No studies have compared how well different prediction models discriminate older men who have a radiographic prevalent vertebral fracture (PVFx) from those who do not. We used area under receiver operating characteristic curves and a net reclassification index to compare how well regression-derived prediction models and nonregression prediction tools identify PVFx among men age ≥65yr with femoral neck T-score of -1.0 or less enrolled in the Osteoporotic Fractures in Men Study. The area under receiver operating characteristic for a model with age, bone mineral density, and historical height loss (HHL) was 0.682 compared with 0.692 for a complex model with age, bone mineral density, HHL, prior non-spine fracture, body mass index, back pain, grip strength, smoking, and glucocorticoid use (. p values for difference in 5 bootstrapped samples 0.14-0.92). This complex model, using a cutpoint prevalence of 5%, correctly reclassified only a net 5.7% (. p = 0.13) of men as having or not having a PVFx compared with a simple criteria list (age ≥ 80yr, HHL >4cm, or glucocorticoid use). In conclusion, simple criteria identify older men with PVFx and regression-based models. Future research to identify additional risk factors that more accurately identify older men with PVFx is needed.
Bibliographical noteFunding Information:
The MrOS Study is supported by National Institutes of Health funding. The following institutes provide support: The National Institute of Arthritis and Musculoskeletal and Skin Diseases , the National Institute on Aging , the National Center for Research Resources , and NIH Roadmap for Medical Research under the following grant numbers: U01 AR45580 , U01 AR45614 , U01 AR45632 , U01 AR45647 , U01 AR45654 , U01 AR45583 , U01 AG18197 , U01-AG027810 , and UL1 TR000128 .
© 2014 The International Society for Clinical Densitometry.
- Bone densitometry
- Model discrimination
- Prediction models
- Prevalent vertebral fracture
- Vertebral fracture assessment