This is a limited coverage policy for pharmacogenomics testing (PGx) including
single gene, multi-gene panels, and combinatorial tests. These tests are
generally covered (with a few exceptions) as described in further detail below
to improve safety in the use of specific medications by avoiding potentially
harmful medications, doses and/or adverse reactions known to occur with
certain genotypes.

PGx testing is considered reasonable and necessary in limited circumstances as
described below as an adjunctive personalized medical decision-making tool
once a treating clinician has narrowed treatment possibilities to specific
medications under consideration for use, or is already using a specified
medication, based on other clinical considerations including the patient's
diagnosis, the patient's other medical conditions, other medications,
professional judgment, clinical science and basic science pertinent to the
drug, and the patient's preferences and values.1

PGx tests must demonstrate analytical validity, clinical validity, and
clinical utility to be considered reasonable and necessary for coverage. This
is demonstrated through a required technical assessment of the test. PGx tests
are considered germline tests and must adhere to other relevant germline
testing policies published by this contractor.

It is understood that some panel/combinatorial tests may include content that
has demonstrated clinical utility and some that has not.  In such
circumstances, this contractor may provide coverage for the components of
tests that have demonstrated clinical utility when used in the proper clinical
context described below.

Clinical Indications

PGx tests are indicated when medications are being considered for use (or
already being administered) that are medically necessary, appropriate, and
approved for use in the patient's condition and are known to have a
gene(s)-drug interaction that has been demonstrated to be clinically
actionable as defined by the FDA (PGx information required for safe drug
administration) or Clinical Pharmacogenetic Implementation Consortium (CPIC)
guidelines (category A and B).

The selection of the medications in question must be derived from clinical
factors/necessity rather than from a PGx test. Once the putative therapeutic
agents are selected, and those agents are known to have gene-drug interactions
as identified above, then a PGx test may be considered reasonable and
necessary when the result of that test is necessary for the physician's
decision-making process regarding safely administering or dosing the drug.

PGx testing is **not** considered reasonable and necessary merely on the basis
of a patient having a particular diagnosis. Unless the record reflects that
the treating clinician has already considered non-genetic factors to make a
preliminary drug selection, PGx testing is not considered reasonable and
necessary.

This LCD does not address (provides neither coverage nor non-coverage
criteria) PGx testing for anticoagulation dosing, which is addressed by the
National Coverage Determination (NCD) 90.1.

_Definitions_

For the purpose of this LCD, the following terms are defined as follows:

Gene - the term "gene" in this document will be used as a term to encapsulate
all of the following: gene, pseudogene, and genetic locus.

Single-gene test - a laboratory test to detect relevant genetic variants
(alleles) of 1 gene. If two or more different single genes are ordered
individually but simultaneously, this is not a panel but rather a couple of or
multiple single gene tests.

Multi-gene panel - a laboratory test to detect genetic variants of at least 2
genes, wherein the clinician does not individually order genes, but orders a
panel with a specified list of genes.

Combinatorial PGx test - a type of multi-gene panel that requires a
proprietary algorithm to evaluate pharmacokinetic or pharmacodynamic
relationships resulting in drug recommendations or warnings.

Actionable use - A test is considered to have an actionable use when the
genotype information may lead to selection of or avoidance of a specific
therapy or modification of dosage of a therapy. The selection, avoidance, or
dose change must be based on the FDA-label for the drug, an FDA warning or
safety concern, or a CPIC level A or B gene-drug interaction. An intended
change in therapy based on the result of a genotyping test that is not
supported by one of these sources is not considered an actionable use for the
purposes of this LCD.

_Coverage information_

The clinical record must clearly show the use of or intent to prescribe a drug
that has known drug-gene interactions that require a PGx test to be ordered to
define the safe use of that drug in that patient.

