What type of analysis should be performed in a clinical trial that had high patient withdrawal rates for estimating benefits?

In a clinical trial with high patient withdrawal rates, performing an intention-to-treat analysis is critical for accurately estimating the benefits of the intervention under investigation. This analytical approach includes all participants in the groups to which they were originally assigned, regardless of whether they completed the study or adhered to the treatment protocol.

The intention-to-treat principle helps to eliminate bias that could arise from patient withdrawals. If participants who withdraw tend to have different outcomes than those who remain in the study, there can be a risk of skewed results if only the data from those who completed the trial are analyzed. By retaining all participants in their original groups, intention-to-treat analysis preserves the randomization benefits and reflects real-world scenarios more accurately. This approach is particularly important in clinical trials aimed at evaluating the effectiveness of interventions, as it provides a more realistic estimate of how the treatment would perform in a general population, taking into account the potential impact of patient dropouts.

In contrast, other types of analyses like on-treatment focus only on participants who adhered to the treatment protocols and exclude those who dropped out or switched therapies, which can lead to biased conclusions. A meta-analysis is a systematic review of multiple studies and is not applicable to analyzing a single trial's data in this scenario.