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Performance of FRAX in older adults with frailty: the Framingham Heart Study

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Abstract

Summary

We compared the performance of FRAX according to frailty status in 3554 individuals from the Framingham Study. During 10-year follow-up, 6.9% and 3.0% of participants with and without frailty experienced MOF. Discrimination profiles were lower in participants with frailty compared to those without, but they improved when FRAX included BMD.

Introduction

Frailty increases fracture risk. FRAX was developed to predict fractures but never validated in individuals with frailty. We aimed to compare the predictive performance of FRAX (v4.3) in individuals with and without frailty.

Methods

We conducted a cohort study using the Framingham Heart Study. Frailty was defined by the Fried phenotype. Major osteoporotic fractures (MOF) were ascertained from medical records during 10-year follow-up. To evaluate discrimination and calibration of FRAX, we calculated the area-under-the-receiver-operating characteristics curves (AUC) using logistic regression models and observed-to-predicted fracture probabilities. Analyses were stratified by frailty status.

Results

Frailty was present in 550/3554 (15.5%) of participants. Participants with frailty were older (81.1 vs. 67.6 years), female (68.6% vs. 55.1%), and had greater mean FRAX scores (MOF: 15.9% vs. 10.1%) than participants without frailty. During follow-up, 38 participants with frailty (6.9%) and 91 without (3.0%) had MOFs. The AUC for FRAX (without BMD) was lower in participants with frailty (0.584; 95% CI 0.504–0.663) compared to those without (0.695; 95% CI 0.649–0.741); p value = 0.02. Among participants with frailty, the AUC improved when FRAX included BMD (AUC 0.658, p value < 0.01). FRAX overestimated MOF risk, with larger overestimations in individuals without frailty. Performance of FRAX for hip fracture was similar.

Conclusion

FRAX may have been less able to identify frail individuals at risk for fracture, as compared with individuals without frailty, unless information on BMD is available. This suggests that BMD captures features important for fracture prediction in frail persons. Future fracture prediction models should be developed among persons with frailty.

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References

  1. Cesari M, Prince M, Thiyagarajan JA, De Carvalho IA, Bernabei R, Chan P et al (2016) Frailty: an emerging public health priority. J Am Med Dir Assoc 17(3):188–192

    Article  PubMed  Google Scholar 

  2. Collard RM, Boter H, Schoevers RA, Oude Voshaar RC (2012) Prevalence of frailty in community-dwelling older persons: a systematic review. J Am Geriatr Soc 60(8):1487–1492

    Article  PubMed  Google Scholar 

  3. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K (2013) Frailty in elderly people. Lancet 381(9868):752–762

    Article  PubMed  Google Scholar 

  4. Cesari M, Landi F, Vellas B, Bernabei R, Marzetti E (2014) Sarcopenia and physical frailty: two sides of the same coin. Front Aging Neurosci 6:192

    Article  PubMed  PubMed Central  Google Scholar 

  5. Middleton R, Poveda JL, OrfilaPernas F, Martinez Laguna D, Diez Perez A, Nogués X et al (2022) Mortality, falls, and fracture risk are positively associated with frailty: a SIDIAP cohort study of 890 000 patients. J Gerontol A Biol Sci Med Sci 77(1):148–154

    Article  PubMed  Google Scholar 

  6. Ofori-Asenso R, Chin KL, Mazidi M, Zomer E, Ilomaki J, Zullo AR et al (2019) Global incidence of frailty and prefrailty among community-dwelling older adults: a systematic review and meta-analysis. JAMA Netw Open 2(8):e198398

    Article  PubMed  PubMed Central  Google Scholar 

  7. Kanis JA, Johnell O, Oden A, Johansson H, McCloskey E (2008) FRAX and the assessment of fracture probability in men and women from the UK. Osteoporos Int 19(4):385–397

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kanis JA, Johansson H, Harvey NC, McCloskey EV (2018) A brief history of FRAX. Arch Osteoporos 13(1):118

    Article  PubMed  PubMed Central  Google Scholar 

  9. Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2007) Development of a nomogram for individualizing hip fracture risk in men and women. Osteoporos Int 18(8):1109–1117

    Article  CAS  PubMed  Google Scholar 

  10. Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2008) Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks. Osteoporos Int 19(10):1431–1444

    Article  CAS  PubMed  Google Scholar 

  11. Hippisley-Cox J, Coupland C (2012) Derivation and validation of updated QFracture algorithm to predict risk of osteoporotic fracture in primary care in the United Kingdom: prospective open cohort study. BMJ 344:e3427

    Article  PubMed  Google Scholar 

  12. Kanis JA, Johansson H, Oden A, Cooper C, McCloskey EV (2014) Worldwide uptake of FRAX. Arch Osteoporos 9:166

    Article  CAS  PubMed  Google Scholar 

  13. El Miedany Y (2020) FRAX: re-adjust or re-think. Arch Osteoporos 15(1):150

    Article  PubMed  PubMed Central  Google Scholar 

  14. Cummings SR, Nevitt MC, Browner WS, Stone K, Fox KM, Ensrud KE et al (1995) Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. N Engl J Med 332(12):767–73

