<P> In order to include such participants in an analysis, outcome data could be imputed which involves making assumptions about the outcomes in the lost participants . Another approach would be efficacy subset analysis which selects the subset of the patients who received the treatment of interest--regardless of initial randomization--and who have not dropped out for any reason . This approach can introduce biases to the statistical analysis . It can also inflate the chance of a false positive; this effect is greater the larger the trial . </P> <P> ITT analysis requires participants to be included even if they did not fully adhere to the protocol . Participants who strayed from the protocol (for instance, by not adhering to the prescribed intervention, or by being withdrawn from active treatment) should still be kept in the analysis . An extreme variation of this is the participants who receive the treatment from the group they were not allocated to, who should be kept in their original group for the analysis . This issue causes no problems provided that, as a systematic reviewer, you can extract the appropriate data from the trial reports . The rationale for this approach is that, in the first instance, we want to estimate the effects of allocating an intervention in practice, not the effects in the subgroup of the participants who adhere to it . </P> <P> In comparison, in a per - protocol analysis, only patients who complete the entire clinical trial according to the protocol are counted towards the final results . </P>

Intention-to-treat vs. on-treatment analysis of clinical trial data