| Coverage Policy Manual | |
| Policy #: | 2015005 |
| Category: | Laboratory |
| Initiated: | January 2015 |
| Last Review: | December 2023 |
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| Genetic Test: Pharmacogenetic Testing for Pain Management | |
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| Description: |
According to an analysis of 2016 National Health Interview Survey (NHIS) data, an estimated 20.4% (50 million) U.S. adults experience chronic pain and 8% (19.6 million) have high-impact chronic pain (ie, pain that frequently limits life or work activities) (Dahlhamer, 2018). Chronic pain may be related to cancer, or be what is termed “chronic non-cancer pain,” which may be secondary to a wide range of conditions, such as migraines, low back pain, or fibromyalgia. Multiple therapeutic options exist to manage pain, including pharmacotherapies, behavioral modifications, and physical and occupational therapy, and complementary/alternative therapies. Nonetheless, the Institute of Medicine (IOM) reports that many individuals receive inadequate pain prevention, assessment, and treatment (IOM, 2011). Given that pain is an individual and subjective experience, assessing and predicting response to pain interventions, including pain medications, is challenging.
Overview of Pain Management
A variety of medication classes are available to manage pain: non-opioid analgesics, including acetaminophen and nonsteroidal anti-inflammatory drugs (NSAIDS), opioid analgesics, which target central nervous system (CNS) pain perception, and a variety of classes of adjuvants, including antiepileptic drugs (eg, gabapentin, pregabalin), antidepressants (eg, tricyclic antidepressants, serotonin-norepinephrine reuptake inhibitors), and topical analgesics. The management of chronic pain has been driven, in part, by the World Health Organization’s analgesic ladder for pain management, which was developed for the management of cancer-related pain but has been applied to the management of other forms of pain. The ladder outlines a stepped approach to pain management, beginning with non-opioid analgesia and proceeding to a weak opioid (eg, codeine), with or without an adjuvant for persisting pain and subsequently to a strong opioid (eg, fentanyl, morphine), with or without an adjuvant for persisting or worsening pain. A wide variety of opioids are available in short- and long-acting preparations and administered through variety of routes, including oral, intramuscular, subcutaneous, sublingual, and transdermal.
For acute pain management, particularly postoperative pain, systemic opioids and non-opioid analgesics remain a mainstay of therapy. However, there has been growing interest in using alternative, nonsystemic treatments in addition to or as an alternative to systemic opioids. These options include neuraxial anesthesia, including intraoperative epidural or intrathecal opioid injection, which can provide pain relief for up to 24 hours postoperatively, and postoperative indwelling epidural anesthesia with opioids and local anesthetics, which may be controlled with a patient-controlled anesthesia (PCA) pump. Postoperative peripheral nerve blocks may also be used.
While available pain management therapies are effective for many patients, there is a high degree of heterogeneity in pain response, particularly in the management of chronic pain. In addition, many opioids are associated with significant risk of, ranging from mild (eg, constipation) to severe (eg, respiratory depression) and are associated with risk of dependence, addiction, and abuse. Limitations in currently available pain management techniques have led to interest in the use of pharmacogenetics to improve the targeting of therapies and prediction and avoidance of adverse events.
Genetics of Pain Management
Genetic factors may contribute to a range of aspects of pain and pain control, including predisposition to conditions that lead to pain, pain perception, and the development of comorbid conditions that may affect pain perception. The currently available genetic tests relevant to pain management assess SNPs single-nucleotide variants in single genes potentially relevant to pharmacokinetic or pharmacodynamic processes.
Genes related to these clinical scenarios include, broadly speaking, those involved in neurotransmitter uptake, clearance, and reception; opioid reception; and hepatic drug metabolism. Panels of genetic tests have been developed and have been proposed for use in the management of pain. Genes relevant to pain management include: 5HT2C (serotonin receptor), 5HT2A (serotonin receptor), SLC6A4 (serotonin transporter), DRD1, DRD2, DRD4, DAT1 or SLC6A3, DBH, COMT, MTHFR, y-Aminobutyric acid (GABA) A receptor, OPRM1, OPRK1, UGT2B15, CYP2D6, CYP2C19, CYP2C9, CYP3A4, CYP2B6 and CYP1A2.