If a treating clinician orders a single gene test or a test for a particular
allele(s), but as a matter of operational practicality, the laboratory tests
that single gene or allele on a platform that looks for variants in other
genes/alleles as well, that particular test done in that particular instance
is considered a single gene/allele test for coverage purposes. In this
scenario the provider may bill for the component of the test that was
reasonable and necessary (in this example, the single gene test).

A multi-gene panel is considered reasonable and necessary if more than one
single gene on that panel would be considered reasonable and necessary for
safe use of the medication in question or if multiple drugs are being
considered (each fulfilling the criteria of actionable gene-drug interactions
identified above) that have different relevant genes. Additionally, a gene
panel must contain at a minimum all the necessary relevant gene/allele content
required for their indicated use to meet clinical utility requirements. Such
minimum criteria are determined by experts including relevant associations
such as the Association for Molecular Pathology and are considered during the
technical assessment. A multi-gene panel is not considered reasonable and
necessary if only a single gene on the panel is considered reasonable and
necessary.

If two or more single genes are tested, rather than a multi-gene panel, then
the record must reflect that a clinician individually ordered each gene, and
each single gene must individually be reasonable and necessary at the time
they are ordered.

The ordering provider of a PGx test is restricted to providers who have the
licensure, qualifications, and necessary experience/training to both diagnose
the condition being treated and also to prescribe medications (the provider
must be able to do both) for the condition either independently or in an
arrangement as required by all the applicable state laws.

Test components that are not reasonable and necessary

Genes not identified as having actionable use are not considered reasonable
and necessary. The algorithms employed in combinatorial testing are also not
currently considered reasonable and necessary components of multi-gene
testing.

Technical requirements

The treating clinician receiving the laboratory report must be able to use the
genetic information presented to guide treatment. To accomplish this, the
laboratory must clearly report the clinical significance of the resultant
genotype, based on empirical data or validated methodologies, as an annotation
or interpretation. For clarity, the report should document the specific
genotype-drug interaction that lead to the resultant interpretation.

A lab may test for a reference allele as a matter of exclusion (e.g. report
that a patient has a reference allele when alternate alleles are not found).
However, in such cases, the report must identify which allele is the reference
allele and that the reference allele is reported as a matter of exclusion.

Noncovered Indications

PGx testing is not covered when a treating clinician is not considering
treatment with a medication that has an actionable drug-gene interaction, or
when the use of a medication with a drug-gene interaction is not reasonable
and necessary. __

Special Documentation Requirements

In order for any of the above services to be covered, the patient's medical
record must clearly reflect the following:

  1. The patient has a diagnosis for which pharmacologic therapy is reasonable and necessary, and the drug or drugs that the clinician is considering using must be reasonable and necessary for the treatment of the patient's diagnosis.
  2. The clinician has made an initial personalized decision for the patient based on the patient's diagnosis, the patient's other medical conditions, other medications the patient is taking, professional judgement, clinical science and basic science pertinent to the drug (e.g. mechanism of action, side effects), the patient's past medical history, pertinent family history, and the patient's preferences and values. 
  3. The provider performing the service must have a record of what drug(s) is/are being considered and for what indication(s) to ensure the test performed is reasonable and necessary. 

Background

With improvements in genetic technologies and the recognition that inter-
individual genetic differences may affect how patients metabolize or
physiologically respond to pharmacologically active substances, PGx testing
has been proposed as a way to personalize medication selection or dose based
on a patient's individual genes.2 The genes encoding the CYP2C19 and CYP2D6
proteins have emerged as having potential importance in the response
(therapeutic or adverse) to numerous medications.3-5 In addition combinatorial
PGx tests have emerged, which find polymorphisms in a number of genes
associated with pharmacologically important proteins.6,7

There is little question that such testing is now technically feasible, but
for a test to be reasonable and necessary there must be sufficient evidence
that it provides incremental information that changes physician management
recommendations in a way that improves patient outcomes.

An abundance of research on genes and alleles (variants) has been published.
To identify alleles and variants of importance, we reviewed FDA-approval
documents, guidelines, and subject matter expert input.

