In epidemiology, an intention to treat (ITT) analysis (sometimes also called intent to treat) is an analysis based on the initial treatment intent, not on the treatment eventually administered. ITT analysis is intended to avoid various misleading artifacts that can arise in intervention research. For example, if people who have a more refractory or serious problem tend to drop out 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 treatment (ignoring those who were enrolled originally, but have since been excluded or dropped out). For the purposes of ITT analysis, everyone who begins the treatment is considered to be part of the trial, whether he or she finishes it or not. This is different from per-protocol analysis.
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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:
Full application of intention to treat can only be performed where there is complete outcome data for all randomized subjects.
Although intention to treat is widely cited in published trials, it is often incorrectly described and its application may be flawed.[2]