Commercially Available Genetic Tests for Pain Management
Several test labs market panels of tests or individual tests designed to address one or more aspects of pain management, including but not limited to drug selection, drug dosing, or prediction of adverse events.
Other laboratories, including CompanionDx (Houston, TX), and AIBioTech (Richmond, VA), which markets the PersonaGene Genetic Panel, offer panels of CYP450 genes.
In addition to the available panel tests, several labs offer genetic testing for individual genes that are included in some of the panels, including MTFHR, CYP450 genes, and OPRM1.
Regulatory Status
Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). The OmeCare OmePainMeds panel, the Millennium PGT (Pain Management) panel, and YouScript Analgesic panel are available under the auspices of the CLIA. Laboratories that offer laboratory-developed tests must be licensed by the CLIA for high-complexity testing. To date, the U.S. Food and Drug Administration (FDA) has chosen not to require any regulatory review of these tests.
No genetic tests approved by the FDA for pain management were identified.
Of note, in February 2020, the FDA expressed "concerns with firms offering genetic tests making claims about how to use the genetic test results to manage medication treatment that are not supported by recommendations in the FDA-approved drug labeling or other scientific evidence" (FDA, 2020). Due to these concerns, the FDA announced a collaboration between the FDA’s Center for Devices and Radiological Health and Center for Drug Evaluation and Research intended to provide the agency’s view of the state of the current science in pharmacogenetics. This collaborative effort includes a web resource, that describes "some of the gene-drug interactions for which the FDA believes there is sufficient scientific evidence to support the described associations between certain genetic variants, or genetic variant-inferred phenotypes, and altered drug metabolism, and in certain cases, differential therapeutic effects, including differences in risks of adverse events" (FDA, 2020).
Coding
The following tests have been codified in CPT:
There is specific CPT coding for this testing:
81225: CYP2C19 (cytochrome P450, family 2, subfamily C, polypeptide 19) (eg, drug metabolism), gene analysis, common variants (eg, *2, *3, *4, *8, *17)
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)
81227: CYP2C9 (cytochrome P450, family 2, subfamily C, polypeptide 9) (eg, drug metabolism), gene analysis, common variants (eg, *2, *3, *5, *6)
81291: MTHFR (5, 10-methylenetetrahydrofolate reductase) (eg, hereditary hypercoagulability) gene analysis, common variants (eg, 677T, 1298C)
Code 81401 includes CYP3A4 testing:
81401: Molecular pathology procedure, Level 2 (eg, 2-10 SNPs, 1 methylated variant, or 1 somatic variant [typically using nonsequencing target variant analysis], or detection of a dynamic mutation disorder/triplet repeat) includes –
CYP3A4 (cytochrome P450, family 3, subfamily A, polypeptide 4) (eg, drug metabolism), common
variants (eg, *2, *3, *4, *5, *6)
There is no specific CPT code for pain management testing panels. If there are CPT codes for the component tests in the panel and there is no algorithmic analysis used, the individual CPT codes may be reported. The unlisted molecular pathology code 81479 would be reported once for the balance of the panel.
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Policy/ Coverage: |
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
Genetic testing for pain management for all indications does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness.
For members with contracts without primary coverage criteria, genetic testing for pain management is considered investigational for all indications. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
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| Rationale: |
This policy was created in January 2015 with a review of the available literature through a search of the Medline database from January 2004 through December 3, 2014, limited to studies published after 2004. The following is a summary of the key literature to date.