PharmGKB is a commonly referenced resource of PGx information, particularly in
following documented clinical validity and utility of relevant PGx biomarkers.
PharmGKB curators create clinical annotations for gene-drug interactions and
assign levels of evidence to the associations based on published evidence.8 As
an example, the database contains annotations regarding 102 drugs from 3
guidelines9 for drugs relevant to psychiatry, an area where PGx testing is
done routinely. CPIC is a common source of guidelines. This group has been
described by Dr. Annette Taylor10:

_CPIC is an NIH-funded organization with a membership of more than 300
clinicians, scientists, laboratorians, and others knowledgeable about
pharmacogenetics with the purpose of facilitating the use of pharmacogenetic
test results for patient care. CPIC 's goal is to address this (potential)
barrier by creating freely available, peer-reviewed, evidence-based, and
updatable gene/drug clinical practice guidelines. A CPIC Overview Presentation
can be found at https://cpicpgx.org/resources/._

_CPIC uses a rigorous and systematic system to grade levels of evidence, and
only gene/drug groupings with strong evidence for actionable prescribing are
selected for guideline development._

_CPIC guidelines help clinicians understand how to use available genetic test
results to guide prescribing.  _

At present, CPIC has 23 guidelines for the dosing and administration of 46
drugs based on gene-drug interactions.11 As part of this process, CPIC reviews
the clinical evidence for gene-drug interactions and assigns clinical utility
"levels" reflecting their confidence in the evidentiary basis for clinicians
to alter their drug administration or dosage. The CPIC levels are A, B, C, and
D. The process for this determination and the definition of each category are
demonstrated in the figure (attached to this LCD) and table below.12



**CPIC Level** | **Clinical Context** | **Level of Evidence** | **Strength of
Recommendation**  
---|---|---|---  
A | Genetic information should be used to change prescribing of affected drug
| Preponderance of evidence is high or moderate in favor of changing
prescribing | At least one moderate or strong action (change in prescribing)
recommended  
B | Genetic information could be used to change prescribing of the affected
drug because alternative therapies/dosing are extremely likely to be as
effective and as safe as non-genetically based dosing | Preponderance of
evidence is weak with little conflicting data | At least one optional action
(change in prescribing) is recommended  
C | There are published studies at varying levels of evidence, some with
mechanistic rationale, but no prescribing actions are recommended because (a)
dosing based on genetics makes no convincing difference or (b) alternatives
are unclear, possibly less effective, more toxic, or otherwise impractical or
(c) few published studies or mostly weak evidence and clinical actions are
unclear. Most important for genes that are subject of other CPIC guidelines or
genes that are commonly included in clinical or DTC tests | Evidence levels
can vary | No prescribing actions are recommended  
D | There are few published studies, clinical actions are unclear, little
mechanistic basis, mostly weak evidence, or substantial conflicting data. If
the genes are not widely tested for clinically, evaluations are not needed |
Evidence levels can vary | No prescribing actions are recommended  
  


The following are examples of genes that are commonly tested for gene-drug
interactions, and evidentiary review by CPIC have resulted in a level A or B
rating:

CYP2C9

The CYP2C9 protein has clinical significance in the metabolism of several
drugs including phenytoin (CPIC Level A).11,13 The recently FDA-approved drug
Mayzent, which is indicated for the treatment of multiple sclerosis, requires
CYP2C9 genotyping for dosing in accordance with the FDA prescribing
information.14 Since this LCD does not address PGx for warfarin dosing,
alleles and variants relevant to warfarin are not reviewed here. The following
alleles are both common and are believed to have clinical significance for
phenytoin dosing: *2, *3, *5, and *6, and a joint recommendation from the
Association for Molecular Pathology and the College of American Pathologists
has recommended that these variants be included as part of a CYP2C9 test.15
The *1, *2, and *3 alleles are necessary to safely dose the newly FDA-approved
drug Mayzent.14

CYP2D6

CYP2D6 is a clinically important enzyme in the metabolism of a large number of
medications and has CPIC level A or B gene-drug interaction and dosing
guideline.11 A number of particular alleles have been reviewed as having
actionable use including: *3, *4, *5, *6, *7, *10, *17, and *41, *1xN, and
*2xN. Drugs that may require _CYP2D6_ testing for safe administration include
iloperidone, clozapine, duloxetine, deutetrabenazine and valbenazine, among
others.

