Comparison between Frailty Index of Deficit Accumulation and Phenotypic Model to Predict Risk of Falls: Data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) Hamilton Cohort
UMass Chan AffiliationsCenter for Outcomes Research
Balance and falls
Health Services Research
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AbstractOBJECTIVES: To compare the predictive accuracy of the frailty index (FI) of deficit accumulation and the phenotypic frailty (PF) model in predicting risks of future falls, fractures and death in women aged > /=55 years. METHODS: Based on the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort (n = 3,985), we compared the predictive accuracy of the FI and PF in risks of falls, fractures and death using three strategies: (1) investigated the relationship with adverse health outcomes by increasing per one-fifth (i.e., 20%) of the FI and PF; (2) trichotomized the FI based on the overlap in the density distribution of the FI by the three groups (robust, pre-frail and frail) which were defined by the PF; (3) categorized the women according to a predicted probability function of falls during the third year of follow-up predicted by the FI. Logistic regression models were used for falls and death, while survival analyses were conducted for fractures. RESULTS: The FI and PF agreed with each other at a good level of consensus (correlation coefficients > /= 0.56) in all the three strategies. Both the FI and PF approaches predicted adverse health outcomes significantly. The FI quantified the risks of future falls, fractures and death more precisely than the PF. Both the FI and PF discriminated risks of adverse outcomes in multivariable models with acceptable and comparable area under the curve (AUCs) for falls (AUCs > /= 0.68) and death (AUCs > /= 0.79), and c-indices for fractures (c-indices > /= 0.69) respectively. CONCLUSIONS: The FI is comparable with the PF in predicting risks of adverse health outcomes. These findings may indicate the flexibility in the choice of frailty model for the elderly in the population-based settings.
SourcePLoS One. 2015 Mar 12;10(3):e0120144. doi: 10.1371/journal.pone.0120144. eCollection 2015. Link to article on publisher's site.
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/27156
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RightsCopyright: © 2015 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Except where otherwise noted, this item's license is described as Copyright: © 2015 Li et al. This is an open access article distributed under the terms of the <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited