title: Predicting Knee Osteoarthritis.
abstract: Treatment options for osteoarthritis (OA) beyond pain relief or total knee replacement are very limited. Because of this, attention has shifted to identifying which factors increase the risk of OA in vulnerable populations in order to be able to give recommendations to delay disease onset or to slow disease progression. The gold standard is then to use principles of risk management, first to provide subject-specific estimates of risk and then to find ways of reducing that risk. Population studies of OA risk based on statistical associations do not provide such individually tailored information. Here we argue that mechanistic models of cartilage tissue maintenance and damage coupled to statistical models incorporating model uncertainty, united within the framework of structural reliability analysis, provide an avenue for bridging the disciplines of epidemiology, cell biology, genetics and biomechanics. Such models promise subject-specific OA risk assessment and personalized strategies for mitigating or even avoiding OA. We illustrate the proposed approach with a simple model of cartilage extracellular matrix synthesis and loss regulated by daily physical activity.
authors.affiliation: School of Engineering and Information Technology, Murdoch University, Perth, WA, Australia.
authors.forename: Bruce S
authors.initials: BS
authors.lastname: Gardiner
authors.affiliation: Faculty of Engineering, Computing and Mathematics, The University of Western Australia, Perth, WA, Australia. francis.woodhouse@uwa.edu.au.
authors.forename: Francis G
authors.initials: FG
authors.lastname: Woodhouse
authors.affiliation: Department of Engineering Science, Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
authors.forename: Thor F
authors.initials: TF
authors.lastname: Besier
authors.affiliation: Departments of Biological Engineering, Electrical Engineering and Computer Science & Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Alan J
authors.initials: AJ
authors.lastname: Grodzinsky
authors.affiliation: Centre for Musculoskeletal Research, Griffith Health Institute, Griffith University, Gold Coast, QLD, Australia.
authors.forename: David G
authors.initials: DG
authors.lastname: Lloyd
authors.affiliation: Department of Infrastructure Engineering, The University of Melbourne, Melbourne, VIC, Australia.
authors.forename: Lihai
authors.initials: L
authors.lastname: Zhang
authors.affiliation: Faculty of Engineering, Computing and Mathematics, The University of Western Australia, Perth, WA, Australia.
authors.forename: David W
authors.initials: DW
authors.lastname: Smith
mesh_terms: D002356:Cartilage / Q000378:metabolism / Q000473:pathology / Q000503:physiopathology; D005109:Extracellular Matrix / Q000378:metabolism / Q000473:pathology; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D020370:Osteoarthritis, Knee / Q000378:metabolism / Q000473:pathology / Q000503:physiopathology; D011237:Predictive Value of Tests; D018570:Risk Assessment
keywords: Biomechanical modeling; Cartilage degeneration; Extracellular matrix; Structural reliability analysis; Subject-specific risk prediction