Performance of risk assessment instruments for predicting osteoporotic fracture risk: a systematic review
- 840 Downloads
We systematically reviewed the literature on the performance of osteoporosis absolute fracture risk assessment instruments. Relatively few studies have evaluated the calibration of instruments in populations separate from their development cohorts, and findings are mixed. Many studies had methodological limitations making susceptibility to bias a concern.
The aim of this study was to systematically review the literature on the performance of osteoporosis clinical fracture risk assessment instruments for predicting absolute fracture risk, or calibration, in populations other than their derivation cohorts.
We performed a systematic review, and MEDLINE, Embase, Cochrane Library, and multiple other literature sources were searched. Inclusion and exclusion criteria were applied and data extracted, including information about study participants, study design, potential sources of bias, and predicted and observed fracture probabilities.
A total of 19,949 unique records were identified for review. Fourteen studies met inclusion criteria. There was substantial heterogeneity among included studies. Six studies assessed the WHO’s Fracture Risk Assessment (FRAX) instrument in five separate cohorts, and a variety of risk assessment instruments were evaluated in the remainder of the studies. Approximately half found good instrument calibration, with observed fracture probabilities being close to predicted probabilities for different risk categories. Studies that assessed the calibration of FRAX found mixed performance in different populations. A similar proportion of studies that evaluated simple risk assessment instruments (≤5 variables) found good calibration when compared with studies that assessed complex instruments (>5 variables). Many studies had methodological features making them susceptible to bias.
Few studies have evaluated the performance or calibration of osteoporosis fracture risk assessment instruments in populations separate from their development cohorts. Findings are mixed, and many studies had methodological limitations making susceptibility to bias a possibility, raising concerns about use of these tools outside of the original derivation cohorts. Further studies are needed to assess the calibration of instruments in different populations prior to widespread use.
KeywordsCalibration Fracture Osteoporosis Risk assessment Systematic review
The authors thank the following individuals who kindly provided requested data from their papers: MJ Bolland, GS Collins, E Czerwinski, B Ettinger, DA Hanley, A Kumorek, WD Leslie, L Langsetmo, and J Tamaki.
Sources of funding
Smita Nayak was supported by grant 7R01AR060809-03 from the National Institute of Arthritis and Musculoskeletal and Skin Diseases; Susan L. Greenspan was supported by NIH grants P30AG024827 and R01AG028068-01A2.
Conflicts of interest
- 1.Lin JT, Lane JM (2004) Osteoporosis: a review. Clin Orthop Relat Res 126–134Google Scholar
- 4.U.S. Department of Health and Human Services (2004) Bone health and osteoporosis: a report of the Surgeon General. U.S. Department of Health and Human Services, Office of the Surgeon General, RockvilleGoogle Scholar
- 8.Leslie WD, Schousboe JT (2011) A review of osteoporosis diagnosis and treatment options in new and recently updated guidelines on case finding around the world. Curr Osteoporos Rep 9:129–140Google Scholar
- 10.Leslie WD, Berger C, Langsetmo L, Lix LM, Adachi JD, Hanley DA, Ioannidis G, Josse RG, Kovacs CS, Towheed T, Kaiser S, Olszynski WP, Prior JC, Jamal S, Kreiger N, Goltzman D (2011) Construction and validation of a simplified fracture risk assessment tool for Canadian women and men: results from the CaMos and Manitoba cohorts. Osteoporos Int 22:1873–1883Google Scholar
- 11.Bolland MJ, Siu AT, Mason BH, Horne AM, Ames RW, Grey AB, Gamble GD, Reid IR (2011) Evaluation of the FRAX and Garvan fracture risk calculators in older women. J Bone Miner Res 26:420–427Google Scholar
- 12.Tamaki J, Iki M, Kadowaki E, Sato Y, Kajita E, Kagamimori S, Kagawa Y, Yoneshima H (2011) Fracture risk prediction using FRAX(R): a 10-year follow-up survey of the Japanese Population-Based Osteoporosis (JPOS) Cohort Study. Osteoporos Int 22:3037–3045Google Scholar
- 13.Lo JC, Pressman AR, Chandra M, Ettinger B (2011) Fracture risk tool validation in an integrated healthcare delivery system. Am J Manag Care 17:188–194Google Scholar
- 14.Leslie WD, Lix LM, Johansson H, Oden A, McCloskey E, Kanis JA (2010) Independent clinical validation of a Canadian FRAX tool: fracture prediction and model calibration. J Bone Miner Res 25:2350–2358Google Scholar