    Article  CAS  PubMed  Google Scholar 

  15. Colón-Emeric CS, Biggs DP, Schenck AP, Lyles KW (2003) Risk factors for hip fracture in skilled nursing facilities: who should be evaluated? Osteoporos Int 14(6):484–489

    Article  PubMed  Google Scholar 

  16. Kanis JA, Harvey NC, Cooper C, Johansson H, Odén A, McCloskey EV (2016) 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

    Article  PubMed  PubMed Central  Google Scholar 

  17. Kanis JA, Chandran M, Chionh SB, Ganeson G, Harvey NC, Koh WP et al (2020) Use of age-dependent FRAX-based intervention thresholds for Singapore. Arch Osteoporos 15(1):104

    Article  PubMed  PubMed Central  Google Scholar 

  18. Lekamwasam S, Adachi JD, Agnusdei D, Bilezikian J, Boonen S, Borgström F et al (2012) A framework for the development of guidelines for the management of glucocorticoid-induced osteoporosis. Osteoporos Int 23(9):2257–2276

    Article  CAS  PubMed  Google Scholar 

  19. Gregson CL, Armstrong DJ, Bowden J, Cooper C, Edwards J, Gittoes NJL et al (2022) UK clinical guideline for the prevention and treatment of osteoporosis. Arch Osteoporos 17(1):58

    Article  PubMed  PubMed Central  Google Scholar 

  20. Clark P, Denova-Gutiérrez E, Zerbini C, Sanchez A, Messina O, Jaller JJ et al (2018) FRAX-based intervention and assessment thresholds in seven Latin American countries. Osteoporos Int 29(3):707–715

    Article  CAS  PubMed  Google Scholar 

  21. Kanis JA, Cooper C, Rizzoli R, Reginster JY (2019) European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int 30(1):3–44

    Article  CAS  PubMed  Google Scholar 

  22. Tsao CW, Vasan RS (2015) Cohort profile: the Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology. Int J Epidemiol 44(6):1800–1813

    Article  PubMed  PubMed Central  Google Scholar 

  23. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J et al (2001) Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 56(3):M146–M156

    Article  CAS  PubMed  Google Scholar 

  24. Millar CL, Dufour AB, Shivappa N, Habtemariam D, Murabito JM, Benjamin EJ et al (2022) A proinflammatory diet is associated with increased odds of frailty after 12-year follow-up in a cohort of adults. Am J Clin Nutr 115(2):334–343

    Article  PubMed  Google Scholar 

  25. Liu CK, Lyass A, Larson MG, Massaro JM, Wang N, D’Agostino RB Sr et al (2016) Biomarkers of oxidative stress are associated with frailty: the Framingham Offspring Study. Age (Dordr) 38(1):1

    Article  PubMed  Google Scholar 

  26. Berry SD, Kiel DP, Donaldson MG, Cummings SR, Kanis JA, Johansson H et al (2010) Application of the National Osteoporosis Foundation Guidelines to postmenopausal women and men: the Framingham Osteoporosis Study. Osteoporos Int 21(1):53–60

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Tucker KL, Chen H, Hannan MT, Cupples LA, Wilson PWF, Felson D et al (2002) Bone mineral density and dietary patterns in older adults: the Framingham Osteoporosis Study. Am J Clin Nutr 76(1):245–252

    Article  CAS  PubMed  Google Scholar 

  28. Dai Z, Zhang Y, Lu N, Felson DT, Kiel DP, Sahni S (2018) Association between dietary fiber intake and bone loss in the Framingham Offspring Study. J Bone Miner Res 33(2):241–249

    Article  CAS  PubMed  Google Scholar 

  29. Gagnon DR, McLean RR, Hannan MT, Cupples LA, Hogan M, Kiel DP (2010) Cross-calibration and comparison of variability in 2 bone densitometers in a research setting: the Framingham experience. J Clin Densitom 13(2):210–218

    Article  PubMed  PubMed Central  Google Scholar 

  30. Lu Y, Fuerst T, Hui S, Genant HK (2001) Standardization of bone mineral density at femoral neck, trochanter and Ward’s triangle. Osteoporos Int 12(6):438–444

    Article  CAS  PubMed  Google Scholar 

  31. Looker AC, Wahner HW, Dunn WL, Calvo MS, Harris TB, Heyse SP et al (1998) Updated data on proximal femur bone mineral levels of US adults. Osteoporos Int 8(5):468–489

    Article  CAS  PubMed  Google Scholar 

  32. Nevitt MC, Cummings SR, Browner WS, Seeley DG, Cauley JA, Vogt TM et al (1992) The accuracy of self-report of fractures in elderly women: evidence from a prospective study. Am J Epidemiol 135(5):490–499

