The Osteoporosis Self-Assessment Tool versus alternative tests for selecting postmenopausal women for bone mineral density assessment: a comparative systematic review of accuracy

  • B. Rud
  • J. Hilden
  • L. Hyldstrup
  • A. Hróbjartsson
Original Article



We performed a systematic review of studies comparing the Osteoporosis Self-Assessment Tool (OST) and other tests used to select women for bone mineral density (BMD) assessment. In comparative meta-analyses, we found that the accuracy of OST was similar to other tests that are based on information from the medical history. By contrast, assessment by quantitative ultrasonography at the heel was more accurate than OST in discriminating between women with high and low BMD. The methodological quality of the included studies was generally low.


Numerous tests are suggested for triaging postmenopausal women for bone mineral density (BMD) assessment by dual-energy X-ray absorptiometry. Previous studies suggest that OST, based on age and weight only, may be as accurate as more complex triage tests. We systematically compare the accuracy of OST and alternative triage tests in postmenopausal women.


We searched PubMed, Embase, Web of Science, citation lists, and conference proceedings. Our main measure of accuracy was the diagnostic odds ratio (DOR). We compared summary estimates of DOR (sDOR) for OST and alternative tests in pairwise meta-analyses by using the Moses–Littenberg approach.


Summary estimates of DOR for OST and the clinical decision rules Simple Calculated Osteoporosis Risk Estimation (SCORE) and Osteoporosis Risk Assessment Instrument (ORAI) did not differ significantly in white women (relative sDOR: 0.57–1.17, all p ≥ 0.11). By contrast, sDOR was higher for Stiffness Index assessed by calcaneal quantitative ultrasonography than for OST (relative sDOR: 1.9, p = 0.005). Studies were few in Asian and black women. Methodological quality, assessed with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) checklist, was generally low.


In white women, the accuracy of OST and alternative clinical decision rules was similar, whereas Stiffness Index was more accurate than OST. Low study quality renders transferability to clinical settings uncertain.


Accuracy Bone mineral density Meta-analysis Osteoporosis Self-Assessment Tool Systematic review Triage test 



We wish to thank the authors of studies included in the review who replied to our request for additional information.

Conflicts of interest


Supplementary material

198_2008_713_MOESM1_ESM.doc (402 kb)
ESM 1 (DOC 402 kb)


