. Chandran M, McCloskey EV, Thu WPP, Logan S, Hao Y, Tay D, Ang WC, Aung TKK, Choo KS, Ali A, Yan SX, Huang XF, Liu XM, Yong EL, Lekamwasam S (2018) FRAX® based intervention thresholds for management of osteoporosis in Singaporean women. Arch Osteoporos 13(1):130. https://doi.org/10.1007/s11657-018-0542-5

    Article  CAS  PubMed  Google Scholar 

  31. Lekamwasam S (2013) Sri Lankan FRAX model and country-specific intervention thresholds. Arch Osteoporos 8:148. https://doi.org/10.1007/s11657-013-0148-x. (Epub 2013 Aug 22)

    Article  PubMed  Google Scholar 

  32. Chen JF, Yu SF, Hsu CY, Chiu WC, Wu CH, Lai HM, Chen YC, Su YJ, Chen JF, Cheng TT (2019) The role of bone mineral density in therapeutic decision-making using the Fracture Risk Assessment Tool (FRAX): a sub-study of the Taiwan OsteoPorosis Survey (TOPS). Arch Osteoporos 14(1):101. https://doi.org/10.1007/s11657-019-0653-7

    Article  PubMed  Google Scholar 

  33. Teeratakulpisarn N, Charoensri S, Theerakulpisut D, Pongchaiyakul C (2021) FRAX score with and without bone mineral density: a comparison and factors affecting the discordance in osteoporosis treatment in Thais. Arch Osteoporos 16(1):44. https://doi.org/10.1007/s11657-021-00911-y

    Article  PubMed  Google Scholar 

  34. Tamaki J, Iki M, Kadowaki E, Sato Y, Kajita E, Kagamimori S, Kagawa Y, Yoneshima H (2011) Fracture risk prediction using FRAX®: a 10-year follow-up survey of the Japanese Population-Based Osteoporosis (JPOS) Cohort Study. Osteoporos Int 22(12):3037–3045. https://doi.org/10.1007/s00198-011-1537-x. (Epub 2011 Jan 29)

    Article  CAS  PubMed  Google Scholar 

  35. Fraser LA, Langsetmo L, Berger C, Ioannidis G, Goltzman D, Adachi JD, Papaioannou A, Josse R, Kovacs CS, Olszynski WP, Towheed T, Hanley DA, Kaiser SM, Prior J, Jamal S, Kreiger N, Brown JP, Johansson H, Oden A, McCloskey E, Kanis JA, Leslie WD, CaMos Research Group (2011) Fracture prediction and calibration of a Canadian FRAX® tool: a population-based report from CaMos. Osteoporos Int 22(3):829–837. https://doi.org/10.1007/s00198-010-1465-1. (Epub 2010 Dec 16. PMID: 21161508; PMCID: PMC5101064)

    Article  PubMed  Google Scholar 

  36. Kyriakos G, Vidal-Casariego A, Quiles-Sánchez LV, Calleja-Fernández A, Ávila-Turcios D, Urosa-Maggi JA, Ballesteros-Pomar MD, Cano-Rodríguez I (2017) A comparative study between the implementation of the FRIDEX calibration and the NOGG guideline in the management of osteoporosis in routine clinical practice. Reumatol Clin 13(5):258–263. https://doi.org/10.1016/j.reuma.2016.05.007. (English, Spanish. Epub 2016 Jun 29)

    Article  PubMed  Google Scholar 

  37. Nagendra L, Bhavani N, Menon VU, Pavithran PV, Menon AS, Abraham N, Nair V, Kumar H (2021) FRAX-based osteoporosis treatment guidelines for resource-poor settings in India. Arch Osteoporos 16. https://doi.org/10.1007/s11657-021-00931-8

  38. Leslie WD, Morin S, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA, Manitoba Bone Density Program (2012) Fracture risk assessment without bone density measurement in routine clinical practice. Osteoporos Int 23(1):75–85. https://doi.org/10.1007/s00198-011-1747-2. (Epub 201)

    Article  CAS  PubMed  Google Scholar 

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The study was supported by the Malaysian Osteoporosis Society.

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Correspondence to Jeyakantha Ratnasingam.

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Ratnasingam, J., Niyaz, M., Mariyappan, S. et al. Age-dependent FRAX-based assessment and intervention thresholds for therapeutic decision making in osteoporosis in the Malaysian population. Arch Osteoporos 19, 18 (2024). https://doi.org/10.1007/s11657-024-01371-w

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