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PMID: 25376757 Published · ppublish English Journal Article Research Support, N.I.H., Extramural

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

Statistics in medicine ·Vol. 34 ·No. 4 ·2015-02-20 ·Pages 652-63

He X, Whitmore GA, Loo GY, Hochberg MC, Lee ML

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.

Keywords
disease progression elderly first hitting time health process threshold regression time-to-event data
MeSH Terms
Aged Biostatistics/methods Disease Progression Female Hip Fractures/epidemiology,etiology Humans Models, Statistical Osteoporosis/complications Proportional Hazards Models Regression Analysis Risk Factors Stochastic Processes Survival Analysis Time Factors
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
He Xin
Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, U.S.A.
Whitmore G A
Loo Geok Yan
Hochberg Marc C
Lee Mei-Ling Ting
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Article Info
Journal
Statistics in medicine
Abbr.
Stat Med
ISSN
1097-0258
Published
2015-02-20
Epub
2014-00-06
Pages
652-63
Language
English
Region
England
NLM ID
8215016
PMCID
PMC4314426
Subset
IM
Grants
NIAMS NIH HHS · R01 AR035583 · United States
NIAMS NIH HHS · R01 AR035584 · United States
NIA NIH HHS · R01 AG027576 · United States
NICHD NIH HHS · R24 HD041041 · United States
NIA NIH HHS · R01 AG005407 · United States
NIAMS NIH HHS · R01 AR035582 · United States
NIA NIH HHS · R01 AG005394 · United States
NIA NIH HHS · R01 AG027574 · United States
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