Statistical consideration for bilateral cases in orthopaedic research.

Background: Statistical independence means that one observation is not affected by another; however, the principle of statistical independence is violated if left and right-side measures within a subject are considered to be independent, because they are usually correlated and can affect each other. The purpose of the present study was to analyze the violation of statistical independence in recent orthopaedic research papers and to demonstrate the effect of statistical analysis that considered the data dependency within a subject.

Methods: First, all original articles that had been published in The Journal of Bone and Joint Surgery (American Volume) over a two-year period were evaluated. The analysis was designed to identify articles that included bilateral cases and possible violations of statistical independence. Second, a demonstrative logistic regression without consideration of statistical independence was performed and was compared with a statistical analysis that considered data dependency within a subject. Radiographs of 1200 hips in 600 patients were used to examine the differences in terms of odds ratios (with 95% confidence intervals) of the risk factors for hip osteoarthritis.

Results: Four hundred and eighty-six original articles were reviewed, and 151 articles (including forty-one articles involving the hip, thirty-four involving the knee, twenty-one involving the foot or ankle, nineteen involving the shoulder, ten involving the hand or wrist, nine involving the elbow, and seventeen involving other structures) were considered to include bilateral cases. Of the 486 articles that were reviewed, 120 articles (25%) (including thirty-six articles involving the hip, twenty-six involving the knee, fifteen involving the foot or ankle, fourteen involving the shoulder, seven involving the elbow, six involving the hand or wrist, and sixteen involving other structures) were found to have possibly violated statistical independence. Demonstrative statistical analysis showed that logistic regression was not robust to the violation of statistical independence. The 95% confidence intervals of the odds ratios for the risk factors showed narrower ranges (1.13 to 2.68 times) when data dependency within a subject was not considered.

Conclusions: Researchers need to consider statistical independence when performing statistical analysis, particularly in studies involving bilateral cases. If data dependency within a subject is not considered, studies involving bilateral cases can bias results, depending on the context of those studies.