  1. 1.
    Cummings SR, Bates D, Black DM (2002) Clinical use of bone densitometry: scientific review. JAMA 288:1889–1897PubMedCrossRefGoogle Scholar
  2. 2.
    Black DM, Thompson DE, Bauer DC et al (2000) Fracture risk reduction with alendronate in women with osteoporosis: the Fracture Intervention Trial. FIT Research Group. J Clin Endocrinol Metab 85:4118–4124PubMedCrossRefGoogle Scholar
  3. 3.
    Chesnut CH III, Skag A, Christiansen C et al (2004) Effects of oral ibandronate administered daily or intermittently on fracture risk in postmenopausal osteoporosis. J Bone Miner Res 19:1241–1249CrossRefGoogle Scholar
  4. 4.
    Ettinger B, Black DM, Mitlak BH et al (1999) Reduction of vertebral fracture risk in postmenopausal women with osteoporosis treated with raloxifene: results from a 3-year randomized clinical trial. JAMA 282:637–645PubMedCrossRefGoogle Scholar
  5. 5.
    Harris ST, Watts NB, Genant HK et al (1999) Effects of risedronate treatment on vertebral and nonvertebral fractures in women with postmenopausal osteoporosis: a randomized controlled trial. Vertebral Efficacy With Risedronate Therapy (VERT) Study Group. JAMA 282:1344–1352PubMedCrossRefGoogle Scholar
  6. 6.
    McClung MR, Geusens P, Miller PD et al (2001) Effect of risedronate on the risk of hip fracture in elderly women. Hip Intervention Program Study Group. N Engl J Med 344:333–340PubMedCrossRefGoogle Scholar
  7. 7.
    Reginster JY, Seeman E, De Vernejoul MC et al (2005) Strontium ranelate reduces the risk of nonvertebral fractures in postmenopausal women with osteoporosis: Treatment of Peripheral Osteoporosis (TROPOS) study. J Clin Endocrinol Metab 90:2816–2822PubMedCrossRefGoogle Scholar
  8. 8.
    Nelson HD, Helfand M, Woolf SH et al (2002) Screening for postmenopausal osteoporosis: a review of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med 137:529–541PubMedGoogle Scholar
  9. 9.
    Schwartz EN, Steinberg DM (2006) Prescreening tools to determine who needs DXA. Curr Osteoporos Rep 4:148–152PubMedCrossRefGoogle Scholar
  10. 10.
    Cummings SR, Melton LJ (2002) Epidemiology and outcomes of osteoporotic fractures. Lancet 359:1761–1767PubMedCrossRefGoogle Scholar
  11. 11.
    Bossuyt PM, Irwig L, Craig J et al (2006) Comparative accuracy: assessing new tests against existing diagnostic pathways. BMJ 332:1089–1092PubMedCrossRefGoogle Scholar
  12. 12.
    Díez-Perez A, Marin F, Vila J et al (2003) Evaluation of calcaneal quantitative ultrasound in a primary care setting as a screening tool for osteoporosis in postmenopausal women. J Clin Densitom 6:237–245PubMedCrossRefGoogle Scholar
  13. 13.
    Gudmundsdottir SL, Indridason OS, Franzson L et al (2005) Age-related decline in bone mass measured by dual-energy X-ray absorptiometry and quantitative ultrasound in a population-based sample of both sexes:identification of useful ultrasound thresholds for osteoporosis screening. J Clin Densitom 8:80–86PubMedCrossRefGoogle Scholar
  14. 14.
    Hodson J, Marsh J (2003) Quantitative ultrasound and risk factor enquiry as predictors of postmenopausal osteoporosis: comparative study in primary care. BMJ 326:1250–1251PubMedCrossRefGoogle Scholar
  15. 15.
    Pacheco EM, Harrison EJ, Ward KA et al (2002) Detection of osteoporosis by dual energy X-ray absorptiometry (DXA) of the calcaneus: is the WHO criterion applicable? Calcif Tissue Int 70:475–482PubMedCrossRefGoogle Scholar
  16. 16.
    Pouilles JM, Tremollieres FA, Martinez S et al (2001) Ability of peripheral DXA measurements of the forearm to predict low axial bone mineral density at menopause. Osteoporos Int 12:71–76PubMedCrossRefGoogle Scholar
  17. 17.
    Boonen S, Nijs J, Borghs H et al (2005) Identifying postmenopausal women with osteoporosis by calcaneal ultrasound, metacarpal digital X-ray radiogrammetry and phalangeal radiographic absorptiometry: a comparative study. Osteoporos Int 16:93–100PubMedCrossRefGoogle Scholar