CYP2C19

CYP2C19 is a clinically important enzyme in the metabolism of a number of
selective serotonin reuptake inhibitors as well as tricyclic antidepressants
with a CPIC level A or B gene-drug interaction and dosing guideline11,13.
Recently published recommendations, including a report of the Association of
Molecular pathology, recommend the following alleles be included in testing as
a minimum based on clinical importance and population frequency: *2, *3,
*17.13,16

HLA testing

Several specific _HLA_ alleles are recommended for testing including some
relevant psychiatric medications.13 They include _HLA-B*15:02_ and
_HLA-A*31:01_. Both of these have level A or B gene-drug recommendations from
CPIC and are relevant to the use of carbamazepine and oxcarbazepine. Other
relevant variants in these genes include _HLA-B 57:01_ and _HLA-B 58:01_ ,
which are relevant to the use of abacavir and allopurinol.

For more information, the FDA has subsequently published a listing of gene-
drug interactions found in drug labels that should be considered when using
those medications.17

Subject Matter Panel and Contractor Advisory Committee (CAC) Meeting on June
26th, 2019

In order to get a better understanding of expert opinion of PGx testing and
CPIC guidelines, a panel of subject matter experts and Carrier Advisory
Committee (CAC) members from CGS, Wisconsin Physicians Services, Noridian, and
Palmetto GBA was convened on June 26th, 2019, via teleconference. While only
invited experts and CAC members could speak, interested members of the public
who registered could listen. The full recording is also available.18 Subject
matter experts on the panel included the list below. Included members may have
additional titles and positions to those listed.

Mary Relling, Chair, Pharmaceutical Dept. St. Jude Children's Research
Hospital

John Greden, Founder and Executive Director, University of Michigan
Comprehensive Depression Center

Annette Taylor, AVP, LabCorp, Co-Business Lead, Pharmacogenomics

Stuart Scott, Associate, Associate Professor, Department of Genetics and
Genomic Sciences, Icahn School of Medicine at Mount Sinai

The panel generally agreed that PGx testing has the ability to provide
clinically utile information that allows treating clinicians to select and
dose particular medications appropriately. PGx testing (presumably for genes
associated with pharmacokinetic pathways) was described as being analogous to
measuring renal function with a serum creatinine prior to dosing renally
cleared medications. The panel generally agreed that single gene testing and
multi-gene panels (as defined at the top of this LCD) have a role in
medication dosing and selection. The panel members did not specifically
recommend or support the use of any combinatorial PGx test or differentiate
one over another. There was general agreement that combinatorial PGx tests
with a proprietary algorithm not available for public review required
independent evidence establishing their validity and utility. Additionally, a
comment was made that _CYP2C19_ and _CYP2D6_ testing would most likely be the
appropriate comparator in a clinical study to determine if a combinatorial PGx
test provides information that improves outcomes more than single gene or
multi-gene panels.

A CAC member commented that PGx testing is becoming increasingly common, and
it should not be restricted by provider type.

