Outcome assessment by central adjudicators in randomised stroke trials: Simulation of differential and non-differential misclassification

INTRODUCTION: We included data from five randomised stroke trials. Differential misclassification was introduced for each primary outcome until the estimated treatment effect was altered. This was simulated 1000 times. We calculated the between-simulation mean proportion of participants that needed to be differentially misclassified to alter the treatment effect. In addition, we simulated hypothetical trials with a binary outcome and varying sample size (1000-10,000), overall event rate (10%-50%) and treatment effect (0.67-0.90). We introduced non-differential misclassification until the treatment effect was non-significant at 5% level. RESULTS: For the five trials, the range of unweighted kappa values were reduced from 0.89-0.97 to 0.65-0.85 before the treatment effect was altered. This corresponded to 2.1%-6% of participants misclassified differentially for trials with a binary outcome. For the hypothetical trials, those with a larger sample size, stronger treatment effect and overall event rate closer to 50% needed a higher proportion of events non-differentially misclassified before the treatment effect became non-significant. DISCUSSION: We found that only a small amount of differential misclassification was required before adjudication altered the primary trial results, whereas a considerable proportion of participants needed to be misclassified non-differentially before adjudication changed trial conclusions. Given that differential misclassification should not occur in trials with sufficient blinding, these results suggest that central adjudication is of most use in studies with unblinded outcome assessment. CONCLUSION: For trials without adequate blinding, central adjudication is vital to control for differential misclassification. However, for large blinded trials, adjudication is of less importance and may not be necessary.