title: Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks.
abstract: We have developed clinical nomograms for predicting 5-year and 10-year fracture risks for any elderly man or woman. The nomograms used age and information concerning fracture history, fall history, and BMD T-score or body weight.
  
  
  BACKGROUND
  Although many fracture risk factors have been identified, the translation of these risk factors into a prognostic model that can be used in primary care setting has not been well realized. The present study sought to develop a nomogram that incorporates non-invasive risk factors to predict 5-year and 10-year absolute fracture risks for an individual man and woman.
  
  
  METHODS
  The Dubbo Osteoporosis Epidemiology Study was designed as a community-based prospective study, with 1358 women and 858 men aged 60+ years as at 1989. Baseline measurements included femoral neck bone mineral density (FNBMD), prior fracture, a history of falls and body weight. Between 1989 and 2004, 426 women and 149 men had sustained a low-trauma fracture (not including morphometric vertebral fractures). Two prognostic models based on the Cox's proportional hazards analysis were considered: model I included age, BMD, prior fracture and falls; and model II included age, weight, prior fracture and fall.
  
  
  RESULTS
  Analysis of the area under the receiver operating characteristic curve (AUC) suggested that model I (AUC = 0.75 for both sexes) performed better than model II (AUC = 0.72 for women and 0.74 for men). Using the models' estimates, we constructed various nomograms for individualizing the risk of fracture for men and women. If the 5-year risk of 10% or greater is considered "high risk", then virtually all 80-year-old men with BMD T-scores < -1.0 or 80-year-old women with T-scores < -2.0 were predicted to be in the high risk group. A 60-year-old woman's risk was considered high risk only if her BMD T-scores < or = -2.5 and with a prior fracture; however, no 60-year-old men would be in the high risk regardless of their BMD and risk profile.
  
  
  CONCLUSIONS
  These data suggest that the assessment of fracture risk for an individual cannot be based on BMD alone, since there are clearly various combinations of factors that could substantially elevate an individual's risk of fracture. The nomograms presented here can be useful for individualizing the short- and intermediate-term risk of fracture and identifying high-risk individuals for intervention to reduce the burden of fracture in the general population.
authors.affiliation: Bone and Mineral Research Program, Garvan Institute of Medical Research, St Vincent's Hospital, 384 Victoria Street, Darlinghurst, Sydney, NSW, 2010, Australia. n.nguyen@garvan.org.au
authors.forename: N D
authors.initials: ND
authors.lastname: Nguyen
authors.forename: S A
authors.initials: SA
authors.lastname: Frost
authors.forename: J R
authors.initials: JR
authors.lastname: Center
authors.forename: J A
authors.initials: JA
authors.lastname: Eisman
authors.forename: T V
authors.initials: TV
authors.lastname: Nguyen
mesh_terms: D000058:Accidental Falls; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D015519:Bone Density; D004812:Epidemiologic Methods; D005260:Female; D050723:Fractures, Bone / Q000453:epidemiology / Q000209:etiology* / Q000503:physiopathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D009517:New South Wales / Q000453:epidemiology; D049451:Nomograms; D010024:Osteoporosis / Q000150:complications / Q000453:epidemiology; D011379:Prognosis; D012737:Sex Factors