Xuezhi Jiang1, Lauren B Westermann, Gabriella V Galleo, John Demko, Kimberly A Marakovits, Peter F Schnatz. 1. Departments of Obstetrics-Gynecology and Internal Medicine, the Reading Hospital, Reading, Pennsylvania; Philadelphia College of Osteopathic Medicine, Philadelphia, Pennsylvania; the Departments of Obstetrics-Gynecology and Internal Medicine, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania.
Abstract
OBJECTIVE: To compare several fracture risk-prediction models and their predictive values. METHODS: Women older than age 49 years were sent for dual-energy X-ray absorptiometry screening between January 2007 and March 2009. Data collection included multiple osteoporosis risk factors. The ability to identify fractures was analyzed and compared using the North American Menopause Society 2006 and 2010 Position Statements, The Fracture Risk Assessment Tool, along with age alone. The area under the curve (AUC) comparison with chance (AUC 0.50) and paired AUC comparisons between models were used to investigate the efficacy of each model in predicting osteoporotic fractures. RESULTS: Among the 615 women studied, with mean (standard deviation) age of 61.4 (8.3) years and 94.5% being white, 15 have experienced a fracture. All screening approaches were significantly better than chance at predicting fractures. Paired comparisons of the detection ability of fracture prediction models showed no significant differences. Age alone was a significant predictor for fracture (AUC 0.79, 95% confidence interval [CI] 0.67-0.91, P<.001) with the optimal cutoff age of 65 years, which was associated with a sensitivity (95% CI) of 80% (77-83%) and specificity (95% CI) of 73% (70-77%). Compared with young postmenopausal women (younger than 65 years), the odds ratio (95% CI) of fractures in older women (65 years or older) is 10.2 (2.32-44.97). In addition, when age was added, it significantly increased the AUC of each model. CONCLUSION: These data suggest that all current screening modalities are effective in predicting fracture but not significantly better than age alone. Age should be considered carefully while evaluating patients for osteoporosis screening and treatment. LEVEL OF EVIDENCE: II.
OBJECTIVE: To compare several fracture risk-prediction models and their predictive values. METHODS:Women older than age 49 years were sent for dual-energy X-ray absorptiometry screening between January 2007 and March 2009. Data collection included multiple osteoporosis risk factors. The ability to identify fractures was analyzed and compared using the North American Menopause Society 2006 and 2010 Position Statements, The Fracture Risk Assessment Tool, along with age alone. The area under the curve (AUC) comparison with chance (AUC 0.50) and paired AUC comparisons between models were used to investigate the efficacy of each model in predicting osteoporotic fractures. RESULTS: Among the 615 women studied, with mean (standard deviation) age of 61.4 (8.3) years and 94.5% being white, 15 have experienced a fracture. All screening approaches were significantly better than chance at predicting fractures. Paired comparisons of the detection ability of fracture prediction models showed no significant differences. Age alone was a significant predictor for fracture (AUC 0.79, 95% confidence interval [CI] 0.67-0.91, P<.001) with the optimal cutoff age of 65 years, which was associated with a sensitivity (95% CI) of 80% (77-83%) and specificity (95% CI) of 73% (70-77%). Compared with young postmenopausal women (younger than 65 years), the odds ratio (95% CI) of fractures in older women (65 years or older) is 10.2 (2.32-44.97). In addition, when age was added, it significantly increased the AUC of each model. CONCLUSION: These data suggest that all current screening modalities are effective in predicting fracture but not significantly better than age alone. Age should be considered carefully while evaluating patients for osteoporosis screening and treatment. LEVEL OF EVIDENCE: II.
Authors: Kyla L Naylor; Amit X Garg; Guangyong Zou; Lisa Langsetmo; William D Leslie; Lisa-Ann Fraser; Jonathan D Adachi; Suzanne Morin; David Goltzman; Brian Lentle; Stuart A Jackson; Robert G Josse; Sophie A Jamal Journal: Clin J Am Soc Nephrol Date: 2015-02-05 Impact factor: 8.237