Medical Policy

 

Subject: Genotype Testing for Genetic Polymorphisms to Determine Drug-Metabolizer Status
Document #: GENE.00010 Publish Date:    02/28/2018
Status: Reviewed Last Review Date:    01/25/2018

Description/Scope

This document addresses genotype testing for polymorphisms which can identify variants of specific genes associated with abnormal and normal drug metabolism.  The use of such testing is based on the theory that individuals with certain gene variants may potentially be able to receive higher or lower doses of some drugs, or should avoid some drugs altogether, to improve the likelihood of achieving clinical goals as well as lessening the risk of adverse drug effects.

Note: Testing for thiopurine methyltransferase (TPMT) for individuals receiving treatment with azathioprine or 6-mercaptopurine therapy, and testing for NS3 Q80K for individuals being treated for Hepatitis C virus are NOT addressed on this document.

Note: For additional information regarding pharmacogenomics, please see:

Position Statement

Medically Necessary:

Genotype testing for genetic polymorphisms of Human Leukocyte Antigen B*1502 (HLA-B*1502) to determine the drug-metabolizer status of individuals for whom the use of carbamazepine is being proposed is considered medically necessary when the criteria below have been met:

  1. The individual is of Asian descent; and
  2. There are no other alternatives to the use of carbamazepine.

Genotype testing for identification of the CYP2C19 variant of Cytochrome P450 is considered medically necessary to determine the drug-metabolizer status of individuals who meet either of the following criteria:

  1. The individual is currently undergoing treatment with clopidogrel and has not been tested: or
  2. The use of clopidogrel is being proposed.

Genotype testing for Human Leukocyte Antigen B (HLA-B*5701) is considered medically necessary before beginning treatment with abacavir (Ziagen®) for persons infected with HIV-1.

Genotype testing for identification of the CYP2D6 variant of Cytochrome P450 to determine the drug-metabolizer status of individuals being considered for treatment with eliglustat (Cerdelga) is considered medically necessary.

Genotype testing for identification of the CYP2D6 variant of Cytochrome P450 to determine the drug-metabolizer status of individuals with Huntington’s disease being considered for treatment with a dosage of tetrabenazine (Xenazine®) greater than 50 mg per day is considered medically necessary.

Investigational and Not Medically Necessary:

Genotype testing for genetic polymorphisms for individuals who potentially may receive the drugs mentioned above is considered investigational and not medically necessary when the criteria or circumstances detailed above are not met.

Genotype testing for genetic polymorphisms to determine drug-metabolizer status is considered investigational and not medically necessary in all other circumstances, including but not limited to:

  1. Individuals initiating therapy with the following drugs:
    1. 5-fluorouracil (5-FU); or
    2. Antidepressants or antipsychotics; or
    3. Irinotecan; or
    4. Opioids and narcotics; or
    5. Phenytoin; or
    6. Tamoxifen; or
    7. Warfarin.
  2. Analysis of the following enzymes:
    1. Cytochrome P450 (including CYP2C9) [except where noted above]; or
    2. Dihydropyrimidine dehydrogenase (DPYD); or
    3. Leukocyte Antigen B*1502 (HLA-B*1502) [except where noted above]; or
    4. Thymidylate synthetase (TYMS); or
    5. Uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1); or
    6. Vitamin K epoxide reductase subunit C1 (VKORC1).

The use of testing panels for genetic polymorphisms to determine drug-metabolizer status is considered investigational and not medically necessary unless all components of the panel have been determined to be medically necessary based on the criteria above.  Individual components of a panel may be considered medically necessary when criteria above are met. Examples of such panels include but are not limited to the following:

  1. AIBioTech® CardioloGene Genetic Panel
  2. AIBioTech® Pain Management Panel
  3. AIBioTech® PsychiaGene Genetic Panel
  4. AIBioTech® Urologene Panel
  5. DrugMEt™
  6. Genecept™ Assay
  7. GeneSight® Analgesic
  8. GeneSight® Psychotropic
  9. GeneSight® ADHD
  10. Millennium PGTSM
  11. PHARMAchip
  12. Proove® Drug Metabolism test panel
  13. Proove® Narcotic Risk test panel
  14. SureGene Test for Antipsychotic and Antidepressant Response (STA2R).
Rationale

Current evidence regarding the use of genotyping tests for the determination of drug metabolizer status indicates that while available testing methods may accurately identify genetic variations in an individual, there is insufficient data to demonstrate that such testing, and the clinical decisions made based on the testing, result in a significant impact on health outcomes.  Specifically, clinical trials have not yet adequately demonstrated that such testing results in either enhanced clinical effectiveness or in decreased short-term or long-term serious adverse events.

Recently, the U.S. Food and Drug Administration (FDA) added language to the labels of many approved drugs to include pharmacogenomic information.  Wang and colleagues (2014) published a study evaluating the evidence that supports pharmacogenomic biomarker testing in drug labels and how frequently testing is recommended.  Their analysis found that of the 119 drug-biomarker combinations identified, only 43 (36.1%) had labels that provided convincing clinical validity evidence supporting pharmacogenomic testing related to a specific drug.  Furthermore, only 18 (15.1%) provided convincing evidence of clinical utility.  Recommendations about how clinical decisions should be based on the results of a biomarker test were made on 61 labels (51.3%); but only 36 (30.3%) of these contained convincing clinical utility data.  A full description of the supporting studies for these recommendations was included in 13 labels (10.9%).  The authors found that less than one-sixth of drug labels contained or referenced convincing evidence of clinical utility of biomarker testing, whereas more than half of the labels made recommendations based on biomarker test results.  They concluded that it may be premature to include biomarker testing recommendations on drug labels when convincing data that links testing to health outcomes does not exist.

Critical elements of assessing the effectiveness of such genetic tests include: (1) analytic (diagnostic) validity; (2) clinical validity; and (3) clinical utility.  Analytic validity measures the technical performance of the test, in terms of accurately identifying the genetic markers to be measured.  Clinical validity measures the strength of association between genetic test results and clinical parameters such as dose, therapeutic efficacy, or adverse events.  Clinical utility, the ultimate goal of genetic testing, measures the ability of the test to improve clinical outcomes, such as whether prescribing or dosing based on information from genetic testing improves therapeutic efficacy or adverse event rate as compared with treatment without genetic testing.

Therefore, when considering whether or not a test to determine drug metabolizer status is appropriate in the treatment of individuals prescribed certain medications, specific issues need to be evaluated, including:

Carbamazepine

There has been investigation into the role of HLA-B*1502 mutations in the occurrence of toxic epidermal necrolysis (TEN) and Stevens-Johnson syndrome in ethnic Han Chinese individuals receiving treatment with the anticonvulsant drug carbamazepine (CBZ).  A molecular study by Hung et al. (2006) identified this genetic variation as a contributor to this reaction.  Based on data reviewed by an expert panel, the FDA decided to place a black-box warning on the label of carbamazepine as follows:

Serious and sometimes fatal dermatologic reactions, including toxic epidermal necrolysis (TEN) and Stevens-Johnson syndrome (SJS), have been reported during treatment with carbamazepine. These reactions are estimated to occur in 1 to 6 per 10,000 new users in countries with mainly Caucasian populations, but the risk in some Asian countries is estimated to be about 10 times higher. Studies in patients of Chinese ancestry have found a strong association between the risk of developing SJS/TEN and the presence of HLA-B*1502, an inherited allelic variant of the HLA-B gene. HLA-B*1502 is found almost exclusively in patients with ancestry across broad areas of Asia. Individuals with ancestry in genetically at risk populations should be screened for the presence of HLA-B*1502 prior to initiating treatment with carbamazepine. Patients testing positive for the allele should not be treated with tegretol unless the benefit clearly outweighs the risk.

Chen and colleagues (2001) conducted a study of 4877 carbamazepine-naïve subjects who were genotyped for the HLA-B*1502 allele.  B*1502 allele-positive subjects were given an alternative medication while negative subjects were treated with carbamazepine.  The authors then compared the incidence of SJS and TEN in the study population to historical controls.  Results demonstrated that a mild, transient rash developed in 4.3% of B*1502 positive subjects; more widespread rash developed in 0.1% of subjects, who were hospitalized.  SJS/TEN did not develop in any of the HLA-B*1502–negative subjects receiving carbamazepine.  In contrast, the estimated historical incidence of carbamazepine-induced SJS/TEN (0.23%) would translate into approximately 10 cases among study subjects (p<0.001).  

Other genetic mutations have also been investigated as having clinical impact on the outcomes of individuals who may undergo treatment with carbamazepine.  McCormack and others (2011) described a study investigating the association of the HLA-A*3101 allele and the incidence of carbamazepine-related complications. This study included 65 subjects who had experienced carbamazepine-related complications and 3987 control subjects.  An independent genome-wide association study demonstrated a significant association between subjects with the HLA-A*3101 allele and the incidence of carbamazepine-induced hypersensitivity reactions among subjects of Northern European ancestry.  Further study is warranted to understand the impact of genetic testing on the rate of occurrence of complications in subjects carrying the HLA-A*3101 allele.  He and colleagues (2014) investigated the impact of several genes on the development of SJS in a population of 225 ethnic Han Chinese subjects (n=25 with SJS, 200 non-SJS controls) who had been exposed to carbamazepine.  They observed statistically significant differences in EPHX1 c.337T>C polymorphisms between SJS group subjects and controls in terms of allelic and genotypic frequencies (p=0.011 and p=0.007, respectively).  They stated that the C allele and the C-G diplotype of EPHX1 may play important roles in increasing the risk of CBZ-SJS/TEN development (odds ratio [OR], 0.478; p=0.011; OR, 0.21; p=0.025, respectively).  No significant associations were reported between ABCB1, CYP3A4, EPHX1, FAS, SCN1A, MICA or BAG6 genes and carbamazepine dose, or dose-adjusted concentration in carbamazepine-tolerant subjects.

Clopidogrel

Recent focus has been placed on the impact of drug metabolizer status testing for individuals prescribed clopidogrel.  Several published nonrandomized, controlled studies addressed the use of testing for genetic variants in CYP4502C19, ABCB1, CYP2A5, and P2RY12 (Collet, 2009; Mega, 2009; Simon, 2009).  These studies found that mutations in these genes, especially CYP2C19 variants, have significant effects on cardiovascular health outcomes.  Mega and colleagues (2009) conducted a study addressing the impact of CYP-450 gene variants on clinical response to clopidogrel treatment.  This study included 162 healthy subjects and 1477 subjects with acute coronary disease being treated with clopidogrel.  Carriers of at least one CYP2C19 allele had a 32.4% reduction in the active metabolite of clopidogrel, a 9% decrease in maximal platelet aggregation response, a 300% increase in the risk of stent thrombosis (ST), and relative increase of 53% in the composite primary efficacy outcome of the risk of death from cardiovascular causes, myocardial infarction, or stroke, as compared with non-carriers.

