BACKGROUND: Changes in patient-reported seizure frequencies are the gold standard used to test efficacy of new treatments in randomized controlled trials (RCTs). Recent analyses of patient seizure diary data suggest that the placebo response may be attributable to natural fluctuations in seizure frequency, though the evidence is incomplete. This study aims to develop a data-driven statistical model and assess the impact of the model on interpretation of placebo response.
METHODS: A synthetic seizure diary generator matching statistical properties seen across multiple epilepsy diary datasets was constructed. The model was used to simulate the placebo arm of 5000 RCTs. A meta-analysis of 23 historical RCTs was compared to the simulations.
RESULTS: The placebo 50%-responder rate (RR50) was 27.3 ± 3.6% (simulated) and 21.1 ± 10.0% (historical). The placebo median percent change (MPC) was 22.0 ± 6.0% (simulated) and 16.7 ± 10.3% (historical).
CONCLUSIONS: A statistical model of daily seizure count generation which incorporates quantities related to the natural fluctuations of seizure count data produces a placebo response comparable to those seen in historical randomized controlled trials. This model may be useful in better understanding the seizure count fluctuations seen in patients in other clinical settings.