Although seizure freedom is always the goal of initiating antiepileptic drug (AED) therapy in patients with epilepsy, identifying when this goal has been achieved can be problematic. A common challenge for epileptologists lies in determining what constitutes an adequate amount of time without seizures following an intervention such as the start of a new medication for a patient to be considered seizure-free. This determination has important implications for counseling patients about when to resume risky activities, and for public policy such as how long patients must go without seizures before returning to driving. A recent International League Against Epilepsy (ILAE) task force proposed that a patient should be considered “seizure-free” in response to a new antiseizure treatment (e.g., medication or surgery) once they have gone without a seizure for at least three times the duration of their longest preintervention interseizure interval in the preceding 12 months (Kwan et al., 2009). Inspiration for this proposed working definition of seizure freedom is credited to a statistical principle known as the “Rule of Three,” proposed several decades ago as a generic statistical rule of thumb for reasoning about “zero numerators,” that is, for inferring from the fact that no adverse events have occurred so far the probability that an adverse event may yet occur at some future time (Hanley & Lippman-Hand, 1983; Jovanovic & Levy, 1997). However, as acknowledged by the ILAE task force, the proposed application toward the determination of seizure freedom entails a compromise, dictated by practical considerations rather than following strictly from the logic embodied in the original statistical formulation of the Rule of Three (Kwan et al., 2009).

Because the Rule of Three has not to our knowledge been applied before to the problem of determination of seizure freedom, and because the rule in its original formulation is not widely known among epileptologists, our first goal in this article is to provide an accessible mathematical derivation and an explanation of its literal meaning and implications. We shall see that it relies on a type of “worst case scenario” reasoning which, followed strictly, requires waiting much longer than the period proposed in the ILAE task force definition of seizure freedom, in some cases for many years, hence the original Rule of Three apparently requires modification to be of practical clinical use. Hereafter, we refer to the original statistical formulation and its attendant statistico-logical implications as the “Classical Rule of Three.” Our second goal in this article is to propose a set of probabilistic considerations that do support the ILAE’s proposed pragmatic adaptation of the Classical Rule of Three, at least for many cases encountered in clinical practice, thus placing the rule on more solid theoretical grounds. We demonstrate that for many cases commonly encountered in practice a waiting period of three times the preintervention interseizure interval is adequate, whereas in other cases as long as six interseizure intervals is required. Consequently, we refer to our final justified-and-extended version of the Classical Rule of Three, and the attendant probabilistic considerations behind our formulation, as the “Rule of Three-To-Six.”

The fulcrum of our approach is the recognition that information available before initiating an intervention can be informative in interpreting the response to an intervention so far, whereas such information is ignored by the Classical Rule of Three. For example, in medication-naive adult epilepsy patients, it is well-known that roughly 50–70% become “seizure-free” in response to AED therapy, whereas for patients who have already “failed” one to two previous AEDs, the probability of achieving seizure freedom with subsequent AED trials is known to be low, around 5–10% (Kwan & Brodie, 2000, 2001). Similarly, certain carefully selected patients with lesional epilepsy can be quoted an approximately 80% probability of achieving seizure freedom with surgery (McIntosh et al., 2001). Such preintervention probabilities are routinely used in counseling patients who are contemplating new medical or surgical interventions. We therefore propose a simple statistical model that allows such estimates of the a priori probability of seizure freedom to be combined, via Bayes’ rule, with the time without a seizure since starting medication, to yield an informed estimate of the probability that a patient will remain seizure-free. This model provides a principled probabilistic justification for the ILAE’s proposed working definition of seizure freedom, rescuing it from the shortcomings of the Classical Rule of Three.