A study by Simon and others (2009) enrolled 2208 subjects with acute myocardial infarction (MI) who were receiving clopidogrel therapy.  The authors reported a significantly increased risk of adverse cardiovascular events in individuals with CYP2C19 variants when compared to those with no mutations (21.5% vs. 13.3%).  Among the 1535 participants who also underwent percutaneous coronary intervention during hospitalization, the rate of cardiovascular events among individuals with two CYP2C19 loss-of-function (LOF) alleles was 3.58 times the rate among those with none.

In March 2010, the FDA announced that it was requiring a black-box warning on the label of clopidogrel that addresses the use of pharmacogenetic testing. The warning has four specific points:

Mega and colleagues published the findings of a large meta-analysis conducted in 2010.  This report included 9685 subjects who were treated with clopidogrel in nine studies. The findings indicated that subjects with one or two LOF CYP2C19 alleles had a significantly increased risk of composite endpoint events (hazard ratio [HR], 1.55; p=0.01; HR, 1.76; p=0.002, respectively).  Additionally, these subjects had an increased risk of stent thrombosis when compared to non-carriers of LOF alleles.

A study by Simon and colleagues (2011) involved 2210 subjects being treated for acute MI who were genotyped for CYP2C19 polymorphisms.  They reported that the presence of two CYP2C19 LOF alleles was significantly associated with the risk of in-hospital death and major myocardial events at 1 year for individuals with acute MI (adjusted odds ratio 6.67) and those undergoing percutaneous coronary interventions (PCI) (adjusted odds ratio 6.87).  They also investigated the association of PON1 polymorphism with major myocardial events, but reported that no statistically significant association was found.

Mega and others (2011) conducted a randomized double-blind trial that enrolled 333 subjects with cardiovascular disease who were genotyped for CYP2C19*2 LOF allele status.  Non-carriers of the allele received either 75 mg or 150 mg daily dose of clopidogrel in one of two blinded 28-day long blocks.  Carriers of the CYP2C19*2 allele received 75 mg, 150 mg, 225 mg, or 300 mg doses of clopidogrel in a blinded sequence of four 14-day long blocks.  For the 75 mg dosage, both CYP2C19*2 hetero- and homozygotes had significantly higher on-treatment platelet reactivity than non-carriers (p<0.001 for both groups).  Higher doses of clopidogrel in CYP2C19*2 heterozygotes significantly reduced the proportion of non-responders to 10% in both 225 mg (8 of 75 subjects, p<0.001) and 300 mg (7 of 73 subjects, p<0.001).  In CYP2C19*2 homozygotes, higher doses of clopidogrel did not provide similar benefits, with 80% of this group being non-responders at 75 mg and 60% still being non-responders at the 300 mg dosage.  The authors reported that in CYP2C19*2 heterozygotes, a dose of 225 mg provided similar platelet reactivity scores to that found with non-carriers receiving a 75 mg dose.  In CYP2C19*2 homozygotes, not even the 300 mg dose provided equivalent platelet reactivity to non-carriers.  There were no deaths, cerebrovascular events, or Thrombolysis in Myocardial Infarction (TIMI) major or minor events reported in either group at any dose level.  This study provides significant evidence to demonstrate that CYP2C19*2 guided dosing of clopidogrel can provide significant benefits in platelet reactivity measures.  Further data would be helpful in determining if this also results in significant health outcomes in terms of decreased cardiovascular disease-related deaths and complications.

Sibbing and colleagues (2009) published the results of a case series study of 2485 subjects undergoing coronary stent placement after pre-treatment with 600 mg of clopidogrel.  Genotyping of all subjects was conducted and the results found that 805 subjects (73%) were CYP2C19 wild-type homozygotes and 680 subjects (27%) carried at least one *2 allele.  The authors reported that cumulative 30-day incidence of stent thrombosis was significantly higher in CYP2C19*2 allele carriers vs. wild-type homozygotes (HR=3.81; p=0.007).  The risk of stent thrombosis was highest (2.1%) in subjects with the CYP2C19 *2/*2 genotype (p=0.002).  The authors concluded that CYP2C19*2 carrier status is significantly associated with an increased risk of ST following coronary stent placement.

This group published another study in 2010 (Sibbing, 2010) involving 1524 subjects undergoing percutaneous coronary intervention after pretreatment with 600 mg clopidogrel.  Genotyping for CYP2C19*17 allelic variant and adenosine diphosphate (ADP)-induced platelet aggregation were assessed.  For both heterozygous (n=546) and homozygous (n=76) *17 allele carriers, significantly lower ADP-induced platelet aggregation values were found vs. wild-type homozygotes (n=902; p=0.039 and p=0.008, respectively). Furthermore, CYP2C19*17 allele carriage was found to be significantly associated with an increased risk of bleeding, with the highest risk observed for CYP2C19*17 homozygous subjects (p=0.01).  A multivariate analysis confirmed the independent association of CYP2C19*17 allele carriage with platelet aggregation values (p<0.001) and the occurrence of bleeding (p=0.006).  However, no significant influence of CYP2C19*17 was detected in relation to the incidence of stent thrombosis (p=0.79).  The authors concluded that CYP2C19*17 carrier status is significantly associated with enhanced response to clopidogrel and an increased risk of bleeding.

The results of two large placebo-controlled, randomized controlled trials (RCTs) were published by Pare et al. (2010).  The two studies included a total of 5059 subjects randomized to receive either clopidogrel or placebo and followed for the occurrence of primary and secondary composite outcomes.  The authors concluded that “no significant difference in the effect of clopidogrel treatment on clinical outcomes was observed when subjects were stratified according to metabolizer status.”  However, some increase in efficacy was seen in subjects with gain-of-function alleles in terms of reduced ischemic events.

In 2011, three meta-analyses were published looking at the health-related outcomes of CYP2C19 genotype testing for individuals receiving clopidogrel.  One of these reported that CYP2C19*2 carrier status was significantly associated with increased risk of cardiovascular events.  The other two found no such benefit.

The first study, by Jin and colleagues, included a total of eight prospective cohort studies including 2345 subjects carrying the CYP2C19*2 LOF allele and 5935 wild-type controls.  The authors reported that the summary odds ratio demonstrated a statistically significant association in increased cardiac mortality (p=0.007), myocardial infarction (p=0.002), and stent thrombosis (p=0.0001).  However, while these findings point to a major role of the CYP2C19 allele in the incidence of major cardiovascular events, the study itself was comparatively small and did not include any RCT data.

In the second study, Bauer et al. looked at the data collected in 15 studies encompassing 28,368 subjects.  They found the random effects summary odds ratio for stent thrombosis in carriers of at least one CYP2C19 LOF allele vs. non-carriers was 1.77 (p<0.001).  However, the authors note that this finding is subject to significant small study bias and replication diversity.  When adjusted for these factors, the significance of this finding was nullified. Furthermore, the odds ratio for major cardiovascular events and stent thrombosis was likewise non-significant.  The overall quality of the epidemiological evidence reviewed was graded as low, and the authors’ conclusion was that “… at the current state of accumulated information, there is no sufficiently robust and consistent evidence that CYP2C19 represents a strong susceptibility gene modifying the clinical efficacy of clopidogrel.”

The third meta-analysis was published by Holmes and others and included 32 studies encompassing 42,016 subjects.  Six of the included studies were RCTs.  As with the Bauer study previously discussed, this study concluded that “this systematic review and meta-analysis does not demonstrate a clinically important association of genotype with cardiovascular outcomes with the possible exception of stent thrombosis.”  The report stated that when statistically significant analyses were re-run with only studies that included greater than 200 subjects, the original statistically significant findings were nullified.  The authors concluded that significant small study bias existed in the body of evidence.  This is supported by positive results of the Harbord test for small study bias (p=0.001).  The authors also state that selective outcome reporting and genotype misclassification errors impair the available evidence.

Mao (2013) reported a meta-analysis of 21 studies involving 23,035 subjects.  They reported that compared with non-carriers of the CYP2C19 variant allele, carriers were found to have an increased risk of adverse clinical events (OR=1.50; p=0.0003), myocardial infarction (OR=1.62; p<0.00001), stent thrombosis (OR=2.08; p<0.00001), ischemic stroke (OR=2.14; p=0.001) and repeat revascularization (OR=1.35; p=0.004), but not of mortality (p=0.500) and bleeding events (p=0.930).  They concluded that the presence of the CYP2C19 polymorphism is significantly associated with risk of adverse clinical events in clopidogrel-treated subjects.

In 2014, Sorich and others reported the results of a meta-analysis of 24 studies with ≥ 500 participants involving 30,076 subjects, investigating the effects of the CYP2C19 genotype on clopidogrel effectiveness.  Data was stratified by the predominant clopidogrel indication (percutaneous coronary intervention [PCI] versus non-PCI) and ethnic population (white versus Asian) of each primary study.  The association between carriage of more than one CYP2C19 LOF allele and major cardiovascular outcomes differed significantly (p<0.001) between studies of whites not undergoing PCI (relative risk [RR], 0.99; n=7043), whites undergoing PCI (RR, 1.20; n=19,016), and Asians undergoing PCI (RR, 1.91; n=10,017).  Similar differences were identified in secondary analyses of two CYP2C19 LOF alleles, stent thrombosis outcomes, and studies with ≥ 200 participants.  The conclusions stated that the reported association between CYP2C19 LOF allele carriage and major cardiovascular outcomes differs based on the ethnic population of the study and, to a lesser extent, the clopidogrel indication.  This is potentially of major importance given that over 50% of Asians carry at least one CYP2C19 LOF allele.

In 2015, Osnabrugge published a systematic review and critical assessment of 11 overlapping meta-analyses that involved 30 primary studies that addressed the association between CYP2C19 loss-of-function alleles and clinical efficacy of clopidogrel.  Of the 11 meta-analyses, eight reported statistically significant associations, with mean effect size ranging from 1.26 to 1.96.  Of those eight studies, five reported associations between the presence of loss-of-function polymorphisms and clinical endpoints, and the other three reported no statistically significant pooled effect or could not pool data to a high degree of heterogeneity.  The four studies concluding no association were the most recently published.  All 11 studies reported a statistically significant association with CYP2C19 LOF alleles and stent thrombosis with mean effect size 1.77 to 3.85.  The authors reported that all included meta-analyses reported significant heterogeneity, which was handled in significantly different manners.  Publication bias was assessed in nine of the 11 meta-analyses included; six concluded that some publication bias was present and two did not find evidence of bias.  The remaining study provided a funnel plot, but no discussion of the data.  The authors concluded that meta-analyses on the association between CYP2C19 loss-of-function alleles and clinical efficacy of clopidogrel differed widely with regard to assessment and interpretation of heterogeneity and publication bias.

