CLINICAL
NEWS JACC in a FLASH
Does Data Mining
Help Identify
Harmful Drug
Interactions?
The authors
said more work
needs to be done
to understand
fat density, and
why and how
it is associated
with metabolic
consequences of
obesity.
14
CardioSource WorldNews
adverse changes in cardiovascular risk
were evident over a relatively short
period of time and persisted even
after accounting for changes in BMI
and waist circumference.
Moving forward, the authors said
more work needs to be done to understand fat density, and why and how it
is associated with metabolic consequences of obesity (e.g., hypertension, abnormal cholesterol, diabetes,
inflammation and insulin resistance).
Also, it will be important to understand how less dense fat, along with
simultaneous increases in the amount
of fat may spur the development of
harmful cardiometabolic changes.
In an editorial comment accompanying the study, Ian J. Neeland, MD,
and James A. de Lemos, MD, wrote
that while there are a number of
important questions that still need to
be answered, these findings “support
a growing body of data that clearly
demonstrate that adipose tissue imaging, which allows anatomical characterization of regional fat depots,
provides important information about
cardiometabolic risk not contained in
the simple BMI measurement.”
By coupling data mining of adverse
event reports and electronic health records with targeted laboratory experiments, researchers may have found a
way to identify and confirm previously unknown drug interactions,
according to a study published Oct.
10 in JACC. Specifically, researchers
discovered that when taken together,
ceftriaxone and lansoprazole may be
associated with an increased risk of
acquired long QT syndrome.
Using an algorithm called Latent
Signal Detection, Nicholas Tatonetti,
PhD, and colleagues scanned data from
two independent databases to investigate possible QT interval-prolonging
drug-drug interactions. All told, 1.8
million adverse event reports were
analyzed from the U.S. Food and Drug
Administration’s (FDA) Adverse Event
Reporting System and 1.6 million
electrocardiograms were analyzed from
382,221 patients treated at New YorkPresbyterian/CUMC between 1996
and 2014. The most likely drug-drug
interactions were flagged, allowing researchers to then apply more traditional
analyses and laboratory experiments to
validate the predictions.
Results showed that patients taking ceftriaxone and lansoprazole were
40% more likely to have a QT interval
above 500 ms, which is the current
FDA-stated threshold of clinical
concern. Among men taking both of
these drugs, QT intervals were 12ms
longer than men who took either drug
alone. This trend was then validated
by cellular data from the electrophysiology experiment, which found that
together these drugs blocked one
of the cardiac ion channels responsible for controlling heart rhythm.
Researchers also noted that white
women and men appeared to be more
sensitive to this interaction.
In an accompanying editorial,
Dan M. Roden, MD, and colleagues
noted that the study’s findings are not
robust enough to advise clinicians to
avoid this combination in all patients.
However, they note the findings highlight the need to examine the effects
of these drugs individually and in
combination in patients – especially
given an aging population and the
likelihood of patients taking multiple
medications.
“Solving the methodological challenges of developing approaches to
systematically leverage these data
sources will be a next frontier in identifying and preventing adverse drug
reactions,” they said.
Lorberbaum T, Sampson KJ, Chang JB, et al..
J Am Coll Cardiol. 2016;68(16):1756-64.
Lee JJ, Pedley A, Hoffmann U, Massaro JM, Fox CS. J Am Coll Cardiol.
2016;68(14):1509-21.
November 2016