*Geek Box: Intention to Treat Analysis
In a randomised controlled trial, it is important to match both arms of the trial to ensure that one side doesn’t influence [i.e., bias] the results more than the other. This can be a problem if there is, for example, a high drop-out rate in one arm of the trial; the other arm will then have more statistical power, and it may over-inflate the effect of that arm vs. the comparative arm [or the control, if it is a control arm].
Intention to treat [ITT] is where the researchers will conduct analysis as if all subjects randomised in the trial completed it, irrespective of whether they dropped out, or didn’t comply with the protocol. Drop-out and noncompliance are two issues which face many trials, in particular nutrition and weight loss interventions.
True intention to treat analysis requires complete data to be available for all subjects who didn’t complete the trial according to protocol. However, that data is not always available, and so often researchers will make assumptions based on, e.g., a last data point or a baseline measurement.
Let’s say a participant dropped out of a 1yr weight loss trial after 6-months; the researchers would use their baseline weight and weight at 6-months, and the change in weight, as the data included in the statistical analysis, as if the participant had completed the full study.
Intention to treat is a positive because it maintains the study sample size, and it assumes a real-world practicality, because in the real world, not everyone is compliant with a protocol.