In epidemiology, an intention to treat (ITT) analysis is an analysis based on the initial treatment intent, not on the treatment eventually administered. It is based on the assumption that, as in real life, sometimes patients do not all receive optimal treatment, even though that was the initial intention. For the purposes of analysis, the reasons why the patient did not receive the treatment are ignored.

Rationale

Intention to treat analyses are done to avoid the effects of crossover and drop-out, which may break the randomization to the treatment groups in a study. Intention to treat analysis provides information about the potential effects of treatment policy rather than on the potential effects of specific treatment.

In contrast, efficacy subset analysis 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
• inflate the type I error; this effect is greater the larger the trial^[1].

Full application of intention to treat can only be performed where there is complete outcome data for all randomised subjects.

Although intention to treat is widely cited in published trials, it is often incorrectly described and its application may be flawed.

References

1. ^ Lachin JM (June 2000). "Statistical Considerations in the Intent-to-Treat Principle". Statistics in Medicine 21 (3): 167-189. PMID 10822117.

See also

• Randomized controlled trial
• Clinical trial
• Per-protocol analysis