Doll and colleagues (2016) reported the results of a study involving 2236 subjects receiving clopidogrel or prasugrel, investigating the association of CYP2C19 metabolizer status (extensive vs. reduced) and their primary endpoints of cardiovascular death, MI, or stroke.  They reported finding no association between CYP2C19 metabolizer status and the primary endpoints (HR=0.86).  Subjects in either group had similar rates of the primary endpoint whether treated with prasugrel (HR=0.82) or clopidogrel (HR=0.91; p=0.495).  After adjusting for clinical and treatment variables, they stated that extensive metabolizers had a lower risk of MI vs. reduced metabolizers (HR=0.80), but the risk of other outcomes were similar.  Reduced metabolizers had significantly higher mean P2Y12 reaction units versus extensive metabolizers when treated with clopidogrel (39.93), but not with prasugrel (3.87).

In 2017, Cui and colleagues published a meta-analysis involving 5769 subjects in 15 studies with an aim to evaluate a relation between T744C, G52T, and C34T polymorphisms in the P2Y12 receptor gene in relation to clopidogrel resistance in subjects with cardiovascular disease.  The authors reported that a G52T and C34T polymorphism might be associated with clopidogrel resistance as evident from platelet function assay (p<0.05), and that there was no significant association found between T744C polymorphism and clopidogrel resistance in various genetic models (p>0.05).  This study did not demonstrate a link between the testing for these polymorphisms and improved clinical outcomes when treatment is guided by their results.

A systematic review and meta-analysis was performed by Pan and colleagues (2017) and included 15 studies involving of 4762 subjects with stroke or transient ischemic attack (TIA) treated with clopidogrel.  It was concluded that, in subjects with ischemic stroke or TIA treated with clopidogrel, carriers of CYP2C19 loss-of-function alleles are at a greater risk of stroke and composite vascular events than non-carriers (p<0.001).  The authors also found there was no significant difference in bleeding rates between CYP2C19 carriers and non-carriers (p=0.59), and other genetic variants were not associated with clinical outcomes associated with clopidogrel efficacy for acute ischemic stroke or TIA.  While these findings may suggest the need for genetic testing when clopidogrel is used as the treatment option for stroke or TIA, the meta-analysis lacked statistical heterogeneity among the included studies, one study accounted for 31% of the subjects in the meta-analysis, and the authors disclosed publication bias for the primary end point.     

The results of these large, well-done meta-analyses call into question earlier assessments regarding the efficacy of CYP2C19 genotyping for individuals receiving clopidogrel.  Additional data from large-scale, well-done prospective RCTs is needed to further clarify this issue.

Abacavir

The role of genetic polymorphisms in the metabolism and tolerance of various drugs used to treat HIV-1 infection has been of major interest.  The most widely studied of these interactions is between the histocompatibility complex allele for HLA-B*5701 and the occurrence of abacavir (ABC) hypersensitivity reactions (ABC-HSR).  Since shortly after the U.S. Food and Drug Administration (FDA) approval of ABC in 1999, studies began to arise associating the presence HLA-B*5701 with the occurrence of ABC-HSR.  The largest study currently available addressing the incidence of ABC-HSR was conducted by Hetherington and colleagues (2001).  Using data from approximately 200,000 subjects enrolled in various ABC clinical trials, the authors conducted a retrospective review of pooled adverse events.  Of the 31,096 subjects identified as having hypersensitivity reactions, 1302 (4.3%) were identified as having ABC-HSR.  Of these, 176 (9.8%) were considered definitive ABC-HSR cases after failing rechallenge with ABC.  These findings were supported by a later study by the same authors that found the incidence of ABC-HSR to be approximately 4% in a case control study of 197 subjects from the Glaxo-SmithKlein database (Hetherington, 2002).  Mallal and others (2002) were the first to publish the results of a trial demonstrating a positive correlation between ABC-HSR and the presence of HLA-B*5701.  This small study of 200 HIV-1 subjects exposed to ABC identified 18 individuals with definitive ABC-HSR (9%).  However, the Mallal study went further and typed all subjects for HLA loci.  They reported that HLA-B*5701 occurred in only 4% of ABC tolerant subjects and 78% in subjects with ABC-HSR (p<0.0001), strongly supporting their hypothesis that the presence of the HLA-B*5701 haplotype was strongly associated with ABC-HSR.  They went on to calculate that the presence of HLA-B*5701 had a positive predictive value for ABC-HSR of 100% and a negative predictive value of 97%.  These findings were supported by a retrospective study by Rauch and colleagues (2008) that performed genotyping on 131 individuals with suspected ABC-HSR.  While these authors did not conduct confirmatory rechallenge to confirm ABC-HSR, they did conduct a blind case review of subjects’ medical records, sorting them into likely ABC-HSR (n=27, 21%), unlikely ABC-HSR (n=43, 33%), and uncertain ABC-HSR (n=61, 47%).  They found that HLA-B*5701 was present in 31% of likely cases compared to 1% of unlikely cases (p<0.0001).  A retrospective case control study investigating the sensitivity and specificity of HLA-B*5701 genotyping in subjects receiving ABC enrolled 130 white and 69 black subjects for suspected ABC-HSR (Saag, 2008).  Positive skin-patch testing identified 42 (33.2%) white and 5 (7.2%) black subjects with confirmed ABC-HSR. All confirmed ABC-HSR subjects were HLA-B*5701 positive (sensitivity=100%), regardless of race. Among all subjects with clinically suspected ABC-HSR, sensitivity was 44% for white subjects and 14% for black subjects.  Specificity for white control subjects was 96% and 99% for black subjects.  In the most rigorous study to investigate this issue, Mallal and colleagues conducted a prospective randomized, double-blind study involving 1956 subjects with HIV-1 who were ABC naïve (2008).  Subjects were randomized to undergo prospective HLA-B*5701 screening, with positive subjects forgoing ABC treatment.  The control group received routine care with ABC without HLA-B*5701 screening.  Similar to the previous studies, the prevalence of HLA-B*5701 was 5.6%.  The authors reported that immunologically confirmed ABC-HSR occurred in 2.7% of subjects in the experimental group vs. none in the control group.  The calculated negative predictive value reported to be 100% and positive predictive value was 47.9%.  The existing data, discussed above, adequately demonstrate that the HLA-B*5701 genotype is strongly associated with ABC-HSR, and that screening for this genotype significantly decreases the occurrence of ABC-HSR in individuals who have been prescribed ABC.

In 2016, the Department of Health and Human Services (DHHS) Panel on Antiretroviral Guidelines for Adults and Adolescents published its Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents. The guidelines recommend the following:

Eliglustat

In 2014, the FDA approved eliglustat “for the long-term treatment of adult subjects with Gaucher disease type 1 who are CYP2D6 extensive metabolizers (EMs), intermediate metabolizers (IMs), or poor metabolizers (PMs) as detected by an FDA-cleared test.”

The evidence addressing the use of CYP2D6 genotyping for individuals who may be prescribed eliglustat for the treatment of Gaucher disease was presented in the FDA’s Clinical Pharmacology and Biopharmaceuticals Review of Eliglustat from June 24, 2014.  This document describes data addressing CYP2D6 testing for individuals prescribed eliglustat from several sources. The first is a series of three unpublished Phase I and II safety and effectiveness studies involving 151 subjects.  All subjects were genotyped and followed for drug response and subject pools were stratified into poor metabolizers (PM), intermediate metabolizers (IM), and ultra-rapid metabolizers (URM).  The data demonstrates that there is significant variation in eliglustat metabolism based on CYP2D6 status.  Another source of data presented in the FDA Review document is data derived from computer simulations of metabolic response derived from computer modeling using the SimCYP® software package.  Again, this data demonstrated that there was significant metabolic response to eliglustat dependent upon CYP2D6 status.

Additionally, two peer-reviewed published articles have addressed the use of CYP2D6 genotyping in populations given eliglustat.  The first, by Lukina (2010), was an open-label case series study involving 26 subjects with Gaucher disease.  In the results section, the authors briefly comment that, “Lower exposure was associated with lower administered dose, greater body weight, and higher CYP2D6 metabolic activity.”  No further data or comments are provided, including any outcomes data related to CYP2D6 genotype.  The other study was a small Phase I dose-finding RCT involving healthy volunteers evaluating the safety, tolerability, and pharmacokinetics in escalating doses of eliglustat in 36 subjects.  The authors commented in the discussion section, “As expected, because Genz-99067 is predominantly metabolized by CYP2D6, participants with genotypes corresponding to slower CYP2D6 metabolism exhibited higher exposure.”

Tetrabenazine

There is very little available data addressing the possible benefits of such genotype testing for individuals who may receive treatment with tetratbenazine.  The only available peer-reviewed published study to investigate the issue was published by Mehanna and colleagues in 2013.  This study involved 127 subjects with Huntington disease (chorea) who were genotyped for CYP2D6.  Of this population, 100 were identified as EMs, 14 were IMs, 11 as PMs, and 2 as URMs. The authors noted that the URM subjects required a significantly longer titration period compared to other metabolizer groups (8 vs 3.3, 4.4, and 3 weeks, respectively; p<0.01) to achieve optimal benefit.  This group also required a higher average daily dose than the other subjects, but this difference did not reach statistical significance.  The treatment response was less robust in the IM group when compared with the EM subjects (p=0.013), but there were no statistically significant differences between the various groups with regard to adverse effects.  They concluded that, aside from the need for a longer titration in the URMs, there are no distinguishing features of individuals with various CYP2D6 genotypes, and, “therefore the current recommendation to systematically genotype all patients prescribed more than 50 mg/day of tetrabenazine should be reconsidered.”

However, the FDA-approved label for tetrabenazine states the following:

Before patients are given a daily dose of greater than 50 mg, they should be tested for the CYP2D6 gene to determine whether they are poor metabolizers (PMs) or extensive or intermediate metabolizers (EMs or IMs). When a dose of tetrabenazine is given to PMs, exposure will be substantially higher (about 3-fold for α-HTBZ and 9-fold for β-HTBZ) than it would be in EMs. The dosage should therefore be adjusted according to a patient’s CYP2D6 metabolizer status by limiting the dose to 50 mg in patients who are CYP2D6 poor metabolizers.

Despite the low level of evidence supporting the use of genotyping for individuals who may receive tetrabenazine, at this time the use of such testing for individuals who may receive a dose greater than 50 mg/day is supported by the practicing community based on a preponderance of caution.

Warfarin

Perhaps the most studied area regarding the use of genotype polymorphism testing involves genetic variations in enzymes key to the metabolism and operation of the drug warfarin.  A significant amount of evidence has shown that the enzymes cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase enzyme subunit C1 (VKORC1) have the most significant role in warfarin metabolic variability (Higashi, 2002; Kirchheiner, 2005; Osman, 2006; Sconce, 2005.)  Some reports attribute approximately 55% of warfarin dose variability to these two variants (Sconce, 2005; Wadelius, 2005).

A report published by McClain and colleagues, conducted for the American College of Medical Genetics (ACMG, 2007), evaluated the use of CYP4502C9 (CYP2C9) and VKORC1 testing of individuals receiving warfarin due to increased risk of thrombotic events.  The authors concluded the following:

Caraco and colleagues (2007) describe a randomized, controlled trial evaluating CYP2C9-guided warfarin therapy.  This study included 191 participants (n=96 controls, n=95 in the experimental groups) prescribed warfarin therapy.  While this study did find significant benefits in some secondary outcomes, such as time to stable dosing, more time spent in therapeutic range, and lower rates of minor bleeding, the small study population did not permit assessment of significant differences in serious bleeding, thrombotic events, major morbidity or mortality.  The authors state that further research is warranted.

A study by Anderson and colleagues (2007) indicates some promise for the use of genetic polymorphism testing for individuals receiving warfarin therapy.  In their randomized, blinded study of 206 participants, the investigators compared pharmacogenetic-guided therapy vs. standard dosing methodology.  While the results indicated that the pharmacogenetic-guided therapy more closely approximated stable doses resulting in significantly smaller and fewer dosing changes, the primary endpoint of reducing out-of-range INRs was not significantly different.  However, in a post-hoc subset analysis, the authors reported that in wild-type individuals and those with multiple variant carriers, the differences were significant between groups.  These authors also indicate that additional research is warranted based upon their findings.

In February 2009, the International Warfarin Pharmacogenetics Consortium published a study that describes the development and modeling of two warfarin therapy algorithms that aid in the prediction of the ideal therapeutic dose.  The first algorithm uses both clinical and pharmacogenetic information from a retrospective cohort of 4043 individuals (2009).  The second algorithm uses the same population and methodology, excluding the pharmacogenetic data.  Using data from a separate retrospective cohort of 1009 individuals, the consortium created a model testing the use of these two algorithms against a standard fixed treatment approach of 5 mg warfarin/day.  While this study is of interest, it is only a model and does not provide real-world clinical results.  As has been discussed earlier, clinical validity data is needed for the proper evaluation of the clinical role of pharmacogenetic testing methods.  This report does not provide data on adverse events such as thromboembolic events or bleeding.  The next step is to see how this algorithm functions in a clinical setting with outcomes data reported.

In early 2008, based upon the information provided above, the ACMG published a position statement regarding the use of CYP2C9 and VKORC1 testing, which concluded:

The group determined that the analytical validity of these tests has been met, and there is strong evidence to support association between these genetic variants and therapeutic dose of warfarin. However, there is insufficient evidence, at this time, to recommend for or against routine CYP2C9 and VKORC1 testing in warfarin-naive patients. Prospective clinical trials are needed that provide direct evidence of the benefits, disadvantages, and costs associated with this testing in the setting of initial warfarin dosing…  Although the routine use of warfarin genotyping is not endorsed by this work group at this time, in certain situations, CYP2C9 and VKORC1 testing may be useful, and warranted, in determining the cause of unusual therapeutic responses to warfarin therapy.

However, selection criteria or specific algorithms were not described based upon clinical study evidence.

The Agency for Healthcare Research and Quality (AHRQ) published a technology assessment addressing the use of pharmacogenetic testing for warfarin and statin therapy (2008).  In this assessment, it evaluated the available evidence regarding the clinical impact and outcomes related to the use of pharmacogenetic testing for variants of CYP2C9, VKORC1, and MTHFR. The report concludes:

Overall, studies evaluating associations between the pharmacogenetic test results and the patient’s response to therapy for non-cancer and cancer conditions showed considerable variation in study designs, study populations, medication dosages, and the type of medications. This variation warrants caution when interpreting our results. Data on the relationships among pharmacogenetic test results and patient- and disease-related factors and on the patient’s response to therapy are limited. We found no data on the benefits, harms, or adverse effects from subsequent therapeutic management after pharmacogenetic testing. Detailed patient-level analyses are needed to adjust estimates for the effects of modifiers, such as age or tumor stage.

In 2011, Burmester and others conducted a double-blind RCT with 203 subjects randomized to receive warfarin therapy guided by either standard algorithm (n=112) or by genotype-guided algorithm (n=113).  Only 184 subjects (80%) completed the 60-day trial period.  The results indicated that the genotype-based algorithm was almost more than twice as accurate at predicting final effective dose compared to the standard model (p<0.0001).  However, no difference was noted between groups for time spent in the therapeutic range, time to stable therapeutic dose, time to INR > 4, or adverse events.  The authors concluded that their data was not able to demonstrate that genotype-based initial warfarin dosing is superior to clinical-based dosing with respect to time in therapeutic range through the first 14 days of therapy.  However, the impact of this benefit on the incidence of adverse events remains to be evaluated in a large well-designed study.

A large double-blind RCT conducted by Kimmel (2013) involved 1015 subjects initiating warfarin treatment who were randomized to receive treatment guided by a protocol which included genotype data for CYP2C9 and VKORC1 variants plus clinical variables (n=514) or a protocol that included clinical variables only (n=501).  Subjects had their initial dose and dose adjustments for the first 4-5 days of therapy guided by the assigned protocols.  Subsequent adjustments were per standard protocol for the next 4 weeks.  All subjects were followed for 6 months.  The results show no significant differences between groups with regard to mean percentage of time within therapeutic range during the first 4 weeks (p=0.91).  Overall, there were no significant between-group differences in the mean percentage of time above or below the therapeutic range (INR, < 2 or > 3).  The time to determination of the maintenance dose did not differ significantly between the two groups overall or according to race or total number of genetic variants.  The authors did note a significant difference between groups when a pre-specified sub-analysis was conducted for race.  For black subjects, the mean time in the therapeutic range in the first 4 weeks was less in the genotype-guided group (p=0.01), and overall, black subjects in the genotype-guided group took longer on average to reach the first therapeutic INR than did those in the clinically-guided group.  Black subjects in the genotype-guided group also took longer on average to reach the first therapeutic INR than did those in the control group.  No differences between groups were reported with regard to time of INR ≤ 4, major bleeding, or thromboembolism.  The authors concluded that the genotype-guided algorithms performed better at predicting maintenance dose among non-black subjects.  However, there was no overall benefit of genotype-guided dosing with respect to percentage of time in the therapeutic INR range.  The authors end their report by stating, “Our results emphasize the importance of performing randomized trials for pharmacogenetics, particularly for complex regimens such as warfarin.”

An unblinded RCT published in 2013 by the EU-PACT study group (Pirmohamed, 2013) reported contradictory findings to those by Kimmel.  The study used point-of-care genotype-guided dosing in 455 subjects with either atrial fibrillation (72.1%) or venous thromboembolism (27.9%) receiving initial treatment with warfarin.  Subjects were randomized to receive management with either a genotype-guided algorithm which included data for CYP2C9 and VKORC1 variants plus clinical variables (n=227) or management with an algorithm which included clinical variables only (n=228).  Similar to the Kimmel study, subjects had their initial dose and dose adjustments for the first 4-5 days of therapy guided by the assigned protocols.  Subsequent adjustments were per local clinical practice standards.  All subjects were followed for 3 months.  The presented analysis included only those subjects with at least 13 days of INR data (genotype-guided group, n=211 vs. control group, n=216).  The percentage of time with an INR of 2.0 to 3.0 was 67.4% in the genotype-guided group vs. 60.3% in the control group when adjusted for center and indication (p<0.001).  In the per-protocol analysis, values in the genotype-guided group (n=166) and control group (n=184) were 68.9% and 62.3% (p=0.001).  The difference between the two groups with regard to mean percentage of time in the therapeutic range was significantly different at weeks 1-4 (p<0.001) and 5-8 (p<0.001), but not for weeks 9-12 (p<0.6).  Subjects in the genotype-guided group were less likely to have an INR of 4.0 or higher vs. the control group (p<0.03).  A total of 173 subjects (82.0%) in the genotype-guided group reached a stable dose by 3 months vs. 52 subjects (70.4%) in the control group (p<0.003).  Fewer dose adjustments were required in the genotype-guided group (p=0.02).  No significant differences in bleeding or other adverse events were reported.  The authors concluded that genotype-based dosing at the initiation of warfarin therapy increased the time in the therapeutic range by 7% and reduced the incidence of excessive anticoagulation, the time required to reach a therapeutic INR, the time required to reach a stable dose, and the number of adjustments in the dose of warfarin.

In 2015, Mega and colleagues published the results of a large randomized double-blind clinical trial involving 14,348 subjects.  Subjects were assigned in a 1:1:1 ratio to warfarin (n=4833) or lower dose edoxaban (30 mg) or higher dose endoxaban (60 mg) (n not provided for either group).  Subjects receiving warfarin were genotyped for CYP2C9 and VKORC1 polymorphisms: 2982 (61.7%) were classified as normal responders, 1711 (35.4%) as sensitive responders, and 140 (2.9%) as highly sensitive responders.  Compared with normal responders, sensitive and highly sensitive responders spent greater proportions of time over-anticoagulated in the first 90 days of treatment (ptrend<0.0001) and had increased risks of bleeding with warfarin (sensitive responders HR=1.31; p=0.0179; highly sensitive responders HR=2.66; p<0.0001).  The authors stated that genotype added independent information beyond clinical risk scoring.  Looking at intergroup comparisons, it was reported that during the first 90 days of treatment, when compared with warfarin, treatment with edoxaban reduced bleeding more so in sensitive and highly sensitive responders than in normal responders (higher-dose edoxaban pinteraction=0.0066; lower-dose edoxaban pinteraction=0.0036).  However, after 90 days this reduction in bleeding risk with edoxaban versus warfarin was similarly beneficial across genotypes.  The authors concluded that the identification of CYP2C9 and VKORC1 genotypes helps identify individuals who are more likely to experience early bleeding with warfarin and who may derive a greater early safety benefit from initial use of edoxaban vs. warfarin.

