Addressing the statistical analysis dilemma that exists when analyzing clinical trial results with full efficacy using the Kaplan Meier survival analysis method
Peerawaranun P., Van Der Pluijm RW., Mukaka M.
The use of a Kaplan-Meier (K-M) survival time approach is generally considered appropriate to report antimalarial efficacy trials. However, when a treatment arm has 100% efficacy, confidence intervals may not be computed. Furthermore, methods that use probability rules to handle missing data for instance by multiple imputation, encounter perfect prediction problem when a treatment arm has full efficacy, in which case all imputed values are either treatment success or all imputed values are failures. The use of a survival K-M method addresses this imputation problem in estimating the efficacy estimates also referred to as cure rates. We discuss the statistical challenges and propose a potential way forward. The proposed approach includes the use of K-M estimates as the main measure of efficacy. Confidence intervals could be computed using the binomial exact method. p-Values for comparison of difference in efficacy between treatments can be estimated using Fisher's exact test. We emphasize that when efficacy rates are not 100% in both groups, the K-M approach remains the main strategy of analysis considering its statistical robustness in handling missing data and confidence intervals can be computed under such scenarios.