Statistical approaches to evaluating the effect of risk factors on the pain of knee osteoarthritis in longitudinal studies


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Abstract

Purpose of reviewWe describe commonly used measures of knee pain in longitudinal studies and review various analytic approaches to evaluating the effect of a risk factor on each type of pain measure.Recent findingsIn longitudinal epidemiologic studies of knee pain, frequent knee pain and activity-related pain severity are the most commonly used measures for pain. Various analytic approaches have been used to evaluate the effect of a risk factor on each type of pain measure. Analytic approaches utilized include the generalized estimating equations model and the mixed-effects linear regression model for pain severity assessed as a continuous outcome variable, the mixed-effects logistic regression model and conditional logistic regression model for pain exacerbation measured as a dichotomous outcome variable, and a mixed-effects regression model, stratified proportional odds model, and a multistate transition model for pain severity measured as an ordinal outcome variable.SummaryCompared with cross-sectional studies, longitudinal studies allow investigators to assess the effect of change in a risk factor of interest on change in risk of knee pain or change in pain severity. With appropriate analysis methods, investigators are able to minimize potential confounders that differ among individuals or knees but which do not vary over time within a person or knee.

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