Fifty-six studies included a definition of the ITT population, primarily within the methods (38) and results (18) sections. Of the 42 studies where all randomized subjects were analyzed, 20 included definitions of ITT. Diagrams showing the flow of participants through each trial were present in 41 of 100 articles, including 1 on a journal’s web site. An additional 8 articles had diagrams that showed patient flow without giving the number of patients. Presence of a flow diagram was not related to whether or not all randomized subjects were included in the ITT analysis (36% vs 45% respectively, P = .37). Of the 31 articles from journals that participate in CONSORT, 29 included flow diagrams, compared with 12 of the 69 articles from journals that do not participate in CONSORT (P < .0001).
TABLE
Categories of randomized patients excluded from ITT analysis*
| Category | Number of studies |
|---|---|
| All randomized subjects were analyzed (true intention to treat) | 42 |
| Some randomized subjects were excluded | 58 |
| Subjects found not to meet entry criteria | 12 |
| Subjects who did not receive any of the assigned treatment | 14 |
| Subjects who received some but not all of the assigned treatment | 1 |
| Subjects with no follow-up after randomization | 16 |
| Subjects with some but not all follow-up achieved | 1 |
| Subjects who dropped out for selected reasons | 4 |
| Subjects with specific protocol violations | 2 |
| Subjects with protocol violations but details not given | 2 |
| Other | 9 |
| Author needs to be contacted to determine who was in the ITT group | 13 |
| *Reports of 100 randomized trials were analyzed. Studies could have more than one group of excluded subjects. ITT, intention to treat. | |
Discussion
The hallmark of ITT analysis is that all randomized subjects are analyzed.7 In more than half of the articles we examined, this was not the case. Analysis of only certain subgroups of patients is sometimes appropriate, but an explanation should be provided whenever subjects are left out of any analysis. For example, we examined a report of a trial that was stopped based on the results of an interim analysis, thus excluding subjects who were randomized after the interim analysis.11 This type of exclusion, based on an a priori decision rather than individual characteristics or behavior, is less likely to bias results.
While all the articles in our sample reported analysis by ITT, many authors did not define the term, even when they excluded some randomized subjects from the ITT analysis. In these cases, the reader is left to infer which subjects were excluded based on information given in the text, figures, and tables.
Despite numerous recommendations for detailed reporting of RCT methods,1-4 many articles were vague and lacked detail. We could not determine which categories of participants were excluded from the ITT analysis in 13 articles. In 8 of the 100 articles we examined, we could not determine how many subjects were randomized or included in the ITT or primary analysis. Four of these 8 articles were in journals that endorsed the CONSORT statement. All were published well after the initial CONSORT statement was released in 1996.1
The number of randomized subjects excluded from the ITT analysis was usually small. It is unlikely that excluding up to 1% of subjects had a major effect on the results. In 11% of our sample, however, more than 10% of randomized subjects were excluded. Exclusions of this magnitude have significant potential to alter the findings. When outcome data can’t be determined and the outcome is categorical (eg, alive/dead), it can be helpful to produce best-case and worst-case scenarios in which patients lost to follow-up are arbitrarily ascribed good or bad outcomes. These extremes delimit the potential effect of the exclusions on results.12 Similarly, missing continuous outcomes (eg, weight change) can be assigned specific values to determine the potential impact on the results.
We assessed only articles that mentioned ITT in the abstract, so we probably missed some studies that used ITT analysis; however, we doubt that this caused us to significantly underestimate accurate use of the term ITT. The articles came from a wide spectrum of journals (62), of which 21 were listed in the Abridged Index Medicus subset. The 17 articles requiring a committee vote described the analytic process in terms that were often vague and ambiguous. In these cases, we cannot be certain that we correctly interpreted the authors’ methods; most readers would have similar difficulties.
We found considerable variation in how the term ITT was used in reports of RCTs. Fewer than half of the reports we examined included all randomized subjects in the ITT analysis. While exclusions were negligible in many cases, more than 10% of the subjects were excluded in 10% of the trials. In 7 trials, including some drawn from journals that endorse the CONSORT statement, it was not even possible to determine the number of subjects included in the ITT analysis. These problems highlight the continued need for better reporting of clinical trials.