A poisson process model for hip fracture risk.
The primary method for assessing fracture risk in osteoporosis relies primarily on measurement of bone mass. Estimation of fracture risk is most often evaluated using logistic or proportional hazards models. Notwithstanding the success of these models, there is still much uncertainty as to who will...
| Published in: | Medical & Biological Engineering & Computing Vol. 48; no. 8; pp. 799 - 811 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Published: |
Springer Nature
Aug2010
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104912429&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104912429 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Aug2010 vid: 48 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104912429 NLM20524073 2010713744 10.1007/s11517-010-0638-6 NLM20524073 104912429 ppf: 799 ppct: 12 formats: fmt: @attributes: type: P tig: atl: A poisson process model for hip fracture risk. aug: au: Schechner Z Luo G Kaufman JJ Siffert RS Schechner, Zvi Luo, Gangming Kaufman, Jonathan J Siffert, Robert S affil: CyberLogic, Inc., 611 Broadway, Suite 707, New York, NY 10012, USA sug: subj: Hip Fractures Etiology Models, Statistical Osteoporosis Complications Accidental Falls Bone Density Physiology Hip Fractures Physiopathology Risk Assessment Methods Statistics ab: The primary method for assessing fracture risk in osteoporosis relies primarily on measurement of bone mass. Estimation of fracture risk is most often evaluated using logistic or proportional hazards models. Notwithstanding the success of these models, there is still much uncertainty as to who will or will not suffer a fracture. This has led to a search for other components besides mass that affect bone strength. The purpose of this paper is to introduce a new mechanistic stochastic model that characterizes the risk of hip fracture in an individual. A Poisson process is used to model the occurrence of falls, which are assumed to occur at a rate, lambda. The load induced by a fall is assumed to be a random variable that has a Weibull probability distribution. The combination of falls together with loads leads to a compound Poisson process. By retaining only those occurrences of the compound Poisson process that result in a hip fracture, a thinned Poisson process is defined that itself is a Poisson process. The fall rate is modeled as an affine function of age, and hip strength is modeled as a power law function of bone mineral density (BMD). The risk of hip fracture can then be computed as a function of age and BMD. By extending the analysis to a Bayesian framework, the conditional densities of BMD given a prior fracture and no prior fracture can be computed and shown to be consistent with clinical observations. In addition, the conditional probabilities of fracture given a prior fracture and no prior fracture can also be computed, and also demonstrate results similar to clinical data. The model elucidates the fact that the hip fracture process is inherently random and improvements in hip strength estimation over and above that provided by BMD operate in a highly "noisy" environment and may therefore have little ability to impact clinical practice. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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