Additional Expert Input from the CAC

In addition to the panel, a number of experts who were unable to attend
provided written correspondence. These included the following:

John Logan Black, Co-Director, Personalized Genomics Laboratory, Department of
Laboratory Medicine and Pathology, Mayo Clinic

To summarize, Dr. Black's comment generally agreed with the comments of the
panel. He indicated support for the use of genetics in guiding pharmacologic
treatment, and in referencing guidelines from CPIC and the FDA. He also
provided references to a number of peer-reviewed studies which have been
reviewed in this LCD. As regards combinatorial testing, he noted that evidence
does support their use, though he also noted that it "is unclear whether the
power of combinatorial PGx is driven by a few genes or if it is absolutely due
to the combinatorial effects." While it was not discussed by the panel, a
manuscript (describing the GUIDED study) submitted by Dr. Black did a
retrospective comparison (using statistical modelling rather than a direct
comparison) of GeneSight to single gene testing.19 This study suggested that
combinatorial testing predicts poor antidepressant response and outcomes
better than single gene testing. Two gene panels were not considered.

He indicated that for panel testing, he would recommend a minimum panel in
psychiatry consisting of the genotypes of _CYP2C9, CYP2C19, CYP2D6,
HLA-A*31:01_ and _HLA-B*15:02_.

Jose DeLeon, Professor, Psychiatry, University of Kentucky

Dr. de Leon's comments largely agree with the panel's comments as well, though
he specifically noted the clinical utility of HLA-B*15:02 in any patient of
Asian ancestry before starting carbamazepine, and for _CYP2D6_ and _CYP2C19_
for some antidepressants and some antipsychotics. Additionally, Dr. de Leon
also indicated his belief that the evidence did not support the use of
GeneSight. Notably, he indicated the importance of _CYP2D6_ and _CYP2C19_ and
questioned the testing of other CYP genes. He also noted that the GUIDED study
(reviewed above) "further demonstrated that the study results were negative,
and the authors had to use secondary outcomes to try to demonstrate that a
negative study had positive results."

Bruce Cohen - Director of the Program for Neuropsychiatric Research at McLean
Hospital and Harvard Medical School

Dr. Cohen voiced concern for the use of PGx testing in drug selection. He
noted that the FDA has published a document raising concerns about PGx testing
for general use in psychiatry.20 The document notes: "...the relationship
between DNA variations and the effectiveness of antidepressant medication has
never been established.'' It goes on to state as a recommendation to
providers:

_If you are using, or considering using, a genetic test to predict a patient's
response to specific medications, be aware that for most medications, the
relationship between DNA variations and the medication's effects has not been
established._

However, the document also notes:

_There are a limited number of cases for which at least some evidence does
exist to support a correlation between a genetic variant and drug levels
within the body, and this is described in the labeling of FDA cleared or
approved genetic tests and FDA approved medications. The FDA authorized labels
for these medical products may provide general information on how DNA
variations may impact the levels of a medication in a person's body, or they
may describe how genetic information can be used in determining therapeutic
treatment, depending on the available evidence. 18 _

A manuscript examining the metascience of PGx testing and providing an
accompanying viewpoint reviewed 10 clinical studies of PGx in psychiatry and
found that none of them were blinded and used a protocol-based comparison.21
The authors point to two evidence-based protocols that are freely available
and could have been used, STAR*D and the Texas Medication Algorithm Project.
As the authors state early on:

_Simply put, MDD [Major Depressive Disorder] is determined by a large number
of genes, and, except in rare cases, no single gene or limited gene set, even
those for drug metabolism and drug targets, determines more than a few percent
of the risk of illness or course of treatment._

The STAR*D study included 2,876 subjects with major depressive disorder from
multiple institutions.23-24 In this study all participants started with
citalopram as the initial treatment and may have advanced through additional
levels of treatment up to level 4. If a subject did not respond at a given
level, that subject was then advanced to the next level of treatment, which
included alternative treatments instead of or in addition to the treatment the
patient was on.

Cohen suggests that PGx tests offer no clear clinical value over freely
available and well-established protocols for drug selection with a reference
to a number of recent documents.20,21 He also suggests that, should a
clinician be unsure about drug choice, a psychiatry consultation costs
substantially less money than PGx testing.

_Additional comments of support_

This contractor received numerous comments on this proposed policy. Of note,
we received letters of support for coverage of PGx testing as described in
this policy by prominent associations including the Association for Molecular
Pathology, the College of American Pathologists, and the American Psychiatric
Association.