In 2017, two RCTs were completed with the aim of evaluating genotype-guided dosing versus clinically-guided dosing for warfarin in two different populations.  Gage and colleagues focused on 1650 randomized subjects undergoing hip or knee arthroplasty; 1597 subjects (96.8%) completed the study.  While study personnel and subjects were blinded to genotype and study groups, warfarin dosing was open label.  Using the primary end point of the combined risk of major bleeding, INR of 4 or greater, venous thromboembolism, or death, the authors found that 87 subjects (10.8%) in the genotype-guided group met at least one of the end point components (p=0.02).  In another study, Wen and colleagues studied 318 subjects of Han-Chinese descent.  In this single blind (subjects) study, three different dosing algorithms were used.  One was clinically-guided and two were genotype-guided to aid in identifying any difference in the outcomes found from each algorithm.  The authors reported that genotype-guided dosing did not significantly improve percentage of time in the therapeutic INR range by 10 to 12 weeks (p=0.84).

Also in 2017, two systematic reviews and meta-analyses on polymorphism and warfarin were published.  One study assessed CYP2C9 polymorphism while the other focused on VKORC1 polymorphism.  Zhang and colleagues (2017a) studied CYP2C9 polymorphism on pediatric warfarin maintenance dosage requirements in eight articles with a total of 507 subjects.  They found that CYP2C9 *1/*2, CYP2C9 *1/*3, and CYP2C9 variant genotypes in this population were significantly associated with lower warfarin maintenance dose requirements (p<0.05).  Limitations to this study included small sample size and lack of ethnic diversity in subjects.  Tang and colleagues assessed VKORC1 polymorphism and warfarin maintenance dosing in relation to age and ethnicity.  From the 53 studies with a total of 9578 subjects, the authors reported that Caucasian carriers of VKORC1 polymorphisms required a higher mean daily warfarin dose compared with Asian carriers (p<0.05), and that warfarin dosing requirements varied in both Asian and Caucasians aged greater than 60 years and less than 60 years (p<0.05).  The authors concluded that VKORC1 polymorphism testing is needed for optimal therapeutic warfarin dosing.

Acenocoumarol and Phenprocoumon

A second EU-PACT study (Verhoef, 2013) described the results of a single-blind RCT of genotype-guided dosing of acenocoumarol (n=381) and phenprocoumon (n=127).  Subjects were randomized to receive management with either a genotype-guided algorithm which included data for CYP2C9 and VKORC1 variants plus clinical variables (n=273) or management with an algorithm which included clinical variables alone (n=275).  The percentage of time in the therapeutic range during the first 4 weeks after the initiation of treatment was 52.8% in the genotype-guided group vs. 47.5% in the control group (p=0.02).  However, this difference did not persist through the 3 month follow-up period with the percentage of time in the therapeutic INR range being 61.6% for genotype-guided group vs. 60.2% in the control group (p=0.52).  No significant differences between the two groups were reported for several secondary outcomes, including number of subjects with INR ≥ 4, percentage of time with INR ≥ 4, percentage of time with INR < 2, time to reach therapeutic INR and number of subjects with stable dose within 12 weeks.  Additionally, no significant differences were reported with regard to the incidence of bleeding or thromboembolic events.  The authors concluded that genotype-guided dosing of acenocoumarol or phenprocoumon did not improve the percentage of time in the therapeutic INR range during the 12 weeks after the initiation of therapy.

Irinotecan

The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group published its recommendations regarding the use of UGT1A1 testing for individuals undergoing treatment with irinotecan (2009).  This paper concluded:

The evidence is currently insufficient to recommend for or against the routine use of UGT1A1 genotyping in patients with metastatic colorectal cancer who are to be treated with irinotecan, with the intent of modifying the dose as a way to avoid adverse drug reactions (severe neutropenia).

A systematic review and meta-analysis consisting of 746 wild genotype cases and 394 variant genotype cases in 12 studies was published in 2017 by Zhang and colleagues (2017b).  The study was designed to assess if UGT1A1*6 polymorphisms and irinotecan-related severe neutropenia in cancer patients have an association.  Findings from the meta-analysis suggest the UGT1A1*6 polymorphisms correlated with an increased risk of IRI-induced neutropenia in cancer patients.  The authors also concluded that increased cases of severe neutropenia could be associated with diverse regions, cancer type, low dose of IRI, and the duration of treatment.

Also in 2017, Chen and colleagues performed a meta-analysis to determine if UGT1A1*6 and UGT1A1*28 are effective predictor biomarkers of IRI-induced neutropenia, diarrhea, and IRI-based chemotherapy tumor response in Asians with lung cancer.  The analysis included 577 subjects in 9 studies.  The results suggest that UGT1A1*6 polymorphism is significantly associated with an increased risk of IRI-induced neutropenia and diarrhea, and UGT1A1*28 polymorphism is not an effective predictor biomarker of IRI-induced neutropenia and diarrhea.  In addition, the results show that UGT1A1*6 and UGT1A1*28 polymorphisms may not affect IRI-based chemotherapy tumor response.

The two meta-analyses published in 2017 suggest UGT1A1*6 polymorphisms correlate with an increased risk of IRI-induced neutropenia in cancer patients; however, there are limitations to this finding.  Both studies have relatively low sample sizes compared to other meta-analyses.  Also, many of the studies included are lower quality including retrospective and nonrandomized designs.  Higher quality studies are needed to substantiate this finding. 

Dihydropyrimidine Dehydrogenase (DPYD)

Deenen and others conducted a retrospective nested case control study of 45 subjects with colorectal cancer (CRC) who had capecitabine-related toxicity and 100 randomly selected controls (2011).  All subjects were selected from a sample of 568 individuals with previously untreated CRC enrolled in the CAIRO2 trial and were tested for DPYD genetic variants.  From this data, genotype frequencies of polymorphisms were calculated.  The authors reported that four variant alleles (IVS14+1G>A, 1236G>A, 2846G>A, and 2194G>A) were significantly associated with severe diarrhea when carriers were treated with capecitabine-based chemotherapy.  Furthermore, heterozygous carriers of IVS14+1G>A were significantly at risk for developing grade 3 to 4 toxicity.  No association with overall survival was noted for any specific allele.  While this study did identify a role of several alleles in capecitabine-related toxicity, no data regarding outcomes benefit of screening for DYPD genotypes was provided.  Further investigation is warranted.

Tamoxifen

The use of CYP2D6 genotyping testing to determine drug metabolizer status and predict breast cancer-related outcomes in individuals with breast cancer treated with tamoxifen has been a topic of significant debate for the past few years.  Several large scale RCTs have been published addressing this issue.  Abraham and colleagues reported the results of their study, which used data from the Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) study (2010).  This study included 6640 subjects with invasive breast cancer, with 3155 subjects receiving tamoxifen therapy and genotyped for CYP2D6.  Along with genetic data, survival data was used to calculate breast cancer specific survival (BCSS) in this population.  The authors concluded that there was weak, if any, effect of CYP2D6 on BCSS in tamoxifen-treated subjects.  These findings were corroborated in two separate large scale double-blind RCTs published in 2012.  The first was a study using subjects enrolled in the Arimidex, Tamoxifen, Alone or in Combination (ATAC) study, which involved 1203 women genotyped for CPY2D6 and 1209 genotyped for UGT2B7 (Rae, 2012).  No statistically significant associations were observed between CYP2D6 and disease recurrence.  Additionally, a near-null association was noted between UGT2B7 and recurrence in tamoxifen treated subjects.  The second study, by Regan et al. included subjects enrolled in the Breast International Group (BIG) 1-98 study, which involved 1243 subjects with breast cancer treated with tamoxifen (2012).  As with the previously mentioned studies, the BIG study authors found no association between CYP2D6 metabolism phenotype and breast cancer-free interval. 

The results of these trials have been somewhat controversial, with several editorials pointing out significant methodological flaws.  Kelly and Pritchard commented that the power of these studies was insufficient to show a positive association between CYP2D6 and outcomes in subjects taking tamoxifen (2012).  Pharoah and others pointed out that both the Rae and Regan studies were not properly randomized to control for the exposure of interest (2012).  Both these studies were randomized for treatment regimen, not CYP2D6 genotype.  They continue, criticizing both studies for the use of tumor samples to determine genotype, and the Regan study in particular for failure to report consistency of genotype quality and Hardy-Weinberg equilibrium (HWE) data.  The Rae article did not provide data on power calculation, and Pharoah indicates that the study was probably underpowered.  Nakamura and colleagues also point out the inadequacies in the Regan study in relation to HWE issues, and insufficient data provided with regard to genotype data quality (2012).  Finally, as Pharoah pointed out, the use of tumor samples to determine genotype is flawed.  They comment that CYP2D6 is frequently deleted in some common cancers, leading to misclassification of the subject’s actual phenotype, as the unaffected cells in their body may contain a different genotype than their cancer cells.

The results of these studies indicate that the use of CYP2D6 genotyping does not provide data that significantly affects breast cancer-related health outcomes.  However, as the editorials accompanying these studies indicate, there are many flaws in these trials that leave important questions unanswered.  Further investigation is warranted in fully assessing the use of genotyping in this population of individuals.

Other Tests

Testing for genetic polymorphisms has also been proposed for a wide array of other drugs, involving many different conditions and enzymes.  At this time, the available literature addressing such testing is limited and insufficient to allow any assessment of clinical utility in the treatment of individuals.  The outcomes that require further research attention include major adverse events, utilization of health resources, and time to clinically significant changes in condition using appropriate and validated measures.

While the potential of pharmacogenomics is intriguing for many clinical applications, it is not yet clear which are most likely to yield clinical benefit in the near future.  As this field evolves and matures, and if pre-prescription testing can be shown to be of clinical utility for specific drugs and individuals, it will be imperative to establish evidence-based guidelines for healthcare professionals delineating the most effective courses of action based on such genotype testing results.  

