title: Evaluation of the simple calculated osteoporosis risk estimation (SCORE) in a sample of white women from Belgium.
abstract: Identifying patients at risk of developing an osteoporosis-related fracture will continue to be a challenge. The "gold standard" for osteoporosis diagnosis is bone densitometry. However, economic issues or availability of the technology may prevent its use under a mass screening scenario. A risk assessment instrument, the "simple calculated osteoporosis risk estimation" (SCORE), has been reported to appropriately identify women likely to have low (t score < or = -2 SD) bone mineral density (BMD) and who should be referred for bone densitometry. The aim of our study is to evaluate the discriminatory performance of SCORE in a random sample of postmenopausal white women from Belgium. For this purpose, we gathered medical data on 4035 consecutive patients aged > or = 45 years, either consulting spontaneously or referred for a BMD measurement to an outpatient osteoporosis center located at the University of Liège, Belgium. BMD measurements, using dual-energy X-ray absorptiometry (DXA) technology, were taken at the hip (total and neck) and lumbar spine (L2-4). At the recommended cutoff point of 6, SCORE had a sensitivity of 91.5% to detect low BMD at any of the measured sites, a specificity of 26.5%, a positive predictive value of 52.8%, and a negative predictive value of 77.7%. According to SCORE, 18% of the patients would not be recommended for densitometry. Among these, 10.9% were misclassified as they had osteoporosis (t score < or = -2.5 SD) at one or more of the sites investigated. The negative predictive errors of SCORE, when failing to detect osteoporosis, were only 1% for the total hip, 3.2% for the femoral neck, and 8.8% for the lumbar spine. We conclude that, notwithstanding the high values of sensitivity, SCORE specificity is too low to be useful as a diagnostic tool for screening patients at high risk to later develop osteoporosis. Nevertheless, from a resource allocation perspective, this instrument can be used with relative confidence to exclude patients who do not need a BMD measurement, and would therefore provide an opportunity to realize substantial cost savings in comparison to a mass screening strategy.
authors.affiliation: Department of Epidemiology and Public Health, University of Liège, Liège, Belgium.
authors.forename: W
authors.initials: W
authors.lastname: Ben Sedrine
authors.forename: J P
authors.initials: JP
authors.lastname: Devogelaer
authors.forename: J M
authors.initials: JM
authors.lastname: Kaufman
authors.forename: S
authors.initials: S
authors.lastname: Goemaere
authors.forename: G
authors.initials: G
authors.lastname: Depresseux
authors.forename: B
authors.initials: B
authors.lastname: Zegels
authors.forename: R
authors.initials: R
authors.lastname: Deroisy
authors.forename: J Y
authors.initials: JY
authors.lastname: Reginster
mesh_terms: D015502:Absorptiometry, Photon; D000368:Aged; D001530:Belgium / Q000453:epidemiology; D015519:Bone Density; D015331:Cohort Studies; D017046:Cost Savings; D005260:Female; D006801:Humans; D008403:Mass Screening / Q000191:economics / Q000379:methods / Q000706:statistics & numerical data*; D008875:Middle Aged; D015663:Osteoporosis, Postmenopausal / Q000175:diagnosis* / Q000208:ethnology*; D011237:Predictive Value of Tests; D012307:Risk Factors; D012680:Sensitivity and Specificity; D044465:White People