An intention-to-treat analysis of the results of an experiment is based on the initial treatment
assignment and not on the treatment eventually received.
ITT analysis is intended to avoid various misleading artifacts that can arise in intervention
research such as non-random attrition of participants from the study or crossover.
ITT is also simpler than other forms of study design and analysis because it does not require
observation of compliance status for units assigned to different treatments or incorporation
of compliance into the analysis.
Although ITT analysis is widely employed in published clinical trials, it can be incorrectly
described and there are some issues to its application.
Furthermore, there is no consensus on how to carry out an ITT analysis in the presence
of missing outcome data.
Rationale Randomized clinical trials analyzed by the
intention-to-treat approach provide unbiased comparisons among the treatment groups.
Intention to treat analyses are done to avoid the effects of crossover and dropout, which
may break the random assignment to the treatment groups in a study.
ITT analysis provides information about the potential effects of treatment policy rather
than on the potential effects of specific treatment.
Since it started in the 1960s, the principle of ITT has become widely accepted for the
analysis of controlled clinical trials.
Example In an ITT population, none of the patients
are excluded and the patients are analyzed according to the randomization scheme.
In other words, for the purposes of ITT analysis, everyone who is randomized in the trial is
considered to be part of the trial regardless he or she is dosed or completes the trial.
For example, if people who have a more refractory or serious problem tend to drop out of a study
at a higher rate, even a completely ineffective treatment may appear to be providing benefits
if one merely compares the condition before and after the treatment for only those who
finish the study.
Issues Medical investigators often have difficulties
in accepting ITT analysis because of clinical trial issues like missing data or adherence
to protocol.
To address some of these issues, many clinical trials have excluded participants after the
random assignment in their analysis, which is often referred to as modified intention-to-treat
analysis or mITT.
Trials employing mITT have been linked to industry sponsorship and conflicts of interest
by the authors.
Missing data
An important problem is the occurrence of missing data for participants in a clinical
trial.
This can happen when patients are lost to follow-up and no response is obtainable for
these patients.
However, full application of ITT analysis can only be performed where there is complete
outcome data for all randomized subjects.
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.
Adherence to protocol ITT analysis requires participants to be included
even if they did not fully adhere to the protocol.
Participants who strayed from the protocol 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.
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.
See also Analysis of clinical trials
Protocol Clinical trial
Randomized controlled trial References
External links Intention to Treat Bandolier's definition
Intention to Treat – Tufts.edu Intention-to-Treat Analysis – Bu.edu
What is meant by intention to treat analysis?
Survey of published randomised controlled trials – BMJ
Intention-to-treat principle – CMAJ Inclusion of patients in clinical trial analysis:
the intention-to-treat principle – eMJA Inconsistent Definitions for Intention-To-Treat
in Relation to Missing Outcome Data: Systematic Review of the Methods Literature PLoS ONE
Alshurafa et al.