4 | DISCUSSION
This study describes our experience from the implementation of a 16-gene
PGx panel in routine clinical practice with a focus on clinical
relevance. The 16-gene PGx panel test was able to detect variants that
are clinically relevant according to the PHARMGKB classification in
100% of tested patients. More important, results of PGx testing led to
an actual change of medication or specific recommendations to do so in a
high proportion of tested patients. These adjustments of current
medication and specific recommendations regarding potential future
medication were supported by a PGx expert system and implemented through
personalized clinical pharmacology consultations.
Overall, frequencies of PGx variants shown in Figure 2 are in agreement
with previous studies in Caucasian populations [14-16]. The
detection rate of 100% for at least actionable variants is also not an
unexpected finding for a 16-gene PGx panel if one considers that in a
previous study even a panel with only 5 genes had a reported detection
rate of 99% [15]. Detection rates are typically based on the
PHARMGKB classification of clinical relevance, which may be considered
as the single best currently available PGx knowledgebase. SONOGEN XP
further enhances PGx clinical decision support through additional
reviews of other knowledgebases, thorough review of the original
literature, collaborations with external experts, and an array of
separate reports for different purposes. These range from concise
reports written for patients, over specific therapeutic recommendations
for prescribing physicians, to extensive summaries for experts of ten
and more pages including references to original research publications.
The very high detection rate of PGx panel tests for variants that are
classified as “required”, “recommended” or “actionable” support
the use of such multi-gene PGx panels with the automated interpretation
from expert systems for preemptive testing with the ultimate goal to
improve efficacy of pharmacotherapy, and to reduce adverse reactions and
costs [15, 17].
Furthermore, the experience reported in our study looks beyond PGx panel
tests with automated clinical decision support for PGx-based
pharmacotherapy and their merely theoretical impact on pharmacotherapy.
Whereas Table 2 lists a large number of PGx drugs for the identified PGx
variants including some that are hardly ever used (e.g. pimozide or
atazanavir), Table 3 provides a real-life insight into the prevalence of
specific drugs plus relevant PGx variants that required a change of
therapy in our patients. In our subpopulation of patients with a
specific indication for PGx testing and a median number of 6 concomitant
drugs we provided personalized clinical pharmacology consultations and
issued personalized expert recommendations to adjust therapy with the
PGx-triggering drug, current concomitant medication and potential future
medication. We recommended or, if the clinical pharmacologist was
directly involved in patient care, directly changed the PGx-triggering
drug in 32.4%, and any other concomitant medication as a “bycatch” in
22.5% of patients based on PGx panel results. This high value supports
the clinical relevance of PGx panels for actual clinical decision making
and, to our knowledge, has not been investigated in this way before.
Because additional costs of panel vs. single gene tests are moderate and
likely to further decrease with advancing technology and widespread use,
these findings further support the cost-efficiency of PGx panel testing
and provide an alternative view at traditional cost-benefit calculations
based on single drug-gene pairs.
However, a closer look also reveals that PGx-based management of
pharmacotherapy in real-life clinical practice is a complex process, and
that the standardized PHARMGKB classification can be highly
heterogeneous within the same class. For example, PGx testing for
clopidogrel and tamoxifen is merely classified as “actionable”
according to PHARMGKB. But the lack of efficacy associated with the
tested PGx variants is potentially lethal, and based on a review of the
latest evidence, PGx expert guidelines, as well as our own clinical
experience, we conclude that PGx testing indeed makes an important
contribution to clinical decisions related to those frequently
prescribed drugs and can even improve patient compliance [4-6,
18-20]. Furthermore, one must realize that most PGx variants do not
have a high predictive value for efficacy or adverse reactions of a drug
in individual patients. Rather, they act as one of several factors with
complex and often poorly understood interactions, and their effect may
be best described by a causative pie model [21]. Accordingly, our
clinical experience from PGx-supported clinical decision making also
taught us that PGx decision support algorithms are helpful, but that
they do not comprehensively capture the complexity of (shared) clinical
decision making. As shown in Table 1, we identified a considerable
number of patients with comedication inhibiting CYP2C19 or CYP2D6, or
renal impairment, and our therapeutic decisions considered all those
factors and their interactions with PGx variants, as well as alternative
therapeutic options. Indeed, the number of new drugs where the SmPC
includes information on PGx variants is steadily increasing. For
example, prescription of siponimod (Mayzent®) requires
preemptive CYP2C9 PGx testing, and the prescribing information of
bexpiprazole (Rexulti®) provides dosing
recommendations that consider both, PGx variants as well as concomitant
therapy with inhibitors of CYP2D6 or CYP3A4. And even for drugs that
have been marketed for a long time, postmarketing studies may identify
previously unknown relevant PGx variants [22]. Therefore, we expect
a growing demand for PGx testing with integrated expert consulting in
clinical pharmacology in the near future, also outside academic centres.
Some limitations of our study should also be addressed. Our study
population was selected, partially through physicians that referred
patients for specific drug-gene indications, and partially through
“mere” screening indications. Characteristics of our patients are
therefore transparently presented in Table 1, and one may consider that
those may be different in other institutions that offer PGx services.
Although our recommendations are a critical appraisal of clinical
relevance, we were not able to conduct a larger study with longitudinal
follow-up in order to evaluate outcomes of our PGx-based
recommendations. These must be addressed in prospective large controlled
studies for specific PGx-guided therapy [4, 20]. Nevertheless, we
were able to perform a separate analysis for our PGx consultations in
patients with clopidogrel therapy, and our results appear to be in line
with those studies [18]. Another limitation concerns the 16-gene
panel itself that we were able to use. Due to technical reasons this
panel did not include relevant HLA variants associated with severe
adverse reactions towards carbamazepine or abacavir [23, 24], but
from a medical point of view this would certainly be desirable.
In conclusion, our study demonstrates the value of PGx panel testing in
routine clinical practice and the valuable contribution of a PGx
clinical decision support system. Additional costs of panel vs. single
gene tests are moderate, and the efficiency of PGx panel testing
challenges traditional cost-benefit calculations based on single
drug-gene pairs. However, a closer look also reveals that truly
personalized pharmacogenetic medication management will not achieve its
full potential without individual patient consultations where additional
factors and individual weighing of risks vs. benefits and
pharmacotherapeutic as well non-pharmacotherapeutic care are considered.
Limited availability of experts and specialized clinics may become a
bottle neck for the implementation of PGx-guided pharmacotherapy, which
is a challenge but also an opportunity and responsibility for clinical
pharmacology and clinical pharmacy services to seek direct patient
contact and involvement in PGx-guided medication management.