Abstract:Objective
To assess how meniscus damage and baseline cartilage thickness influence the rate of cartilage loss and knee pain.
Methods
Of 4,796 participants in the Osteoarthritis Initiative (OAI), 86 had baseline and 48 month follow-up quantitative MRI data for medial compartment cartilage thickness. Baseline meniscus pathology was scored by a musculoskeletal radiologist using Whole-Organ Magnetic Resonance Imaging Score (WORMS). Findings were correlated with 72-month Knee Injury and Osteoarthritis Outcome Sco… Show more
“…A previous study showed that subjectively graded joint space narrowing was a risk factor for frequent pain in subjects that had frequent knee pain in one knee but not in the contralateral knee [ 9 ]. However, other investigators have not been able to document an association between joint space narrowing and symptoms [ 10 - 11 ]. A re-analysis of the data using the threshold limit graphical approach described in this paper may provide additional insights into the association between change in the knee joint space and outcomes in the OAI study, other knee studies, and eventually in clinical practice.…”
Scatter plots, bar charts, linear regressions, analysis of variance, and other graphics and tests are frequently used to document associations between an independent variable and an outcome. However, these methods are also frequently limited when understanding how to use an independent variable in subsequent research or patient management. A novel graphical approach to visualizing data—the threshold limit graph—was therefore developed.Publically available data from the Osteoarthritis Initiative was used to illustrate the graphical approach to understanding the association between the change in joint space width (ΔJSW, independent variable) over four years, and knee symptoms at four years (using the Knee Injury and Osteoarthritis Outcome Score [KOOS], dependent variable).Using data for 4,202 knees, the traditional scatter plot and linear regression approach showed a significant but weak linear relationship between the symptom subscore of the KOOS and ΔJSW. However, the threshold level of ΔJSW that affects symptoms was not clear from the data. The same dataset was then plotted using the threshold limit graphical approach, which revealed a non-linear relationship between the variables. In contrast to the scatter plot, plotting the average KOOS symptom subscore for subgroups of the data, with each subgroup defined using sequentially increasing or decreasing ΔJSW thresholds revealed that symptoms got worse with joint space loss, but only when there was a significant amount of ΔJSW. A threshold limit analysis was repeated using small, randomly selected subsets of the data (N = ~100) to demonstrate the utility of the technique for identifying trends in smaller datasets.The threshold limit graph is a simple, graphical approach that may prove helpful in understanding how an independent variable might be used to predict outcomes. This approach provides an additional option for visualizing and quantifying associations between variables.
“…A previous study showed that subjectively graded joint space narrowing was a risk factor for frequent pain in subjects that had frequent knee pain in one knee but not in the contralateral knee [ 9 ]. However, other investigators have not been able to document an association between joint space narrowing and symptoms [ 10 - 11 ]. A re-analysis of the data using the threshold limit graphical approach described in this paper may provide additional insights into the association between change in the knee joint space and outcomes in the OAI study, other knee studies, and eventually in clinical practice.…”
Scatter plots, bar charts, linear regressions, analysis of variance, and other graphics and tests are frequently used to document associations between an independent variable and an outcome. However, these methods are also frequently limited when understanding how to use an independent variable in subsequent research or patient management. A novel graphical approach to visualizing data—the threshold limit graph—was therefore developed.Publically available data from the Osteoarthritis Initiative was used to illustrate the graphical approach to understanding the association between the change in joint space width (ΔJSW, independent variable) over four years, and knee symptoms at four years (using the Knee Injury and Osteoarthritis Outcome Score [KOOS], dependent variable).Using data for 4,202 knees, the traditional scatter plot and linear regression approach showed a significant but weak linear relationship between the symptom subscore of the KOOS and ΔJSW. However, the threshold level of ΔJSW that affects symptoms was not clear from the data. The same dataset was then plotted using the threshold limit graphical approach, which revealed a non-linear relationship between the variables. In contrast to the scatter plot, plotting the average KOOS symptom subscore for subgroups of the data, with each subgroup defined using sequentially increasing or decreasing ΔJSW thresholds revealed that symptoms got worse with joint space loss, but only when there was a significant amount of ΔJSW. A threshold limit analysis was repeated using small, randomly selected subsets of the data (N = ~100) to demonstrate the utility of the technique for identifying trends in smaller datasets.The threshold limit graph is a simple, graphical approach that may prove helpful in understanding how an independent variable might be used to predict outcomes. This approach provides an additional option for visualizing and quantifying associations between variables.
“…Longitudinal medial tibiofemoral compartment cartilage structural progression over 8 years was associated with worsening semiquantitative meniscal tear scoring for the combined medial and lateral menisci over 8 years 26 . Only two of the 16 cohort analyses did not support the association of meniscal tear with structural progression 25,38 .…”
“…While walking speed decline is a prognostic marker of knee OA, how it relates to structural changes prior to the onset of radiographic OA remains unclear. Understanding whether early changes in walking speed are associated with commonly used sensitive measures of knee health that are related to OA onset and progression (e.g., changes in bone marrow lesions [BMLs; ], effusion , or cartilage ) may provide a better understanding of the early link to physical function and joint health decline.Understanding whether early changes in walking speed are associated with sensitive measures of knee structure may provide a better understanding of the early link to physical function and joint health decline.Individuals with accelerated knee osteoarthritis present with earlier worsening of knee structure as well as poorer patient‐reported and physical function measures compared to individuals with a more common, gradual onset of knee osteoarthritis.Individuals with accelerated knee osteoarthritis who slowed their walking speed were 3.0 and 3.4 times more likely to demonstrate an increase in bone marrow lesion and effusion volume, respectively.Cartilage structure changes were not associated with walking speed decline in individuals with accelerated or common knee osteoarthritis.…”
A change in an easily assessable clinical examination (i.e. 20m walk test) is associated with concurrent worsening in BML and effusion volume in adults who developed AKOA. This article is protected by copyright. All rights reserved.
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