The evaluation of a genetic test’s clinical utility focuses on 3 main principles: (1) analytic validity (technical accuracy of the test in detecting a mutation that is present or in excluding a mutation that is absent); (2) clinical validity (diagnostic performance of the test [sensitivity, specificity, positive and negative predictive values] in detecting clinical disease); and (3) clinical utility (how the results of the diagnostic test will be used to change management of the patient and whether these changes in management lead to clinically important improvements in health outcomes).
In the case of genetic testing for pain management, testing is not used primarily as a diagnostic test; rather, testing is used to guide medication management, in one of the following ways:
Drug selection or avoidance:
Dose optimization:
Analytic Validity
Information on analytic validity of the test is lacking. No published studies were identified that specifically evaluated the analytic validity of the test as performed commercially. There was no information identified in the published literature or from the manufacturers’ websites concerning the genetic testing methods used for analysis. As a result, it is not possible to determine the analytic validity of the testing process.
Clinical Validity
Evidence on the clinical validity of genetic testing for pain management primarily consists of genome-wide association studies (GWAS) that correlate specific genetic polymorphisms with pain medication requirements or measures of pain control and case-control and cohort studies that report differences in pain medication requirements or measures of pain control for different genotypes. A comprehensive review of the GWAS and case control studies for all of these genes is beyond the scope of this policy. However, some of the representative literature, with a focus on studies published within the last 10 years, in this area is discussed next.
Genetic Variants and Analgesic Requirements
A variety of studies have evaluated the association of various genes with pain sensitivity or efficacy of pain medication, either elicited directly via subject report of pain or indirectly via analgesic dose requirement. Studies that evaluate the association between single nucleotide polymorphisms (SNPs) and analgesic dose requirements may provide a more objective outcome measurement of pain control; although this design makes it difficult to separate the effects of genotype on pain sensitivity from those of genotype on pain medication efficacy, these types of studies most directly translate to the clinical use of dose optimization.
Genetic Variants and Analgesic Requirements: Multiple-Gene Studies
Several studies have evaluated the association between multiple genes and SNPs and pain control. Klepsted et al reported results of a large genetic association study that evaluated the impact of variability in multiple genes on opioid use for cancer pain among 2294 cancer pain patients (Klepstad, 2011). Patients were enrolled from 17 European centers and were considered eligible if they had malignant disease and were using an opioid for moderate or severe pain (step III or higher on the World Health Organization treatment ladder for cancer pain). The authors assessed a large number of SNPs in multiple candidate genes, which had previously been associated with pain control:
· OPRM1 (mu opioid receptor; 9 SNPs);
· OPRD1 (delta opioid receptor; 3 SNPs);
· OPRK1 (kappa opioid receptor; 1 SNP);
· ARRB (beta-arrestin; 7 SNPs);
· GNAZ (G nucleotide-binding protein 1; 1 SNP);
· HIN1 (histidine trinucleotide binding protein 1; 5 SNPs);
· Stat6 (signal transducer and activator of receptor 6; 3 SNPs);
· ABCB1 (p-glycoprotein transporter; 8 SNPs);
· COMT (catechol-O-methyltransferase; 6 SNPs);
· ADRA21 (alpha 2A adrenergic receptor; 3 SNPs);
· MC1R (melanocortin 1 receptor; 1 SNP);
· TACR1 (neurokinin 1 receptor; 10 SNPs);
· GCH1 (GTP cyclohydrolase 1; 3 SNPs);
· DRD2 (dopamine receptor D2; 11 SNPs);
· DRD3 (dopamine receptor D3; 8 SNPs);
· HTR3A, -3B, -2A, -3C, -3D, -3E, 1 and 4 (serotonin receptors; 36 SNPs);
· HRH1 (histamine receptor H1; 4 SNPs);
· CNR1 (cannabinoid receptor 1; 3 SNPs.