  18. 18.
    Nakamoto T, Taguchi A, Ohtsuka M et al (2003) Dental panoramic radiograph as a tool to detect postmenopausal women with low bone mineral density: untrained general dental practitioners’ diagnostic performance. Osteoporos Int 14:659–664PubMedCrossRefGoogle Scholar
  19. 19.
    Cadarette SM, Jaglal SB, Kreiger N et al (2000) Development and validation of the Osteoporosis Risk Assessment Instrument to facilitate selection of women for bone densitometry. CMAJ 162:1289–1294PubMedGoogle Scholar
  20. 20.
    Koh LK, Sedrine WB, Torralba TP et al (2001) A simple tool to identify Asian women at increased risk of osteoporosis. Osteoporos Int 12:699–705PubMedCrossRefGoogle Scholar
  21. 21.
    Lydick E, Cook K, Turpin J et al (1998) Development and validation of a simple questionnaire to facilitate identification of women likely to have low bone density. Am J Manag Care 4:37–48PubMedGoogle Scholar
  22. 22.
    Rud B, Hilden J, Hyldstrup L et al (2007) Performance of the Osteoporosis Self-Assessment Tool in ruling out low bone mineral density in postmenopausal women: a systematic review. Osteoporos Int 18:1177–1187PubMedCrossRefGoogle Scholar
  23. 23.
    Whiting P, Rutjes AW, Reitsma JB et al (2003) The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol 3:25PubMedCrossRefGoogle Scholar
  24. 24.
    Miller PD, Njeh CF, Jankowski LG et al (2002) What are the standards by which bone mass measurement at peripheral skeletal sites should be used in the diagnosis of osteoporosis? J Clin Densitom 5([Suppl]):S39–S45PubMedCrossRefGoogle Scholar
  25. 25.
    Glas AS, Lijmer JG, Prins MH et al (2003) The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol 56:1129–1135PubMedCrossRefGoogle Scholar
  26. 26.
    Walter SD (1985) Small sample estimation of log odds ratios from logistic regression and fourfold tables. Stat Med 4:437–444PubMedCrossRefGoogle Scholar
  27. 27.
    Armitage P, Berry G (1987) Statistical inference. In Statistical methods in medical research, 2nd edn. Blackwell, Oxford, pp 93–140Google Scholar
  28. 28.
    Moses LE, Shapiro D, Littenberg B (1993) Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations. Stat Med 12:1293–1316PubMedGoogle Scholar
  29. 29.
    Littenberg B, Moses LE (1993) Estimating diagnostic accuracy from multiple conflicting reports: a new meta-analytic method. Med Decis Making 13:313–321PubMedCrossRefGoogle Scholar
  30. 30.
    Thompson SG, Sharp SJ (1999) Explaining heterogeneity in meta-analysis: a comparison of methods. Stat Med 18:2693–2708PubMedCrossRefGoogle Scholar
  31. 31.
    Higgins JP, Thompson SG (2004) Controlling the risk of spurious findings from meta-regression. Stat Med 23:1663–1682PubMedCrossRefGoogle Scholar
  32. 32.
    Higgins JP, Thompson SG, Deeks JJ et al (2003) Measuring inconsistency in meta-analyses. BMJ 327:557–560PubMedCrossRefGoogle Scholar
  33. 33.
    Nguyen TV, Center JR, Pocock NA et al (2004) Limited utility of clinical indices for the prediction of symptomatic fracture risk in postmenopausal women. Osteoporos Int 15:49–55PubMedCrossRefGoogle Scholar
  34. 34.
    Richy F, Deceulaer F, Ethgen O et al (2004) Development and validation of the ORACLE score to predict risk of osteoporosis. Mayo Clin Proc 79:1402–1408PubMedCrossRefGoogle Scholar
  35. 35.
    Cho J-J (2005) Evaluation of two screening decision rules for osteoporosis of menopause or perimenopause women in Korea. Osteoporos Int 13(suppl 3):S68Google Scholar
  36. 36.
    Pongchaiyakul C, Nguyen ND, Pongchaiyakul C et al (2004) Development and validation of a new clinical risk index for prediction of osteoporosis in Thai women. J Med Assoc Thai 87:910–916PubMedGoogle Scholar
  37. 37.