Testing Panels

Several commercial laboratories market multi-test panels for genetic polymorphisms related to drug metabolizer status.  While the use of some individual tests included in these test panels may be reasonable under specific circumstances, the use of all the tests within a panel is rarely justified unless there is clinical evidence that the panel provides information that leads to meaningful impact on treatment.  At this time, the available published evidence addressing the use of such test panels is limited to a few panel- and condition-specific studies (Altar, 2015; Hall-Flavin, 2012, 2013; Winner, 2013a, 2013b).  The results of these studies are limited by the study designs utilized by the investigators, with each having some combination of no blinding, small study population, retrospective methodology, selection bias, short follow-up periods, and subjective study outcomes.  The data from these studies is weak, and further investigation is warranted using better designed, larger study samples and double-blind randomized controlled methodology.

In 2017 Bradley and others reported the results of an RCT involving 685 subjects with depression or anxiety treated with either standard of care (n=333) or guided by the results of the NeuroDgenetix® panel test (n=352).  Subjects were evaluated at 4, 8 and 12 weeks post-initiation of therapy.  The authors reported that subjects with depression had significantly higher response rates (p=0.001; OR, 4.72) and remission rates (p=0.02; OR, 3.54) vs. control subjects at 12 weeks.  They also reported that experimental group subjects diagnosed with anxiety showed a meaningful improvement in Hamilton Rating Scale for Anxiety scores at both 8 and 12 weeks (p=0.02 and p=0.02, respectively) as well as higher response rates (p=0.04; OR, 1.76).  These results are promising.  However, the follow-up time of the study was short, and the authors reported a significant lost to follow-up (15.5%).  Additionally, there were numerous medication changes reported throughout the study, which makes it difficult to determine the true clinical utility of this test.  Finally, the reported results do not appear to be an intent to treat analysis, which may lead to selection bias, as dropped subjects are typically thought to be at risk of being failures or developed troubling side effects.  Further investigation into the potential benefits of this test would be welcome.

Background/Overview

Drug efficacy and toxicity vary substantially between individuals.  Because drugs and doses are typically adjusted to meet individual requirements as needed by using trial and error, clinical consequences may include a prolonged time to optimal therapy and serious adverse events.  It has been found that inherited DNA sequence variation (polymorphisms) in genes for drug-metabolizing enzymes may have a significant effect on the efficacy or toxicity of a drug.  This field of research is referred to as pharmacogenomics. 

It has been proposed that genotype testing for certain genes to detect polymorphisms will allow physicians to predict side effects to drugs and to tailor a drug regimen based on an individual’s genetic make-up.  It may be that genotype testing will improve the choice of drug, or the dose of the drug, when the drug in question has a narrow therapeutic dose range, when the consequences of treatment failure are severe, and/or when serious adverse reactions are more likely in individuals with certain polymorphisms. 

One of the drugs where this approach has been most extensively investigated is for the anticoagulant drug warfarin.  This is because the most appropriate dose of warfarin for an individual varies widely, and individuals must be periodically monitored to ensure that a proper level of anticoagulation is maintained.  Warfarin is primarily metabolized by the enzymes in the CYP450 family, and is heavily impacted by the activity of vitamin K epoxide reductase.  Determination of polymorphisms of these genes has been proposed as an aid to help physicians tailor anticoagulant therapy.

The impact of polymorphisms has been the focus of study with a wide variety of drugs and for many diseases and conditions.  The use of this type of science is just starting to be investigated, and its impact on actual medical practice is not yet fully understood.

Definitions

Cytochrome P450: Refers to a family of 60 different enzymes involved in drug and toxin metabolism.

Genotype testing: Determining the DNA sequence in genes.

Metabolize: Refers to breaking down a drug so that it is no longer clinically active.

Polymorphisms: Refers to genetic variation between individuals resulting in differences in gene expression, in this case differing activity of various enzymes.

Uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1): An enzyme that is involved in drug metabolism.

Vitamin K epoxide reductase subunit C1 (VKORC1): An enzyme involved with the metabolism of vitamin K; its C1 subunit (VKORC1) is the target of the anticoagulant warfarin.

Warfarin: A commonly prescribed anticoagulant, i.e., blood thinner.

Coding

The following codes for treatments and procedures applicable to this document are included below for informational purposes. Inclusion or exclusion of a procedure, diagnosis or device code(s) does not constitute or imply member coverage or provider reimbursement policy. Please refer to the member’s contract benefits in effect at the time of service to determine coverage or non-coverage of these services as it applies to an individual member.

CYP2C19, HLA-B
When Services may be Medically Necessary when criteria are met:

CPT

 

81225

CYP2C19 (cytochrome P450, family 2, subfamily C, polypeptide 19) (eg, drug metabolism), gene analysis, common variants (eg, *2, *3, *4, *8, *17) [for clopidogrel metabolism]

81479

Unlisted molecular pathology procedure [when specified as genotype testing for polymorphisms of Human Leukocyte Antigen B*1502 (HLA-B*1502) for carbamazepine metabolism]

ICD-10 Diagnosis

 

 

All diagnoses

When Services may also be Medically Necessary when criteria are met:

CPT

 

81381

HLA Class I typing, high resolution (ie, alleles or allele groups); one allele or allele group (eg, B*57:01P), each [when specified as Human Leukocyte Antigen B*57:01P (HLA-B*5701) for abacavir metabolism or Human Leukocyte Antigen B*1502 (HLA-B*1502) for carbamazepine metabolism]

ICD-10 Diagnosis

 

B20

Human immunodeficiency virus [HIV] disease

E08.40-E08.49

Diabetes mellitus due to underlying condition with neurological complications

E09.40-E09.49

Drug or chemical induced diabetes mellitus with neurological complications

E10.40-E10.49

Type 1 diabetes mellitus with neurological complications

E11.40-E11.49

Type 2 diabetes mellitus with neurological complications

E13.40-E13.49

Other specified diabetes mellitus with neurological complications

F31.0-F31.9

Bipolar disorder

G40.001-G40.919

Epilepsy and recurrent seizures

G50.0-G59

Nerve, nerve root and plexus disorders

G60.0-G60.9

Hereditary and idiopathic neuropathy

G62.0-G62.9

Other and unspecified polyneuropathies

G63

Polyneuropathy in diseases classified elsewhere

G65.0-G65.2

Sequelae of inflammatory and toxic polyneuropathies

G90.01-G90.09

Idiopathic peripheral autonomic neuropathy

M79.2

Neuralgia and neuritis, unspecified

When Services are Investigational and Not Medically Necessary:
For the procedure and diagnosis codes listed above when criteria are not met, or when the code describes a procedure indicated in the Position Statement section as investigational and not medically necessary.

When Services are also Investigational and Not Medically Necessary:

CPT

 

81381

HLA Class I typing, high resolution (ie, alleles or allele groups); one allele or allele group (eg, B*57:01P), each [when specified as Human Leukocyte Antigen A*3101 (HLA-A*3101) for carbamazepine metabolism]

ICD-10 Diagnosis

 

E08.40-E08.49

Diabetes mellitus due to underlying condition with neurological complications

E09.40-E09.49

Drug or chemical induced diabetes mellitus with neurological complications

E10.40-E10.49

Type 1 diabetes mellitus with neurological complications

E11.40-E11.49

Type 2 diabetes mellitus with neurological complications

E13.40-E13.49

Other specified diabetes mellitus with neurological complications

F31.0-F31.9

Bipolar disorder

G40.001-G40.919

Epilepsy and recurrent seizures

G50.0-G59

Nerve, nerve root and plexus disorders

G60.0-G60.9

Hereditary and idiopathic neuropathy

G62.0-G62.9

Other and unspecified polyneuropathies

G63

Polyneuropathy in diseases classified elsewhere

G65.0-G65.2

Sequelae of inflammatory and toxic polyneuropathies

G90.01-G90.09

Idiopathic peripheral autonomic neuropathy

M79.2

Neuralgia and neuritis, unspecified

CYP2D6
When services may be Medically Necessary when criteria are met:

CPT

 

81226

CYP2D6 (cytochrome P450, family 2, subfamily D, polypeptide 6) (eg, drug metabolism), gene analysis, common variants (eg, *2, *3, *4, *5, *6, *9, *10, *17, *19, *29, *35, *41, *1XN, *2XN, *4XN) [for eliglustat or tetrabenazine metabolism]

0028U

CYP2D6 (cytochrome P450, family 2, subfamily D, polypeptide 6) (eg, drug metabolism) gene analysis, copy number variants, common variants with reflex to targeted sequence analysis  [for eliglustat or tetrabenazine metabolism]
CYP2D6 Genotype Cascade; Mayo Clinic

ICD-10 Diagnosis

 

E75.22

Gaucher disease

G10

Huntington’s disease

 

When Services are Investigational and Not Medically Necessary:
For the procedure code listed above when criteria are not met or for all other diagnoses, or when the code describes a procedure indicated in the Position Statement section as investigational and not medically necessary.

Other polymorphism genes
When Services are Investigational and Not Medically Necessary:

CPT

 

81227

CYP2C9 (cytochrome P450, family 2, subfamily C, polypeptide 9) (eg, drug metabolism), gene analysis, common variants (eg, *2, *3, *5, *6)

81230

CYP3A4 (cytochrome P450 family 3 subfamily A member 4) (eg, drug metabolism), gene analysis, common varfiant(s) (eg, *2, *22)

81231

CYP3A5 (cytochrome P450 family 3 subfamily A member 5) (eg, drug metabolism), gene analysis, common varfiant(s) (eg, *2, *3, *4, *5, *6, *7)

81232

DPYD (dihydropyrimidine dehydrogenase) (eg, 5-fluorouracil/5-FU and capecitabine drug metabolism), gene analysis, common variant(s) (eg, *2A, *4, *5, *6)

81346

TYMS (thymidylate synthetase) (eg, 5-fluorouracil/5-FU drug metabolism), gene analysis, common variant(s) (eg, tandem repeat variant)

81350

UGT1A1 (UDP glucuronosyltransferase 1 family, polypeptide A1) (eg, irinotecan metabolism), gene analysis, common variants (eg, *28, *36, *37)

81355

VKORC1 (vitamin K epoxide reductase complex, subunit 1) (eg, warfarin metabolism), gene analysis, common variant(s) (eg, -1639G>A, c.173+1000C>T)

81479

Unlisted molecular pathology procedure [when specified as drug metabolism testing for all other drugs listed, as a panel of tests for drug metabolism or individual gene tests for drug metabolism for all other drugs listed]

0029U

Drug metabolism (adverse drug reactions and drug response), targeted sequence analysis (ie, CYP1A2, CYP2C19, CYP2C9, CYP2D6, CYP3A4, CYP3A5, CYP4F2, SLCO1B1, VKORC1 and rs12777823)
Focused Pharmacogenomics Panel; Mayo Clinic

