Fracture risk prediction: importance of age, BMD and spine fracture status
- PMID: 24228164
- PMCID: PMC3789218
- DOI: 10.1038/bonekey.2013.138
Fracture risk prediction: importance of age, BMD and spine fracture status
Abstract
Our purpose was to identify factors for a parsimonious fracture risk assessment model considering morphometric spine fracture status, femoral neck bone mineral density (BMD) and the World Health Organization (WHO) clinical risk factors. Using data from 2761 subjects from the Canadian Multicentre Osteoporosis Study (CaMos), a prospective, longitudinal cohort study of randomly selected community-dwelling men and women aged ⩾50 years, we previously reported that a logistic regression model considering age, BMD and spine fracture status provided as much predictive information as a model considering these factors plus the remaining WHO clinical risk factors. The current analysis assesses morphometric vertebral fracture and/or nonvertebral fragility fracture at 5 years using data from an additional 1964 CaMos subjects who have now completed 5 years of follow-up (total N=4725). Vertebral fractures were identified from lateral spine radiographs assessed using quantititative morphometry at baseline and end point. Nonvertebral fragility fractures were determined by questionnaire and confirmed using radiographs or medical records; fragility fracture was defined as occurring with minimal or no trauma. In this analysis, a model including age, BMD and spine fracture status provided a gradient of risk per s.d. (GR/s.d.) of 1.88 and captured most of the predictive information of a model including morphometric spine fracture status, BMD and all WHO clinical risk factors (GR/s.d. 1.92). For comparison, this model provided more information than a model considering BMD and the WHO clinical risk factors (GR/s.d. 1.74). These findings confirm the value of age, BMD and spine fracture status for predicting fracture risk.
Conflict of interest statement
John H. Krege is a full-time employee of Eli Lilly and Company, and Xiaohai Wan was a full-time employee of Eli Lilly and Company at the time the study was conducted. Jonathan D. Adachi has served as consultant/speaker for Amgen, Astra Zeneca, Eli Lilly, GlaxoSmithKline, Merck, Novartis, Pfizer, Procter & Gamble, Roche, Sanofi-Aventis and Servier. Jacques P. Brown has received a research grant from or has served as a consultant/speaker for Abbott, Amgen, Eli Lilly, Genizon, GlaxoSmithKline, Merck, Novartis, Pfizer, Procter & Gamble, Roche, Sanofi-Aventis, Servier, Wyeth and Zelos. Wojciech P. Olszynski has served as a consultant for Abbott Laboratories, Merck Frosst, Amgen, Novartis, Aventis, Pfizer, Boehringer Ingelheim, Procter & Gamble, Eli Lilly, Sanofi-Synthelabo, Genzyme, Schering Canada, GlaxoSmithKline, Solvay Pharma, Hoffmann-LaRoche, Wyeth and Janssen-Ortho Inc./Ortho-Biotech. Robert G. Josse has served on advisory boards and received honoraria and research grants from Eli Lilly, Proctor & Gamble, Sanofi-Aventis, Merck, Novartis, Servier, GlaxoSmithKline and Amgen. David Goltzman has received honoraria from and served on the advisory boards of Eli Lilly, Proctor & Gamble, Merck Frosst and Novartis. The remaining authors declare no conflict of interest.
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