title: Prediction models of prevalent radiographic vertebral fractures among older women.
abstract: It is unknown how well prediction models incorporating multiple risk factors identify women with radiographic prevalent vertebral fracture (PVFx) compared with simpler models and what their value might be in clinical practice to select older women for lateral spine imaging. We compared 4 regression models for predicting PVFx in women aged 68 y and older enrolled in the Study of Osteoporotic Fractures with a femoral neck T-score ≤ -1.0, using area under receiving operator characteristic curves (AUROC) and a net reclassification index. The AUROC for a model with age, femoral neck bone mineral density, historical height loss (HHL), prior nonspine fracture, body mass index, back pain, and grip strength was only minimally better than that of a more parsimonious model with age, femoral neck bone mineral density, and historical height loss (AUROC 0.689 vs 0.679, p values for difference in 5 bootstrapped samples <0.001-0.35). The prevalence of PVFx among this older population of Caucasian women remained more than 20% even when women with low probability of PVFx, as estimated by the prediction models, were included in the screened population. These results suggest that lateral spine imaging is appropriate to consider for all Caucasian women aged 70 y and older with low bone mass to identify those with PVFx.
authors.affiliation: Park Nicollet Osteoporosis Center and Institute for Research and Education, Minneapolis, MN, USA and Division of Health Policy and Management, University of Minnesota, Minneapolis, MN, USA. Electronic address: john.schousboe@parknicollet.com.
authors.forename: John T
authors.initials: JT
authors.lastname: Schousboe
authors.affiliation: Beth Israel Deaconess Medical Center, Boston, MA, USA.
authors.forename: Harold R
authors.initials: HR
authors.lastname: Rosen
authors.affiliation: Department of Medicine, University of Chicago, Chicago, IL, USA.
authors.forename: Tamara J
authors.initials: TJ
authors.lastname: Vokes
authors.affiliation: Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
authors.forename: Jane A
authors.initials: JA
authors.lastname: Cauley
authors.affiliation: San Francisco Coordinating Center, California Pacific Medical Center, San Francisco, CA, USA.
authors.forename: Steven R
authors.initials: SR
authors.lastname: Cummings
authors.affiliation: Division of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Nevitt
authors.affiliation: Division of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, CA, USA.
authors.forename: Dennis M
authors.initials: DM
authors.lastname: Black
authors.affiliation: Bone and Mineral Unit, Oregon Health and Science University, Portland, OR, USA.
authors.forename: Eric S
authors.initials: ES
authors.lastname: Orwoll
authors.affiliation: Departments of Family and Preventive Medicine and Internal Medicine, University of California at San Diego, San Diego, CA, USA.
authors.forename: Deborah M
authors.initials: DM
authors.lastname: Kado
authors.affiliation: Division of Epidemiology, University of Minnesota, Minneapolis, MN, USA and Minneapolis Veterans Administration Medical Center, Minneapolis, MN, USA.
authors.forename: Kristine E
authors.initials: KE
authors.lastname: Ensrud
mesh_terms: D015502:Absorptiometry, Photon; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D015233:Models, Statistical; D015663:Osteoporosis, Postmenopausal / Q000150:complications* / Q000000981:diagnostic imaging*; D011237:Predictive Value of Tests; D012307:Risk Factors; D016103:Spinal Fractures / Q000000981:diagnostic imaging* / Q000209:etiology*
keywords: Bone densitometry; model discrimination; prediction models; prevalent vertebral fracture; vertebral fracture assessment