0030U

Drug metabolism (warfarin drug response), targeted sequence analysis (ie, CYP2C9, CYP4F2, VKORC1, rs12777823)
Warfarin Response Genotype; Mayo Clinic

0031U

CYP1A2 (cytochrome P450 family 1, subfamily A, member 2) (eg, drug metabolism) gene analysis, common variants (ie, *1F, *1K, *6, *7)
Cytochrome P450 1A2 Genotype; Mayo Clinic

0032U

COMT (catechol-O-methyltransferase) (drug metabolism) gene analysis, c.472G>A (rs4680) variant
Catechol-O-methyltransferase (COMT) Genotype; Mayo Clinic

0033U

HTR2A (5-hydroxytryptamine receptor 2A), HTR2C (5-hydroxytryptamine receptor 2C) (eg, citalopram metabolism) gene analysis, common variants (ie, HTR2A rs7997012 [c.614-2211T>C], HTR2C rs3813929 [c.-759C>T] and rs1414334 [c.551-3008C>G])
Serotonin Receptor Genotype (HTR2A and HTR2C); Mayo Clinic

HCPCS

 

G9143

Warfarin responsiveness testing by genetic technique using any method, any number of specimen(s)

ICD-10 Diagnosis

 

 

All diagnoses

References

Peer Reviewed Publications:

  1. Abraham JE, Maranian MJ, Driver KE, et al. CYP2D6 gene variants: association with breast cancer specific survival in a cohort of breast cancer patients from the United Kingdom treated with adjuvant tamoxifen. Breast Cancer Res. 2010; 12(4):R64.
  2. Aithal GP, Day CP, Kesteven PJ, Daly AK. Association of polymorphisms in the cytochrome P450 CYP2C9 with warfarin dose requirement and risk of bleeding complications. Lancet. 1999; 353(9154):717-719.
  3. Altar CA, Carhart JM, Allen JD, et al. Clinical validity: Combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes. Pharmacogenomics J. 2015; 15(5):443-451.
  4. Anderson JL, Horne BD, Stevens SM, et al.; Couma-Gen Investigators. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation. 2007; 116(22):2563-2570.
  5. Artigalás O, Vanni T, Hutz MH, et al. Influence of CYP19A1 polymorphisms on the treatment of breast cancer with aromatase inhibitors: a systematic review and meta-analysis. BMC Med. 2015; 13:139.
  6. Bauer T, Bouman HJ, van Werkum JW, et al. Impact of CYP2C19 variant genotypes on clinical efficacy of antiplatelet treatment with clopidogrel: systematic review and meta-analysis. BMJ. 2011; 343:d4588.
  7. Bradley P, Shiekh M, Mehra V, et al. Improved efficacy with targeted pharmacogenetic-guided treatment of patients with depression and anxiety: A randomized clinical trial demonstrating clinical utility. J Psychiatr Res. 2018; 96:100-107.
  8. Brandl EJ, Tiwari AK, Zhou X, et al. Influence of CYP2D6 and CYP2C19 gene variants on antidepressant response in obsessive-compulsive disorder. Pharmacogenomics J. 2014; 14(2):176-181.
  9. Burmester JK, Berg RL, Yale SH, et al. A randomized controlled trial of genotype-based Coumadin initiation. Genet Med. 2011; 13(6):509-518.
  10. Caldwell MD, Berg RL, Zhang KQ, et al. Evaluation of genetic factors for warfarin dose prediction. Clin Med Res. 2007; 5(1):8-16.
  11. Caraco Y, Blotnick S, Muszkat M. CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin Pharmacol Ther. 2008; 83(3):460-470.
  12. Carlquist JF, Horne BD, Muhlestein JB, et al. Genotypes of the cytochrome p450 isoform, CYP2C9, and the vitamin K epoxide reductase complex subunit 1 conjointly determine stable warfarin dose: a prospective study. J Thromb Thrombolysis. 2006; 22(3):191-197.
  13. Chen P, Lin JJ, Lu CS, et al. Carbamazepine-induced toxic effects and HLA-B*1502 screening in Taiwan. N Engl J Med. 2011; 364(12):1126-1133.
  14. Chen X, Liu L, Guo Z, et al. UGT1A1 polymorphisms with irinotecan-induced toxicities and treatment outcome in Asians with lung cancer: a meta-analysis. Cancer Chemother Pharmacol. 2017; 79(6):1109-1117.
  15. Collet JP, Hulot JS, Pena A, et al. Cytochrome P450 2C19 polymorphism in young patients treated with clopidogrel after myocardial infarction: a cohort study. Lancet. 2009; 373(9660):309-317.
  16. Cui G, Zhang S, Zou J, et al. P2Y12 receptor gene polymorphism and the risk of resistance to clopidogrel: a meta-analysis and review of the literature. Adv Clin Exp Med. 2017; 26(2):343-349.
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  18. Gage BF, Bass AR, Lin H, et al. Effect of genotype-guided warfarin dosing on clinical events and anticoagulation control among patients undergoing hip or knee arthroplasty. JAMA. 2017; 318(12):1115-1124. 
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  48. McCormack M, Alfirevic A, Bourgeois S, et al. HLA-A*3101 and carbamazepine-induced hypersensitivity reactions in Europeans. N Engl J Med. 2011; 364(12):1134-1143.
  49.  Mega JL, Close SL, Wiviott SD, et al. Cytochrome P-450 polymorphisms and response to clopidogrel. N Engl J Med. 2009; 360(4):354-362.
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  51. Mega JL, Simon T, Collet JP, et al. Reduced-function CYP2C19 genotype and risk of adverse clinical outcomes among patients treated with clopidogrel predominantly for PCI: a meta-analysis. JAMA. 2010; 304(16):1821-1830.
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  66. Regan MM, Leyland-Jones B, Bouzyk M, et al.; Breast International Group (BIG) 1-98 Collaborative Group. CYP2D6 genotype and tamoxifen response in postmenopausal women with endocrine-responsive breast cancer: the breast international group 1-98 trial. J Natl Cancer Inst. 2012; 104(6):441-451.
  67. Rojas L, Neumann I, Herrero MJ, et al. Effect of CYP3A5*3 on kidney transplant recipients treated with tacrolimus: a systematic review and meta-analysis of observational studies. Pharmacogenomics J. 2015; 15(1):38-48.
  68. Saag M, Balu R, Phillips E, et al.; Study of Hypersensitivity to Abacavir and Pharmacogenetic Evaluation Study Team. High sensitivity of human leukocyte antigen-b*5701 as a marker for immunologically confirmed abacavir hypersensitivity in white and black patients. Clin Infect Dis. 2008; 46(7):1111-1118.
  69. Sanderson S, Emery J, Higgins J. CYP2C9 gene variants, drug dose, and bleeding risk in warfarin-treated patients: a HuGEnet systematic review and meta-analysis. Genet Med. 2005; 7(2):97-104.
  70. Schelleman H, Chen Z, Kealey C, et al. Warfarin response and vitamin K epoxide reductase complex 1 in African Americans and Caucasians. Clin Pharmacol Ther. 2007; 81(5):742-747.
  71. Schroth W, Goetz MP, Hamann U, et al. Association between CYP2D6 polymorphisms and outcomes among women with early stage breast cancer treated with tamoxifen. JAMA. 2009; 302(13):1429-1436.
  72. Sconce EA, Khan TI, Wynne HA, et al. The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood. 2005; 106(7):2329-2333.
  73. Shams ME, Arneth B, Hiemke C, et al. CYP2D6 polymorphism and clinical effect of the antidepressant venlafaxine. J Clin Pharm Ther. 2006; 31(5):493-502.
  74. Sibbing D, Koch W, Gebhard D, et al. Cytochrome 2C19*17 allelic variant, platelet aggregation, bleeding events, and stent thrombosis in clopidogrel-treated patients with coronary stent placement. Circulation. 2010; 121(4):512-518.
  75. Sibbing D, Stegherr J, Latz W, et al. Cytochrome P450 2C19 loss-of-function polymorphism and stent thrombosis following percutaneous coronary intervention. Eur Heart J. 2009; 30(8):916-922.
  76. Simon T, Steg PG, Becquemont L, et al. Effect of paraoxonase-1 polymorphism on clinical outcomes in patients treated with clopidogrel after an acute myocardial infarction. Clin Pharmacol Ther. 2011; 90(4):561-567.
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Government Agency, Medical Society, and Other Authoritative Publications:

