Home' Australian Pharmacist : Australian Pharmacist June 2015 Contents Australian Pharmacist June 2015 I ©Pharmaceutical Society of Australia Ltd.
CONTINUING PROFESSIONAL DEVELOPMENT
involving hospitalisation or death.
On average, similar percentages
would be predicted for patients on
warfarin since, as noted above, it is a
leading cause of hospitalisation due
Known clinical and
genetic factors currently account for
45–60% of clinical variability in patients
on warfarin (see Figure 1), and would
therefore be predicted to account for
a similar percentage of the 5–20% of
patients with minor and major bleeding
events described above.
correspond to approximately 2–9%
or more of all patients on warfarin.
While this may not appear large, with
over 2.5 million warfarin prescriptions
a large number of Australians
are therefore at risk of adverse outcomes
potentially due to genomic factors.
Claims that application of
pharmacogenomics knowledge does
not improve warfarin responses partly
reflect the lack of studies with sufficient
power to investigate bleeding events
directly in the small proportion of
patients with high‐risk genotypes.
Instead surrogate outcome measures
such as ‘time in therapeutic INR’ are
usually analysed across the full sample
For example, consider a hypothetical
study of 500 patients on warfarin, split
into two groups of standard 5 mg dose
versus clinico‐genomic adjustment, with
250 patients per group. Serious bleeding
involving death or hospitalisation
would be predicted to occur in as few
corresponding to only
five people on warfarin in each group.
Random variation of just two or three
people in either group due to chance
alone could therefore prevent statistical
detection of substantial reductions
in bleeding events. This problem is
further compounded when studies
attempt additional comparisons such
as the effect of clinical factors, making
the relevant group sizes even smaller.
Inadequate power has compromised
many of the research studies performed
to date, fueling the controversy in
As covered in Part 1, both the United
States Food and Drug Administration
(FDA) and the American Medical
Association (AMA) recommend that
genotype be considered along with
clinical factors when administering
12 Dosing regimens
that take both types of factors into
account have therefore been proposed
to provide more safe and effective
treatment for the patient.
Several studies have investigated this.
Gage and colleagues who developed a
‘clinico‐genomic’ algorithm combining
genetic and clinical factors for
1,015 participants and validated it
prospectively on a separate cohort of
15 In addition to genetic
factors, this study considered factors
such as height, weight, age, target INR,
related co‐morbidity and use of other
drugs (e.g. amiodarone, simvastatin).
Just over half (~55%) of the variability
in warfarin dosage was explained by
the combination of genetic and clinical
factors. Only ~20% of dose variability
was explained by clinical factors alone.
The algorithm arising from this study
is available at: www.warfarindosing.
org and can be accessed through
the Pharmacogenomics Knowledge
Base (PharmGKB – run by Stanford
University), which recommends it as the
best way to estimate the anticipated
stable dose of warfarin.
version of the algorithm provides
options for considering additional
genetic factors, ethnicity, race, baseline
and target INR, liver disease, statins,
azoles and certain antibiotics.
Following from the study described
above, the International Warfarin
(IWPC) conducted a larger study
which developed a clinico‐genomic
dose algorithm based on clinical and
genetic data from 4,043 patients and
validated prospectively on a further
The IWPC comprises
21 research groups from 9 countries and
4 continents. Again, the clinico‐genomic
algorithm was found to estimate the
appropriate initial therapeutic dose
of warfarin better than a fixed dose
or purely clinical algorithm alone.
This algorithm is also accessible through
PharmGKB and provides similar dose
recommendations to the algorithm
described in the previous paragraph.
Other studies have also supported
17,18 A prospective Swedish study
of 1,496 patients found that using
pharmacogenomics to guide warfarin
initiation provided better outcomes
for time in range and time to stable
anticoagulation than just considering
However, a setback occurred in late 2013
with the publication of three juxtaposed
reports in the New England Journal of
Medicine. One study found that dosing
based on a clinico‐genomic algorithm
was associated with a higher percentage
of time in the therapeutic INR range
than standard dosing for 455 European
patients during the first 12 weeks
after warfarin initiation.
the other two studies reported that
dosing did not improve anticoagulation
Figure 1. Patient’s response to warfarin
Up to 60% of a patient’s response to warfarin is
affected by known genetic factors and clinical
factors such as age, sex and weight. The other 40%
comprises unknown factors, but may be at least
partially attributed to interactions with other drugs
and with food.
Links Archive Australian Pharmacist May 2015 Australian Pharmacist July 2015 Navigation Previous Page Next Page