    Wallace LS, Ballard JE, Holiday D et al (2004) Evaluation of decision rules for identifying low bone density in postmenopausal African-American women. J Natl Med Assoc 96:290–296PubMedGoogle Scholar
  38. 38.
    Gambacciani M, Genazzani AR (2004) Osteoporosis screening: comparison of the heel ultrasound measurement to calculated risk assessment tools. Osteoporos Int 15(suppl 1):S36Google Scholar
  39. 39.
    Mossman EA, Grinnell NC, Cole L et al (2002) Quantitative ultrasound of the heel does not predict bone density at the femoral neck more accurately than simple clinical indices in postmenopausal Caucasian women. J Bone Miner Res 17:S422Google Scholar
  40. 40.
    Poriau S, Geusens P, Van den Bosch F et al (2004) Osteoporosis screening: comparison of heel ultrasound measurement to calculated risk assessment tools (OST). J Bone Miner Res 20(suppl 2):S378Google Scholar
  41. 41.
    Rud B, Abrahamsen B, Rejnmark L et al (2005) How does estrogen use in early postmenopausal women affect the diagnostic performance of the Osteoporosis Self-assessment Tool and quantitative ultrasonography? Bone 36:S345Google Scholar
  42. 42.
    Cook RB, Collins D, Tucker J et al (2005) Comparison of questionnaire and quantitative ultrasound techniques as screening tools for DXA. Osteoporos Int 16:1565–1575PubMedCrossRefGoogle Scholar
  43. 43.
    Cadarette SM, McIsaac WJ, Hawker GA et al (2004) The validity of decision rules for selecting women with primary osteoporosis for bone mineral density testing. Osteoporos Int 15:361–366PubMedCrossRefGoogle Scholar
  44. 44.
    Mossman EA, DeFrancisco T, Strot S et al (2004) OST versus weight alone in groups defined by clinical guidelines. J Clin Densitom 7:234Google Scholar
  45. 45.
    Rud B, Jensen JE, Mosekilde L et al (2005) Performance of four clinical screening tools to select peri- and early postmenopausal women for dual X-ray absorptiometry. Osteoporos Int 16:764–772PubMedCrossRefGoogle Scholar
  46. 46.
    Choi H, Park YJ, Lee CM et al (2004) The validation and comparisional study of several risk indices for prediction of osteoporosis in peri- and postmenopausal Korean women. Osteoporos Int 15(suppl 1):S27Google Scholar
  47. 47.
    Fujiwara S, Masunari N, Suzuki G et al (2001) Performance of osteoporosis risk indices in a Japanese population. Curr Ther Res 62:586–594CrossRefGoogle Scholar
  48. 48.
    Kung AW, Ho AY, Sedrine WB et al (2003) Comparison of a simple clinical risk index and quantitative bone ultrasound for identifying women at increased risk of osteoporosis. Osteoporos Int 14:716–721PubMedCrossRefGoogle Scholar
  49. 49.
    Taguchi A, Suei Y, Sanada M et al (2004) Validation of dental panoramic radiography measures for identifying postmenopausal women with spinal osteoporosis. Am J Roentgenol 183:1755–1760Google Scholar
  50. 50.
    Dargent-Molina P, Poitiers F, Breart G (2000) In elderly women weight is the best predictor of a very low bone mineral density: evidence from the EPIDOS study. Osteoporos Int 11:881–888PubMedCrossRefGoogle Scholar
  51. 51.
    Edelstein SL, Barrett-Connor E (1993) Relation between body size and bone mineral density in elderly men and women. Am J Epidemiol 138:160–169PubMedGoogle Scholar
  52. 52.
    Wildner M, Peters A, Raghuvanshi VS et al (2003) Superiority of age and weight as variables in predicting osteoporosis in postmenopausal white women. Osteoporos Int 14:950–956PubMedCrossRefGoogle Scholar
  53. 53.
    Pepe MS (2003) Combining binary tests and regression analysis. In The statistical evaluation of medical tests for classification and prediction, 1st edn. Oxford University Press, Oxford, pp 35–65Google Scholar
  54. 54.
    Rutjes AW, Reitsma JB, Di Nisio M et al (2006) Evidence of bias and variation in diagnostic accuracy studies. CMAJ 174:469–476PubMedGoogle Scholar
  55. 55.
