Item 13 of the CONSORT statement recommends a flow diagram to aid in the reporting of participant flow (see Box 1).1 Box 2 provides a checklist for tracking subject participation throughout the trial. In this scheme Part A refers to the number of participants with the condition of interest screened for eligibility criteria as specified in the trial protocol. For a recent example see the Second Australian National Blood Pressure trial.2 This study clearly details the process resulting in the final 6083 participants recruited. With 54 288 people screened to participate, 31 255 had the condition of interest (hypertension). Of these, 8273 were found to be ineligible and 16 899 refused to participate. The remaining 6083 were randomly allocated, corresponding to Part C of the flowchart in Box 2. The ratio of participants randomly allocated to those initially assessed helps determine how generalisable the results of the trial will be, and consequently may also affect the extent to which the results of the trial might influence health policy. Part B of Box 2 indicates assessed participants who do not subsequently participate, with reasons for non-participation given. Enough information should be given to identify separately the numbers who were deemed ineligible, refused to participate and those not randomly allocated to an intervention for other reasons.

The ratio of the number of participants to the number of people initially assessed for eligibility may also provide an insight into the acceptability and practicability of the intervention. For example, if 2000 people were assessed and only 300 recruited, such a low ratio might be the result of highly restrictive eligibility criteria, participant requirements that are too complicated or impractical, or an intervention too intrusive for participants to readily accept over standard care.

Of the total number of participants randomly allocated, the number assigned to each of the study arms should be separately presented (Box 2, Part D). A breakdown of the number of participants who actually received the allocated treatment and those who did not (with reasons given) should be included. This information, together with details of participant follow-up (see below), helps determine how well the intentions of the protocol were met.

During the trial, participants' status in terms of outcomes (both efficacy and safety) is usually ascertained at predefined time intervals. However, some participants may withdraw from the study before completion; these participants are classified as "lost to follow-up" from that point onwards. Details of the number of participants who are lost to follow-up in each of the study arms are essential (Box 2, Part E), as this provides information on the reliability of the study's conclusions. When participants cannot be accounted for at the end of the study, their outcome status cannot be determined. If substantial numbers of participants are lost to follow-up, concerns may arise about the integrity of any observed effect of an intervention.

A common approach to evaluating the potential influence of losses to follow-up is to use a sensitivity analysis, where worst-case and best-case scenarios relating to these losses are examined. For example, at one extreme, it could be assumed that all the control-arm and none of the intervention-arm participants who were lost to follow-up suffered the outcome of interest. At the other extreme, the opposite (ie, all intervention-arm participants lost to follow-up and none of the control participants lost to follow-up have suffered the outcome of interest) could be assumed. This provides bounds for the maximum possible influence of such losses on the observed treatment effect. Less extreme (more plausible) scenarios can also be examined. If this results in the effect of treatment disappearing or reversing direction, the robustness of the results should be questioned. Box 3 provides an example.

A further issue in interpreting study results is the degree to which participants adhered to their allocated treatment during the study period. Participants who stop or never take their allocated treatment are usually called "drop-outs", and those who begin active treatment when they have been allocated to the control group are called "drop-ins"; all are considered compliance losses. Compliance losses reduce the study power and dilute the observed effects of treatment, and should be documented in the participant flow (Box 2, Part E). Where such non-compliance can be predicted in advance, its potential effect on the power of the study may be reduced by increasing the study sample size.3 Differential compliance rates may offer clues as to the real side-effects of an intervention, or about the success of methods used to blind participants or clinicians to treatments.4

Part F of Box 2 relates to the number of participants who were included in the statistical analyses. If any other than those lost to follow-up have been excluded from analysis, both the number in each treatment arm and the reasons should be detailed. As excluding patients from analysis can potentially undermine the effectiveness of the randomisation4 and produce comparisons which may no longer conform to the intention-to-treat principle,5 the nature of, and justification for, any such exclusions should also be provided.