Number, Location, and Time Since Prior Fracture as Predictors of Future Fracture in the Elderly From the General Population.

Prognostic tools are available to identify individuals at high risk of osteoporotic fracture and to assist physicians in management decisions. Some authors have suggested improving the predictive ability of these tools by integrating characteristics of prior fractures (number, location, and time since prior fracture). The objectives of this study were: (1) to evaluate the sex- and age-specific associations between characteristics of prior fractures and the occurrence of a future osteoporotic fracture; and (2) to assess whether the characteristics of prior fractures could increase the discriminative ability of fracture risk prediction tools. A retrospective cohort study was conducted using administrative data. Men and women aged ≥66 years were selected and grouped into two cohorts. In cohort #1 (N = 759,500), history of fractures was measured between fiscal years 1997-1998 and 2003-2004, and future fractures were identified between 2004-2005 and 2013-2014. In cohort #2 (N = 807,245), history of fractures was measured between 1997-1998 and 2008-2009, and future fractures were identified between 2009-2010 and 2013-2014. Time until a first hip/femur and major osteoporotic fracture were the outcomes of interest. Adjusted HRs and c-indices were calculated. The association between history of prior fractures and future fracture was stronger in men and younger individuals. The locations of prior fractures associated with the lowest and highest risks were foot/ankle/tibia/fibula (maximal HR = 1.64) and hip/femur (maximal HR = 9.02), respectively. The association was stronger for recent fractures (maximal HR = 4.93), but was still significant for fractures occurring 10 to 12 years prior to the beginning of follow-up (maximal HR = 1.99). Characteristics of prior fractures did not increase model discrimination. Our study confirms that the risk of future fracture increases with the number of prior fractures, varies according to prior fracture location, and decreases with time since prior fracture. However, the integration of these characteristics in current fracture risk prediction tools is not required because it does not improve predictive ability.