Association between Varus and Valgus Aberration, Load characteristics, and Osteoarthritis of the knee in a Normal population (AVALON)

C. Perka, Head & J. Fussi, Dept. of Orthopedic Surgery, Center for Musculoskeletal Surgery (CMSC) & D.Stengel, UKB Berlin/ CharitéUniversitätsmedizin Berlin & C. O. Schmidt, K. Hegenscheid, University Medicine of Greifswald (UMG)

Abstract: Overload caused by varus or valgus deformation may increase the risk of cartilage degeneration. However, clinical evidence is conflicting and major population-based studies lack routine full leg imaging. Understanding alignment-associated degenerative changes may help to prevent or even rectify tissue damage of the knee. The Study of Health in Pomerania (SHIP) is a population-based study providing data necessary to address the mentioned objectives. To utilize resources more efficiently, the original investigation plan based on the full longitudinal SHIP cohort was skipped in favor of a nested-case control study. This study will correlate measures of exposure (i.e., limb axes, and varus and valgus deviations) and outcome (i.e., risk of osteoarthritis), and semi-quantitative changes osteoarthritis-associated changes of the affected knee joint(s) (as expressed by the Whole-Organ MRI Score [WORMS]) (Peterfy CG et al. Osteoarthritis Cartilage 2004;12:177-90).

During scheduled follow-up examinations of SHIP participants (covering an observation interval of about 6 years) those with osteoarthritis (cases) will be identified in the entire cohort according to a valid practical MRI grading system (Park HJ et al. Eur J Radiol 2013;82:112-7). Controls will be selected considering known confounders and risk factors for osteoarthritis available in SHIP and matched to cases in an adequate ratio using innovative techniques. We will determine crude and adjusted relative risks of osteoarthritis, as well as variability in knee alignment and its time-dependent change.

Current population-based evidence suggests that there will be sufficient variability in limb axis alignment for modeling associations with the endpoints of interest (Sharma L et al. Ann Rheum Dis 2010;69:1940-5). With different assumptions and several scenarios (e.g., varying baseline risks of osteoarthritis, different correlation between multiple predictor variables, and others), the available sample size will allow for detecting odds ratios (OR) below 2.0 even using conservative test criteria. The sample size will also allow for both gender stratification and the evaluation of longitudinal changes in limb axes to detect small and medium sized effects (0.1-0.2) using appropriate and meaningful indices (e.g. standardized effect sizes) and statistical procedures.

For both consortia, the epidemiological study in OVERLOAD will provide a valuable overview about the distribution of limb axes and anatomical variants in healthy and osteoarthritis patients, and also contributes significant information for the intervention trial in PrevOP. Automated imaging markers developed in projects SP2 Overload (Eckstein) and SP4 PrevOP (Zachow), may be applied to data from SHIP for further assessment. 


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