_Evidence for the utility of combinatorial PGx testing_

A review of the available evidence found five combinatorial PGx tests for
which outcome data has been published. These studies focus on testing for drug
selection for psychiatric and neurological use, and include tests such as
CNSDonse, Genecept, Neuropharmagen, Genesight, and NeuroIDGenetix.

A review of the published clinical studies performed demonstrated that,
despite showing some promising findings, these studies had several
shortcomings in that they failed to meet their primary endpoints,25-28 were
not representative of the Medicare population,29-32 or had other significant
shortcomings such as a possible biased sample population.26,29-31,33

Some of these studies yielded interesting observations, for example, Tanner et
al34 that demonstrated that greater improvement in treatment success was seen
by primary care providers using a combinatorial PGx test than compared to
psychiatrists who did not see a significant benefit, although there was no
difference identified between the psychiatrist-treated and primary care
treated groups. Many of these studies saw differences in performance from
using these genetic tests vs. standard of care with the limitations noted
above.

We found two meta-analyses of combinatorial PGx with overlap in the studies
reviewed, the statistical techniques, and the results. Both meta-analyses
included studies that are cited above. All the tests studied in these meta-
analyses included _CYP2D6_ and _CYP2C19_. Both pooled data using a random
effects model. The meta-analysis published by Rosenblatt, Lee, and McIntyre,35
pooled the results of 6 studies and found a pooled relative risk for treatment
remission of 1.71 in favor of PGx testing, and a relative risk of 1.36 for
remission, also favoring testing. A more recent meta-analysis by Bousman et
al36 included 5 studies and found a pooled relative risk for treatment
remission of 1.74 in favor of PGx testing. A pooled relative risk for response
was not reported. Both of these meta-analyses found a high level of
heterogeneity, and the paper by Rosenblatt, Lee, and McIntyre suggested that
this makes it difficult to assume that there is a class effect. Additionally,
because combinatorial PGx tests rely on many of the same PGx biomarkers tested
in single and multi-gene PGx tests, it has been postulated based on an
observational study utilizing GeneSight that there may be little gained from
the proprietary algorithms in these tests above single and multi-gene
panels.37 It should be restated here that our CAC experts were consistent in
their lack of support for the use of combinatorial PGx and cited similar
questions; additional comments received from societies such as the Association
for Molecular Pathology, the College of American Pathologists, and the
American Psychiatric Association similarly stated that the validity and
utility of combinatorial testing has not been demonstrated. Of note, a more
recent review submitted by the APA concludes that "there is insufficient
evidence to support widespread use of combinatorial pharmacogenetic decision
support tools at this point in time" and noted that "a high level of evidence
has been achieved only for the cytochrome P450 genotype data".38

We implemented numerous levels of evidence in the hierarchical framework of
Fryback and Thornbury39 and utilized the ACCE Model Process for Evaluating
Genetic Tests in this policy.40

When a physician is treating a patient for a particular diagnosis, there are
often many available treatment options. The physician may go through a series
of decisions and use numerous sources of information, including evidence,
professional judgement, and patient values and preferences to narrow down the
treatment approach from an array of potential treatments to the selection of a
specific treatment or course of treatment. The optimal medication for a
particular patient is a decision to be made by the physician and patient. The
evidence reviewed by this contractor clearly suggests that PGx testing has the
ability to predict how a patient will metabolize a number of specific drugs,
and some evidence suggests that this can be used as a tool for safe drug
administration. The putative clinical utility of PGx testing comes from the
ability to link genotype to phenotype and then to link phenotype to medication
selection (which may include avoidance) or medication dosing. There appears to
be general agreement within the scientific community that for some alleles of
some genes there is a clear phenotype, and that the phenotype has an
established interaction with particular drugs. There also appears to be
supporting evidence (including guidelines) that specific medication selection
decisions (including dosing and avoidance) may be made based on genotypes and
phenotypes. The CPIC level categorization process, as reviewed, follows a
similar evidentiary process for evaluating clinical utility as used by this
contractor, and similar to other expert organizations, carries weight in its
findings with surveyed experts in the field. When employed in the proper
clinical context, following FDA labels and/or CPIC Level A and B grading are
likely to improve clinical outcomes by avoiding unsafe medications or doses
based on genotype-drug interactions that are clearly described.