    Article  CAS  PubMed  Google Scholar 

  33. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44(3):837–845

    Article  CAS  PubMed  Google Scholar 

  34. Banerjee S (2008) Analyzing receiver operating characteristic curves with SAS, by M Gönen. J Biopharm Stat 18(6):1228–9

    Article  Google Scholar 

  35. Harvey NC, Odén A, Orwoll E, Lapidus J, Kwok T, Karlsson MK et al (2018) Falls predict fractures independently of FRAX probability: a meta-analysis of the osteoporotic fractures in men (MrOS) study. J Bone Miner Res 33(3):510–516

    Article  PubMed  Google Scholar 

  36. Lundin H, Sääf M, Strender LE, Nyren S, Johansson SE, Salminen H (2017) Gait speed and one-leg standing time each add to the predictive ability of FRAX. Osteoporos Int 28(1):179–187

    Article  CAS  PubMed  Google Scholar 

  37. Sonnenfeld MM, Pimentel FL, Nasser EJ, Pompei LM, Fernandes CE, Steiner ML (2022) Performance of the fracture risk assessment tool associated with muscle mass measurements and handgrip to screen for the risk of osteoporosis in young postmenopausal women. Rev Bras Ginecol Obstet 44(1):32–39

    Article  PubMed  PubMed Central  Google Scholar 

  38. Vandenput L, Johansson H, McCloskey EV, Liu E, Åkesson KE, Anderson FA, et al (2022) Update of the fracture risk prediction tool FRAX: a systematic review of potential cohorts and analysis plan. Osteoporos Int 33(10):2103–2136. https://doi.org/10.1007/s00198-022-06435-6

  39. 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

    Article  PubMed  PubMed Central  Google Scholar 

  40. Dagan N, Cohen-Stavi C, Leventer-Roberts M, Balicer RD (2017) External validation and comparison of three prediction tools for risk of osteoporotic fractures using data from population based electronic health records: retrospective cohort study. BMJ 356:i6755

    Article  PubMed  PubMed Central  Google Scholar 

  41. Zhang J, Delzell E, Zhao H, Laster AJ, Saag KG, Kilgore ML et al (2012) Central DXA utilization shifts from office-based to hospital-based settings among Medicare beneficiaries in the wake of reimbursement changes. J Bone Miner Res 27(4):858–864

    Article  PubMed  Google Scholar 

  42. Greenspan S, Nace D, Perera S, Ferchak M, Fiorito G, Medich D et al (2012) Lessons learned from an osteoporosis clinical trial in frail long-term care residents. Clin Trials 9(2):247–256

    Article  PubMed  Google Scholar 

  43. Camacho PM, Petak SM, Binkley N, Diab DL, Eldeiry LS, Farooki A et al (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(Suppl 1):1–46

    Article  PubMed  Google Scholar 

  44. LeBoff MS, Greenspan SL, Insogna KL, Lewiecki EM, Saag KG, Singer AJ, et al (2022) The clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int 33(10):2049–2102. https://doi.org/10.1007/s00198-021-05900-y

  45. Kanis JA, Johansson H, Oden A, Dawson-Hughes B, Melton LJ 3rd, McCloskey EV (2010) The effects of a FRAX revision for the USA. Osteoporos Int 21(1):35–40

    Article  CAS  PubMed  Google Scholar 

  46. Crandall CJ, Larson J, Wright NC, Laddu D, Stefanick ML, Kaunitz AM et al (2020) Serial bone density measurement and incident fracture risk discrimination in postmenopausal women. JAMA Intern Med 180(9):1232–1240

    Article  PubMed  PubMed Central  Google Scholar 

  47. Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S et al (2014) Clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int 25(10):2359–2381

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We wanted to specifically acknowledge Dr. Natalia A. Gouskova for her input on the measures of AUC comparisons.

Funding

This work was supported by the National Institute of Health, National Institute on Aging (NIA), K24 AG070106, and the National Institute of Arthritis Musculoskeletal and Skin Diseases R01 AR041398. We would like to refer to the Framingham contract acknowledgment: National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. HHSN268201500001I).

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Correspondence to Sarah D. Berry.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Conflicts of interest

SS has institutional grants from Solarea Bio Inc., has reviewed grants for the American Egg Board’s Egg Nutrition Center and National Dairy Council, and was a scientific advisor to Institute for the Advancement of Food and Nutrition Sciences (ended 2022). EJS has received funding for her institution from Amgen. DPK acted as a data safety monitoring board member for Agnovos and a scientific advisory board member for Solarea Bio, Reneo, and Pfizer. DPK received grants from Amgen and Solarea Bio. DPK and SDB received royalties from Wolters Kluwer.

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Chattaris, T., Yang, L., Johansson, H. et al. Performance of FRAX in older adults with frailty: the Framingham Heart Study. Osteoporos Int 35, 265–275 (2024). https://doi.org/10.1007/s00198-023-06950-0

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  • DOI: https://doi.org/10.1007/s00198-023-06950-0

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