Literature DB >> 25376757

A model for time to fracture with a shock stream superimposed on progressive degradation: the Study of Osteoporotic Fractures.

Xin He1, G A Whitmore, Geok Yan Loo, Marc C Hochberg, Mei-Ling Ting Lee.   

Abstract

Osteoporotic hip fractures in the elderly are associated with a high mortality in the first year following fracture and a high incidence of disability among survivors. We study first and second fractures of elderly women using data from the Study of Osteoporotic Fractures. We present a new conceptual framework, stochastic model, and statistical methodology for time to fracture. Our approach gives additional insights into the patterns for first and second fractures and the concomitant risk factors. Our modeling perspective involves a novel time-to-event methodology called threshold regression, which is based on the plausible idea that many events occur when an underlying process describing the health or condition of a person or system encounters a critical boundary or threshold for the first time. In the parlance of stochastic processes, this time to event is a first hitting time of the threshold. The underlying process in our model is a composite of a chronic degradation process for skeletal health combined with a random stream of shocks from external traumas, which taken together trigger fracture events.
Copyright © 2014 John Wiley & Sons, Ltd.

Entities:  

Keywords:  disease progression; elderly; first hitting time; health process; threshold regression; time-to-event data

Mesh:

Year:  2014        PMID: 25376757      PMCID: PMC4314426          DOI: 10.1002/sim.6356

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  29 in total

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Authors:  John A Kanis; Helena Johansson; Anders Oden; Olof Johnell; Chris de Laet; L Joseph Melton III; Alan Tenenhouse; Jonathan Reeve; Alan J Silman; Huibert A P Pols; John A Eisman; Eugene V McCloskey; Dan Mellstrom
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Authors:  J A Kanis; H Johansson; A Oden; O Johnell; C De Laet; J A Eisman; E V McCloskey; D Mellstrom; L J Melton; H A P Pols; J Reeve; A J Silman; A Tenenhouse
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  1 in total

1.  Using simulation studies to evaluate statistical methods.

Authors:  Tim P Morris; Ian R White; Michael J Crowther
Journal:  Stat Med       Date:  2019-01-16       Impact factor: 2.497

  1 in total

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