Assessing Statistical Methods for Estimating the Cerebrospinal Fluid Early Fungicidal Activity as an Endpoint for Cryptococcal Meningitis Clinical Trials: A Systematic Review and Simulation Study

Background: Cryptococcal meningitis is a life-threatening infection of the central nervous system. Early fungicidal activity (EFA), which measures how quickly Cryptococcus yeasts are cleared from cerebrospinal fluid (CSF) over time, is a key endpoint in phase 2 antifungal clinical trials. EFA is commonly estimated via a 2-step approach, where simple linear regressions are first fit to each individual's longitudinal measurements, and the slopes are then aggregated for statistical inference. Alternatively, a linear mixed model can estimate individual and group-level effects in one model. A systematic comparison of these methods is needed to understand and clarify their differences in analyzing EFA data in clinical trials. Methods: We conducted a systematic literature review to summarize the usage and reporting of both methods in cryptococcal meningitis clinical trials. We then evaluated their performance and operating characteristics under various simulation scenarios and applied both approaches to data from a phase 2 trial. Results: The 2-step approach and mixed model approach yielded discrepant CSF EFA estimates across literature review, simulation experiments, and real data analysis. The 2-step approach using linear regression produced steeper estimates and larger estimated treatment effects. The linear mixed model yielded smaller standard errors but estimates were biased toward the null, especially when early culture sterility was common. Conclusions: The 2-step approach is preferred for estimating EFA in cryptococcal meningitis studies, especially when early culture sterility occurs. EFA estimates should not be interpreted or compared across studies without accounting for the underlying statistical models and data preprocessing.