The intention-to-treat (ITT) analysis is a statistical method used in randomized controlled trials (RCTs) to include all randomized subjects regardless of their adherence to the treatment protocol. This approach maintains the prognostic balance from the original randomization and avoids overestimating the efficacy of an intervention by not excluding noncompliant or withdrawn subjects. ITT analysis is often described as "once randomized, always analyzed," ensuring that all subjects are considered in the analysis, even if they do not follow the protocol. This method is preferred because it minimizes bias and provides a more realistic reflection of clinical practice. However, ITT analysis can be conservative, as it may dilute the treatment effect due to noncompliance. It also introduces heterogeneity if noncompliant, dropout, and compliant subjects are mixed together. The per-protocol (PP) analysis, which excludes subjects who deviate from the protocol, is an alternative but may not reflect real-world scenarios as accurately. The ITT approach is recommended as the primary analysis in superiority trials, while PP analysis is considered supportive. In non-inferiority trials, both ITT and PP analyses are needed to ensure robust conclusions. The modified ITT (mITT) allows for the exclusion of some subjects but lacks consistent guidelines, leading to potential bias. Overall, ITT analysis is a crucial method in RCTs to ensure valid and unbiased results, despite its limitations.The intention-to-treat (ITT) analysis is a statistical method used in randomized controlled trials (RCTs) to include all randomized subjects regardless of their adherence to the treatment protocol. This approach maintains the prognostic balance from the original randomization and avoids overestimating the efficacy of an intervention by not excluding noncompliant or withdrawn subjects. ITT analysis is often described as "once randomized, always analyzed," ensuring that all subjects are considered in the analysis, even if they do not follow the protocol. This method is preferred because it minimizes bias and provides a more realistic reflection of clinical practice. However, ITT analysis can be conservative, as it may dilute the treatment effect due to noncompliance. It also introduces heterogeneity if noncompliant, dropout, and compliant subjects are mixed together. The per-protocol (PP) analysis, which excludes subjects who deviate from the protocol, is an alternative but may not reflect real-world scenarios as accurately. The ITT approach is recommended as the primary analysis in superiority trials, while PP analysis is considered supportive. In non-inferiority trials, both ITT and PP analyses are needed to ensure robust conclusions. The modified ITT (mITT) allows for the exclusion of some subjects but lacks consistent guidelines, leading to potential bias. Overall, ITT analysis is a crucial method in RCTs to ensure valid and unbiased results, despite its limitations.