  1. Afinitor® [Product Information], East Hanover, NJ. Novartis Pharmaceuticals Corp. Stein. September 2017. Available at: https://www.pharma.us.novartis.com/sites/www.pharma.us.novartis.com/files/afinitor.pdf. Accessed on November 28, 2017.
  2. Agency for Healthcare Research and Quality. Technology Assessment: Reviews of selected pharmacogenetic tests for non-cancer and cancer conditions. November 12, 2008. Available at: http://www.cms.gov/medicare-coverage-database/details/technology-assessments-details.aspx?TAId=61&bc=BAAgAAAAAAAA&. Accessed December 8, 2016.
  3. Aromasin® [Product Information], Kalamazoo, MI. Pharmacia and Upjohn Co. July 2016. Available at: http://labeling.pfizer.com/ShowLabeling.aspx?id=523. Accessed on November 28, 2017.  
  4. Centers for Medicare and Medicaid Services National Coverage Determination for Pharmacogenomic Testing for Warfarin Response. NCD #90.1. Effective August 3, 2009.
  5. Eliglustat® [Product Information], Waterford, Ireland. Genzyme Corporation. August 2014. Available at: http://www.cerdelga.com/pdf/cerdelga_prescribing_information.pdf. Accessed on November 28, 2017.
  6. Erbitux® [Product Information], Branchburg, NJ. ImClone LLC. October 2016. Available at: http://pi.lilly.com/us/erbitux-uspi.pdf. Accessed on November 28, 2017.
  7. Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: can UGT1A1 genotyping reduce morbidity and mortality in patients with metastatic colorectal cancer treated with irinotecan? Genet Med. 2009; 11(1):15-20.
  8. Faslodex® [Product Information], Wilmington DE. AstraZeneca. November 2017. Available at: https://www.azpicentral.com/faslodex/faslodex.pdf#page=1 . Accessed on February 23, 2018.
  9. Femara® [Product Information], East Hanover, NJ. Novartis Pharmaceuticals Corp. July 25, 1997. Available at: http://www.accessdata.fda.gov/drugsatfda_docs/label/2007/020726s014lbl.pdf. Accessed on December 8, 2016.
  10. Flockhart DA, O'Kane D, Williams MS, et al.; ACMG Working Group on Pharmacogenetic Testing of CYP2C9, VKORC1 Alleles for Warfarin Use. Pharmacogenetic testing of CYP2C9 and VKORC1 alleles for warfarin. Genet Med. 2008; 10(2):139-150.
  11. Herceptin® [Product Information], South San Francisco, CA. Genentech, Inc. April 2017. Available at: https://www.gene.com/download/pdf/herceptin_prescribing.pdf. Accessed on November 28, 2017.
  12. Kadcyla® [Product Information], South San Francisco, CA. Genentech, Inc.  July 2016. Available at: https://www.gene.com/download/pdf/kadcyla_prescribing.pdf . Accessed on November 28, 2017.
  13. Kalydeco® [Product Information], Cambridge MA. Vertex Pharmaceuticals Inc. July 2017. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/203188s026,207925s005lbl.pdf. Accessed on November 28, 2017.
  14. McClain MR, Palomaki GE, Piper M, et al. A rapid ACCE1 review of CYP2C9 and VKORC1 allele testing to inform warfarin dosing in adults at elevated risk for thrombotic events to avoid serious bleeding. February 2008. Available at: https://www.acmg.net/docs/Warfarin_Dosing.pdf. Accessed on November 28, 2017.
  15. Clinical Practice Guidelines in Oncology™ (NCCN).© 2017 National Comprehensive Cancer Network, Inc. For additional information visit the NCCN website at: http://www.nccn.org/index.asp. Accessed on November 28, 2017.
    • Breast Cancer (V3.2017). Revised November 10, 2017
  16. Nolvadex® [Product Information], Wilmington DE. Zeneca Pharmaceuticals. March 9, 2006. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2006/017970s054lbl.pdf. Accessed on November 28, 2017.  
  17. Ontak® [Product Information], Hopkinton, MA. Seragen, Inc. August 2011. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2011/103767s5119lbl.pdf. Accessed on November 28, 2017.  
  18. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in adults and adolescents living with HIV. October 17, 2017. Department of Health and Human Services. Available at http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. Accessed on November 28, 2017.
  19. Perjeta® [Product Information], South San Francisco, CA. Genentech, Inc. May 2017. Available at: https://www.gene.com/download/pdf/perjeta_prescribing.pdf. Accessed on November 28, 2017.
  20. Plavix® [Prescribing Information], Bridgewater, NJ. Sanofi Aventis. October 2017. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/020839s068lbl.pdf. Accessed on November 28, 2017.
  21. Pravachol® [Product Information], Princeton, NJ. Bristol-Meyers-Squibb Co. July 2016. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2016/019898s066lbl.pdf. Accessed on November 28, 2017.
  22. Selzentry® [Product Information], New York, New York. Pfizer, Inc. November 2016. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2016/208984_022128s017lbl.pdf. Accessed on November 28, 2017.
  23. Tarceva® [Product Information], Melville, NY. OSI Pharmaceuticals. October 2016. Available at: https://www.gene.com/download/pdf/tarceva_prescribing.pdf. Accessed on November 28, 2017.
  24. Tegretol® [Product Information], East Hanover, NJ. Novartis Pharmaceuticals Corp.  September 2015. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2015/016608s097,018281s045,018927s038,020234s026lbl.pdf. Accessed on November 28, 2017.
  25. Tykerb® [Product Information], Research Triangle Park, NC. GlaxoSmithKlein. April 2017. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/022059s022lbl.pdf. Accessed on November 25, 2017.
  26. U.S. Food and Drug Administration. Clinical Pharmacology and Biopharmaceuticals Review. June 25, 2014. Available at: http://www.accessdata.fda.gov/drugsatfda_docs/nda/2014/205494Orig1s000ClinPharmR.pdf. Accessed on November 28, 2017.
  27. Xenazine® [Prescribing Information], Washington, DC. Prestwick Pharmaceuticals. September 2017. Available at: http://www.lundbeck.com/upload/us/files/pdf/Products/Xenazine_PI_US_EN.pdf. Accessed on November 28, 2017.
  28. Vectibix® [Product Information], Thousand Oaks, CA. Amgen Inc. June 2017. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/125147s207lbl.pdf. Accessed on November 28, 2017.   
  29. Zelboraf® [Product Information], Nutley, NJ. Hoffman La Roche. November 2017. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/202429s016lbl.pdf. Accessed on November 28, 2017.
  30. Ziagen® [Product Information], Research Triangle Park, NC. GlaxoSmithKlein. March 2017. Available at: https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/020977s032,020978s035lbl.pdf. Accessed on November 28, 2017.
Index

5-fluorouracil (5-FU)
Abacavir
Adrucil®
AmpliChip™ Cytochrome P450 (CYP450) Genotype Test
Camptosar®
Carac®
Carbatrol®
Coumadin®
Cytochrome P450 (CYP450)
Cytochrome P450 2C9 (CYP2C9)
Dilantin®
DrugMEt
Efudex®
Equetro®
Fluoroplex®
Genecept Assay
GeneSight Analgesic
GeneSight Psychotropic
GeneSight ADHD
Invader®
Jantoven®
NeuroDgenetix test
Nolvadex®
PHARMAchip
Plavix®
Polymorphisms, Drug Testing
PROOVE Drug Metabolism test
PROOVE Narcotic Risk Profile
Tegretol®
Verigene® Warfarin Metabolism Nucleic Acid Test
Vitamin K Epoxide Reductase
Vitamin K Epoxide Reductase Subunit C1 (VKORC1)
VKORC1
Warfarin DoseAdvise
Ziagen

The use of specific product names is illustrative only.  It is not intended to be a recommendation of one product over another, and is not intended to represent a complete listing of all products available. 

Document History

Status

Date

Action

Reviewed

01/25/2018

Medical Policy & Technology Assessment Committee (MPTAC) review.  Updated Rationale, References, Websites, and Index sections. Updated Coding section with additional diagnosis codes for testing for carbamazepine.

 

12/27/2017

The document header wording updated from “Current Effective Date” to “Publish Date.” Updated Coding section with 01/01/2018 CPT changes; added 81230, 81231, 81232, 81346 replacing Tier 2 codes, added 0028U, 0029U, 0030U, 0031U, 0033U; removed 0015U deleted 12/31/2017.

 

08/01/2017

Updated Coding section with 08/01/2017 CPT PLA code changes.

Revised

02/02/2017

MPTAC review. Updated formatting in the Position Statement. Updated Rationale, Coding and Reference sections.

 

01/01/2017

Updated Coding section; removed code 81291 now addressed in a separate document.

Revised

02/04/2016

MPTAC review. Added new tests to Investigational and Not Medically Necessary statement. Deleted the Vysis ALK Break Apart FISH Probe Kit from the Investigational and Not Medically Necessary statement. Updated Rationale and Reference sections.

 

01/01/2016

Updated Coding section with 01/01/2016 CPT descriptor revision for code 81355; removed ICD-9 codes.

Revised

08/06/2015

MPTAC review. Added note regarding testing for thiopurine methyltransferase (TPMT) for individuals receiving treatment with azathioprine or 6-mercaptopurine therapy, and testing for NS3 Q80K for individuals being treated for Hepatitis C virus are NOT addressed on this document. Removed position statement addressing NS3 Q80K polymorphism testing in individuals with HCV genotype 1a.  Updated Rationale, and References sections. Updated Coding section; removed CPT 87902 no longer addressed.

Revised

02/05/2015

MPTAC review. Added medically necessary statements for individuals who may be treated with eliglustat or tetrabenazine. Added investigational and not medically necessary statement for drugs mentioned in the medically necessary statement when criteria have not been met. Added investigational and not medically necessary statement for individuals who may be treated with simeprevir plus sofosbuvir. Added investigational and not medically necessary statement for individuals who may be treated with opioids and narcotics. Added several commercially available test panels to investigational and not medically necessary statement. Updated Rationale, Coding and References sections.

Revised

08/14/2014

MPTAC review. Added to medically necessary section: “Genotype testing for the presence of hepatitis C virus (HCV) genotype 1a with the NS3 Q80K polymorphism is considered medically necessary before beginning treatment with Olysio™ (simeprevir) plus peginterferon and ribavirin.” Added investigational and not medically necessary statement regarding testing panels. Updated Coding, Rationale, Reference, and Index sections.

Reviewed

02/13/2014

MPTAC review. Updated Rationale and Reference sections.

Reviewed

02/14/2013

MPTAC review. Updated Rationale and Reference sections.

 

01/01/2013

Updated Coding section with 01/01/2013 CPT changes; removed 88384-88386 deleted 12/31/2012.

Revised

02/16/2012

MPTAC review. Added medically necessary statement for genotype testing for Human Leukocyte Antigen B (HLA-B*5701) for persons infected with HIV-1 before starting treatment with abacavir. Updated Rationale, Coding and Reference sections.

 

01/01/2012

Updated Coding section with 01/01/2012 CPT changes.

Reviewed

05/19/2011

MPTAC review. Updated Reference section.

Revised

05/13/2010

MPTAC review. Added testing for CYP2C19 variant of Cytochrome P450 as medically necessary for individuals receiving clopidogrel therapy and who have not been previously tested or those for whom clopidogrel therapy has been proposed. Updated Rationale, Coding, Reference and Index sections.

 

01/01/2010

Updated Coding section with 01/01/2010 HCPCS changes.

Revised

05/21/2009

MPTAC review.

Revised

05/21/2009

Hematology/Oncology Subcommittee review. Added use of Human Leukocyte Antigen B*1502 (HLAB*1502) as medically necessary with criteria. Added Clopidogrel and HLAB*1502 to investigational and not medically necessary section. Updated Rationale, Coding, Reference and Index sections.

Reviewed

02/26/2009

MPTAC review. Updated Rationale and Reference sections.

Reviewed

02/21/2008

MPTAC review. Updated Rationale and Reference sections.

Revised

11/29/2007

MPTAC review. Altered title to replace “Cytochrome P450” with “Genetic.” Revised the investigational/not medically necessary position statements to include all genetic polymorphism testing for drug metabolizer status. The phrase “investigational/not medically necessary” was clarified to read “investigational and not medically necessary.” Updated Rationale, Background, Reference, and Index sections.

Revised

03/08/2007

MPTAC review. Added tamoxifen to investigational/not medically necessary section. References and Coding updated. Document number changed from LAB.00013 to GENE.00010.

Reviewed

03/23/2006

MPTAC review. References updated. 

New

04/28/2005

MPTAC initial document development.