Since these schemes all depend upon assumptions about the structure of the data it s difficult to recommend one over the other for all situations. If dropouts occur for non-random reasons, it is more important to discover and adjust for these reasons than to provide a single statistic. Careful attention should be given to collecting baseline data for comparison of dropout and non-dropout groups. As a specific recommendation, last observation carried forward is probably not appropriate for ALS trials. Stratification Since randomization is not perfect it is often necessary to make sure that key covariates are balanced between the arms of a trial by stratifying on these variables and then conducting blocked randomization within strata.
Clinical sites are almost always one of the strata.
Other possible strata depend upon the disease and the impact of the covariate on the outcome. Covariates which should be considered for strata are those which are highly predictive of the outcome measure being used. At this time, site of onset, age, and FVC are all variables in ALS that are worth considering as separate strata in future trials. Very predictive variables are those with relative risks of 2 or 3. The strata need to be specified in advance and they are part of the primary analysis.