    Whiting P, Rutjes AW, Reitsma JB et al (2004) Sources of variation and bias in studies of diagnostic accuracy: a systematic review. Ann Intern Med 140:189–202PubMedGoogle Scholar
  56. 56.
    Gunaydin R, Kaya T, Goksel Karatepe A et al (2006) Performance of several risk indices for prediction of osteoporosis in peri- and postmenopausal women. Osteoporos Int 17([suppl 2]):S168Google Scholar
  57. 57.
    El maghraoui A, Habbassi A, Ghazi M et al (2006) Validation and comparative evaluation of four osteoporosis risk indices in Moroccan menopausal women. Arch Osteoporos 1:1–6. doi: 10.1007/s11657-006-0001-6 CrossRefGoogle Scholar
  58. 58.
    Harrison EJ, Adams JE (2006) Application of a triage approach to peripheral bone densitometry reduces the requirement for central DXA but is not cost effective. Calcif Tissue Int 79:199–206PubMedCrossRefGoogle Scholar
  59. 59.
    Martinez-Aguila D, Gomez-Vaquero C, Rozadilla A et al (2007) Decision rules for selecting women for bone mineral density testing: application in postmenopausal women referred to a bone densitometry unit. J Rheumatol 34:1307–1312PubMedGoogle Scholar
  60. 60.
    Richy F, Gourlay M, Ross PD et al (2004) Validation and comparative evaluation of the osteoporosis self-assessment tool (OST) in a Caucasian population from Belgium. QJM 97:39–46PubMedCrossRefGoogle Scholar
  61. 61.
    Geusens P, Hochberg MC, van der Voort DJ et al (2002) Performance of risk indices for identifying low bone density in postmenopausal women. Mayo Clin Proc 77:629–637PubMedCrossRefGoogle Scholar
  62. 62.
    Marin F, Lopez-Bastida J, Diez-Perez A et al (2004) Bone mineral density referral for dual-energy X-ray absorptiometry using quantitative ultrasound as a prescreening tool in postmenopausal women from the general population: a cost-effectiveness analysis. Calcif Tissue Int 74:277–283PubMedCrossRefGoogle Scholar
  63. 63.
    Sim MF, Stone M, Johansen A et al (2000) Cost effectiveness analysis of BMD referral for DXA using ultrasound as a selective pre-screen in a group of women with low trauma Colles’ fractures. Technol Health Care 8:277–284PubMedGoogle Scholar
  64. 64.
    Richy F, Ethgen O, Bruyere O et al (2004) Primary prevention of osteoporosis: mass screening scenario or prescreening with questionnaires? An economic perspective. J Bone Miner Res 19:1955–1960PubMedCrossRefGoogle Scholar
  65. 65.
    Kanis JA, Johnell O, Oden A et al (2008) FRAX and the assessment of fracture probability in men and women in the UK. Osteoporos Int 19:385–397PubMedCrossRefGoogle Scholar
  66. 66.
    Lyles KW, Colón-Emeric CS, Magaziner JS et al (2007) Zolendronic acid and clinical fractures and mortality after hip fracture. N Engl J Med 357:1799–809PubMedCrossRefGoogle Scholar
  67. 67.
    De Laet C, Kanis JA, Oden A et al (2005) Body mass index as a predictor of fracture risk: a meta-analysis. Osteoporos Int 16:1330–1338PubMedCrossRefGoogle Scholar
  68. 68.
    Bossuyt PM, Reitsma JB, Bruns DE et al (2003) The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Clin Chem 49:7–18PubMedCrossRefGoogle Scholar
  69. 69.
    Klemetti E, Kolmakov S, Kroger H (1994) Pantomography in assessment of the osteoporosis risk group. Scand J Dent Res 102:68–72PubMedGoogle Scholar

Copyright information

© International Osteoporosis Foundation and National Osteoporosis Foundation 2008

Authors and Affiliations

  • B. Rud
    • 1
  • J. Hilden
    • 2
  • L. Hyldstrup
    • 1
  • A. Hróbjartsson
    • 3
  1. 1.Osteoporosis Unit 545, Department of EndocrinologyHvidovre University HospitalHvidovreDenmark
  2. 2.Department of Biostatistics, Institute of Public Health, Faculty of Health SciencesUniversity of CopenhagenCopenhagenDenmark
  3. 3.The Nordic Cochrane CentreCopenhagenDenmark

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