Since the medical necessity for testing a gene in PGx can only come from the
ability of that test to inform a management decision based on a gene-drug
interaction, a test for a specific gene or allele is not reasonable and
necessary unless and until a clinician is considering using a drug that has an
interaction with a specific gene or allele. Once this initial decision has
been made it may be reasonable and necessary to test for that allele or that
gene. If a clinician is not considering using a medication with an interaction
with a gene being tested, or if the patient who is being tested is unable or
unwilling to use a medication interacting with the gene or allele being
tested, then there is no benefit to the patient to run a test of that gene or
allele.

It should be pointed out, however, that there are several remaining
uncertainties in the evidence.

While there are some large PGx studies, we are not aware of large high-quality
studies that used a clear evidence-based prescribing approach in the control
arm. As a number of prominent psychiatrists with expertise in the biological
underpinnings of mental health have pointed out, it is not clear that PGx
testing is a better tool for drug selection than using a standardized
evidence-based protocol which does not rely on genetics, or a consultation
from a knowledgeable provider. Moreover, psychiatric conditions wherein a lot
of PGx testing is performed have significant complexity involving many genes
and factors outside of PGx. As such, while the evidence does suggest that PGx
testing can be used to refine the selection of a medication or dose, there is
not sufficient evidence to suggest that PGx is reasonable and necessary for
the initial selection of potential medications to treat a patient.

_Combinatorial PGx testing_

Because these tests leverage many of the same biomarkers already discussed
above and because these tests are defined by the proprietary algorithms
required to associate pharmacokinetic and pharmacodynamic events, this
contractor has determined that the evidentiary review of clinical validity and
utility of these tests should be demonstrated beyond the capability of single
gene and multi-gene panel information already evaluated and established. The
algorithms themselves (or more than the sum of the FDA and CPIC Level A and B
biomarker information) must establish validity and utility to have independent
value to establish coverage. Based on our review of the evidence and on expert
feedback submitted both during the CAC meeting and during the comment period
for this policy, it's been determined that there are insufficient data to
support coverage for any combinatorial test. This conclusion was also reached
by the CAC committee members and professional societies whom all agreed that
the combinatorial component of panel tests have not to date demonstrated
independent value. However, it should also be noted that combinatorial tests
are a subtype of multi-gene PGx tests, and there may be components within
those tests that are necessary and reasonable and thus may be covered.

This policy does not restrict use of PGx testing to provider type. While it is
possible that specialists in mental health or PGx are more likely to be aware
of a potential gene-drug interaction in medications used to treat mental
illness, the data reviewed above support the conclusion that the actionability
of the resultant information is not dependent on who submits the order. This
conclusion is in keeping with the CAC discussion held on June 26th, 2019,
which, together with written comments submitted during the comment period,
communicated a high degree of agreement among discussants and commenters that
there is not a reason to limit the coverage by provider type.

In summary, the present evidence does not clearly demonstrate that routine PGx
testing for the purpose of medication selection offers a benefit over
selection of medications based on contemporary evidence-based medication
selection protocols. However, there are clear biological pathways driven by
specific genes which may affect concentrations of a drug that a patient
experiences, including drugs that are components of evidence-based protocols.
As such, when a clinician is specifically considering using a drug, because a
clear evidence-base or individualized factors make it one of the most
appropriate potential treatments, and that medication has a clinically
important drug-gene interaction, the evidence suggests that testing the gene
can help refine that initial medication selection by avoiding an unsafe or
ineffective medication or by leading to a change of dose.