Treatment effects for which shift or binary analyses are advantageous in acute stroke trials.

Area of Science:

• Clinical Trials Methodology
• Stroke Research
• Biostatistics

Background:

• Functional outcomes in acute stroke trials are often analyzed using dichotomized scales or shift analysis.
• The comparative efficiency of these methods under different treatment effect scenarios remains unclear.

Purpose of the Study:

• To delineate the conditions under which shift analysis or dichotomized analysis is more efficient for evaluating functional outcomes in acute stroke trials.
• To compare the statistical power of different analytical approaches based on simulated treatment effects.

Main Methods:

• Modeled randomized clinical trials using the modified Rankin Scale.
• Simulated four types of treatment effects: mild universal benefit, early substantial universal benefit, late substantial benefit with limited full recovery, and benefits at unexpected health state transitions.

Main Results:

• Shift analysis demonstrated highest efficiency in neuroprotective and unexpected benefits models.
• In early recanalization models, shift analysis and dichotomization at excellent outcome were comparable and superior to dichotomization at good outcome.
• Dichotomization at good outcome was most efficient for late recanalization models, while shift analysis was less efficient.

Conclusions:

• The optimal analysis method (shift vs. dichotomized) depends on the specific pattern of treatment effect observed in acute stroke interventions.
• Shift analysis is particularly advantageous for interventions yielding uniform mild benefits across stroke severities or benefits at critical health state transitions.