migraine is topiramate but effective in only 1 in 4. Even
more surprising is that Botox, one of the most commonly
sought after treatments for chronic migraine prevention is
effective in only 1 in 9 patients.
How can this even be possible? The answer is that the
efficacy numbers shown in the diagram do not include
placebo effect. In real world drug use, the placebo effect
can account for 20 to 50% of the response to treatment
in patients (about 50% in migraine clinical trials). So
placebo effect added to a mediocre but real drug effect
equals more acceptable apparent results.
To be sure, nobody is against placebo effect - it is a very
safe way to get real clinical benefits. But to answer our
question: how effective is it really if we develop medicines
for Mr. or Ms. Average? Not very.
The fact that any given drug is therapeutically effective
in only a minority of patients flags a number of issues.
First, how much faith can we place in any “one size fits
all” therapeutic approach? Since the biochemical basis
for this failure is poorly understood, shouldn’t we try
to understand the mechanisms of individual disease
variation that limit the “one-size-fits-all” approach?
Finally, and most importantly, how can we develop better
therapeutic approaches that are built upon recognition of
individual variability?
Migraine, one of the leading causes of disability
worldwide 5 , is a model condition if we want to study
variation between individuals and the therapeutic
implications of these differences. The hallmark of
migraine is episodic, debilitating attacks that are easily
diagnosed and monitored. In addition, many people with
migraine have several attacks per month, so profiling
risk factors both positive and negative (e.g. therapies,
protectors, potential triggers etc.) associated with making
an individual patient better or worse can be done
relatively rapidly.
More importantly, patient susceptibility and
response to a wide range of potential factors represent
an important spectrum of real-world markers for
studying individual variation in genetic, physiological,
psychological, and ultimately biochemical domains. In
addition, many migraine population studies have already
been done, generating aggregate data about the average
migraine patient, which we can use to benchmark against
variation in the individual patient.
A first step toward understanding the level and basis of
individual variation in a chronic disease such as migraine
versus an “average profile” was recently accomplished
in a study done in collaboration with the Department
of Neurology, Medical University of Vienna and the
Plot showing mean cycle day of minimum estrogen
level in the cycle was day 2 (striped line) but
variation in day of minimum estrogen level (range
and median day) is shown for each women over
three cycles (solid purple line) showing that few
women had cycles in which the lowest estrogen day
was the same as the calculated mean.
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HeadW ise ®
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Volume 7, Issue 1 • 2018