- 15.Langsetmo L, Nguyen TV, Nguyen ND, Kovacs CS, Prior JC, Center JR, Morin S, Josse RG, Adachi JD, Hanley DA, Eisman JA (2011) Independent external validation of nomograms for predicting risk of low-trauma fracture and hip fracture. CMAJ 183:E107–114Google Scholar
- 18.Leslie WD, Lix LM (2010) Simplified 10-year absolute fracture risk assessment: a comparison of men and women. J Clin Densitom 13:141–146Google Scholar
- 21.Collins GS, Mallett S, Altman DG (2011) Predicting risk of osteoporotic and hip fracture in the United Kingdom: prospective independent and external validation of QFractureScores. BMJ 342:d3651Google Scholar
- 22.Czerwinski E, Kanis JA, Osieleniec J, Kumorek A, Milert A, Johansson H, McCloskey EV, Gorkiewicz M (2011) Evaluation of FRAX to characterise fracture risk in Poland. Osteoporos Int 22:2507–2512Google Scholar
- 24.Azagra R, Roca G, Encabo G, Prieto D, Aguye A, Zwart M, Guell S, Puchol N, Gene E, Casado E, Sancho P, Sola S, Toran P, Iglesias M, Sabate V, Lopez-Exposito F, Ortiz S, Fernandez Y, Diez-Perez A (2011) Prediction of absolute risk of fragility fracture at 10 years in a Spanish population: validation of the WHO FRAX TM tool in Spain. BMC Musculoskelet Disord 12:30PubMedCentralPubMedCrossRefGoogle Scholar
- 26.Cheung, EYN, Bow CH, Cheung CL, Soong C, Yeung S, Loong C, Kung A (2012) Discriminative value of FRAX for fracture prediction in a cohort of Chinese postmenopausal women. Osteoporos Int 23: 871–878Google Scholar
- 30.Ensrud KE, Lu 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(22):2087–2094PubMedCentralPubMedCrossRefGoogle Scholar
- 33.Hans D, Durosier C, Kanis JA, Johansson H, Schott-Pethelaz A-M, Krieg M-A (2008) Assessment of the 10-year probability of osteoporotic hip fracture combining clinical risk factors and heel bone ultrasound: the EPISEM prospective cohort of 12,958 elderly women. J Bone Miner Res 23(7):1045–1051PubMedCrossRefGoogle Scholar
- 35.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, Gluer C, Goltzman D, Hans D, Krieg M-A, La Croix A, McCloskey E, Mellstrom D, Melton LJ 3rd, Pols H, Reeve J, Sanders K, Schott A-M, 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(8):1033–1046PubMedCrossRefGoogle Scholar
- 38.Moayyeri A, Welch A, Luben RN, Wareham NJ, Bingham S, Khaw KT (2007) Height loss predicts fractures in middle aged and older men and women: European prospective investigation into cancer-Norfolk population cohort study. J Bone Miner Res 22(Suppl 1):S79Google Scholar
- 39.Nguyen ND, Frost SA, Center JR, Eisman JA, Nguyen TV (2007) Development of a clinical nomogram for individualizing 5-year and 10-year risks of fracture. Bone (New York) 40(6, Suppl 2):S148–S149Google Scholar
- 41.Sanfelix-Genoves J, Peiro S, Sanfelix-Gimeno G, Giner V, Gil V, Pascual M, Fluixa C, Fuertes A, Hurtado I, Ferreros I (2010) Development and validation of a population-based prediction scale for osteoporotic fracture in the region of Valencia, Spain: the ESOSVAL-R study. BMC Public Health 10:153PubMedCentralPubMedCrossRefGoogle Scholar
- 43.Tanaka S, Yoshimura N, Kuroda T, Hosoi T, Saito M, Shiraki M (2010) The Fracture and Immobilization Score (FRISC) for risk assessment of osteoporotic fracture and immobilization in postmenopausal women—a joint analysis of the Nagano, Miyama, and Taiji Cohorts. Bone 47(6):1064–1070PubMedCrossRefGoogle Scholar
- 47.Kanis JA, Oden A, Johansson H, McCloskey E (2012) Pitfalls in the external validation of FRAX. Osteoporos Int 23:423–431Google Scholar
- 48.Steurer J, Haller C, Hauselmann H, Brunner F, Bachmann LM (2011) Clinical value of prognostic instruments to identify patients with an increased risk for osteoporotic fractures: systematic review. PLoS One 6:e19994Google Scholar
- 49.Nelson HD, Haney EM, Dana T, Bougatsos C, Chou R (2010) Screening for osteoporosis: an update for the U.S. Preventive Services Task Force. Ann Intern Med 153:99–111Google Scholar
- 52.Cooper C, Cole ZA, Holroyd CR, Earl SC, Harvey NC, Dennison EM, Melton LJ, Cummings SR, Kanis JA (2011) Secular trends in the incidence of hip and other osteoporotic fractures. Osteoporos Int 22:1277–1288Google Scholar
- 53.Leslie WD, Sadatsafavi M, Lix LM, Azimaee M, Morin S, Metge CJ, Caetano P (2011) Secular decreases in fracture rates 1986–2006 for Manitoba, Canada: a population-based analysis. Osteoporos Int 22:2137–2143Google Scholar
- 54.Adams AL, Shi J, Takayanagi M, Dell RM, Funahashi TT, Jacobsen SJ (2013) Ten-year hip fracture incidence rate trends in a large California population, 1997–2006. Osteoporos Int 24:373–376Google Scholar