Statistical Analysis
REGRESSION
A power analysis was performed before the study. It was based on the assumption that the minimal clinically important difference (MCID) for the main outcome, the AOFAS score, was 10 points. At present, no MCID values exist for AOFAS in this patient group. Ten was considered an adequate difference because several studies have reported MCID values to be in the same range (7.9-30.2, 8.9, 8.9, and 9.5) in treatment of other foot pathologies.We used the following treatment allocations to estimate the treatment effect: intention-to-treat (ITT), per protocol (PP), and per protocol excluding crossovers (PPEC). The ITT analysis evaluates treatment effect according to the treatment patients received through baseline randomization, not considering that some of the patients are crossovers. The PP analysis is performed with patients allocated to the treatment received at 6 years. The PPEC analysis is also based on treatment received at 6 years but excluding crossovers to preserve the randomization.To estimate the treatment effect at 6-year follow-up, we performed a linear mixed effects model for each outcome listed above (except MOxFQ), with random intercept and allocation-time interaction, adjusted for baseline level of the respective outcome. We included all patients with a valid baseline measurement of the respective outcome. Missing data during follow-up are handled implicitly by the model.The primary effect estimate was defined as the marginal mean difference from the mixed model with PPEC allocation between AOFAS score at 6 years. We chose this allocation because it reflects the treatment patients received at 6 years and it preserves the randomization.For the ankle dorsiflexion and Achilles complex performance analysis, some patients contributed 2 feet to the analysis. For these data, the model included 2 random intercepts, first the ID of the foot and then the ID of the patient.Model fit was investigated by looking at the residuals (qnorm plot, scatter plot of fitted vs residuals).The MOxFQ score was only assessed at the 6-year follow-up (no baseline value). The treatment effect for this outcome was estimated using a linear regression model with the MOxFQ score as dependent and treatment allocation as independent variable.An external statistician was consulted in determining adequate statistical methods, performing the analyses, and interpreting the results of this study.