Potential for extreme bias due to outcome misclassification in relative measures of effect for rare time-to-event...

Time-to-event outcomes are widely used in clinical and epidemiological research. For instance, studies of medical product safety often involve comparative analyses of rare time-to-event outcomes. The effects of misclassified outcomes and error in survival times for time-to-event data have not been widely investigated. In this Monte Carlo simulation study, we compared the relative bias of absolute and relative measures of effect under varying degrees of outcome misclassification, outcome incidences, direction of error in survival times, and the time point of inference. Relative measures of effect were susceptible to considerable downward bias, which was larger when the outcome incidence and specificity were lower, error in survival times led to earlier times, time point of inference was earlier, and the estimation excluded samples for which an estimate could not be obtained. For absolute measures of effect, the pattern of bias was much simpler, greater downward bias was primarily a function of the degree of sensitivity. The results suggest when the outcome incidence is rare, specificity and sensitivity are high, absolute measures of effect may be preferable to relative measures of effect.