The patients’ primary opioids were morphine (n=830), oxycodone (n=446), fentanyl (n=699), or other opioids (n=234). Patients were randomly divided into 2 groups, with 2/6s serving as a development sample and 1/3 serving as a validation sample. The authors used a 10% false discovery rate for determining SNPs associated with the outcome measure using the Benjamini-Hochberg approach. Ten SNPs investigated had a minor allele frequency of less than 0.05 and/or were not in Hardy–Weinberg equilibrium and were excluded from further analyses. For the primary outcome of opioid dosage, no SNPs were consistently associated with dosage in both the development and validation samples. The authors note that their study design (cross-sectional evaluation of cancer patients already managed with opioids) does not allow the determination of the relative genetic influence of pain perception and opioid efficacy.
In another relatively large study, Lotsch et al evaluated the effect of SNPs in multiple candidate genes on pain control among 352 patients treated in outpatient tertiary care centers.7 The authors assessed the following SNPs:
· OPRM1 (mu opioid receptor) 118A>G;
· COMT (catechol-O-methyltransferase) 472G>A;
· ABCB1 (p-glycoprotein transporter) 1236C>T, 2677G>T(A), and 3435C>T;
· MC1R (melanocortin 1 receptor) 29insA, 451C>T, 478C>T, and 880G>C;
· Nonfunctional CYP2D6 alleles: *3, *4, *6, *7, *8, *9;
· Functionally impaired CYP2D6 *41 allele;
Patients were managed with multiple opioids, most commonly oral tilidine (N=81; 15.6%), oral tramadol 9N=81; 15.6%), and intravenous or subcutaneous morphine (N=74; 14.3%). Opioid doses were converted to oral morphine equivalents. In linear regression, the ABCB1 3435C>T polymorphism was the only factor significantly associated with opioid dose (p=0.004). In linear regression, the OPRM1 118Aà G polymorphism was the only candidate gene significantly associated with 24-hour pain score (p=0.041). No genetic associations were found with opioid-related AEs, including nausea/vomiting, constipation, fatigue, or laboratory abnormalities.
Genetic Variants and Analgesic Requirements: OPRM1 Genotype
The largest body of research assessing the association between SNPs in a specific gene and pain management appears to be for OPRM1 genotype, most often for the A118G SNP (rs1799971).
Genetic Variants and Analgesic Requirements: CYP450 Genotype
A full review of the association between CYP450 genotypes and medications used for pain is beyond the scope of this policy (see MPRM Policy 2.04.38, “Cytochrome P450 Genotyping.”) However, a summary of recent studies focusing on CYP2D6 metabolism status and pain management, primarily in the use of opioid medications, is outlined next.
CYP450 and Metabolism of Multiple Opioids. Jannatto et al evaluated the association between steady-state concentrations of the opioids methadone, oxycodone, hydrocodone, and tramadol and CYP2D6 genotype among 61 patients being treated for chronic pain (Jannetto, 2009). Most patients (54%) were extensive metabolizers (EM), while 41% were intermediate metabolizers (IM), and 5% were poor metabolizers (PM). No statistically significant associations were seen with CYP2D6 metabolizer status and opioid steady state concentration. For CYP2D6 EMs, 21% had complete pain relief, 58% had partial pain relief, and 21% had no relief, whereas for CYP2D6 IMs, 20% had complete pain relief, 68% had partial pain relief, and 12% had no pain relief, while all CYP2D6 PMs had partial pain relief (statistical comparison not reported).
CYP450 and Metabolism of Tramadol. Kirschheiner et al evaluated the association between CYP2D6 genotype and tramadol pharmacokinetics and pharmacodynamics among 25 healthy volunteers given tramadol (11 considered ultrarapid metabolizers [UM], 11 EMs, and 5 PMs based on CYP2D6 genotype) (Kirchheiner, 2008). The maximum plasma concentration of tramadol’s active metabolite were significantly higher for UM subjects than for EM subjects (mean difference, 14 ng/mL; 95% CI, 2 to 26 ng/mL; p=0.005). The mean increase in pain tolerance from baseline to 4 hours after tramadol intake was -1 second, 20 seconds, and 36 seconds in the PM, EM, and UM groups, respectively. UMs demonstrated a stronger miosis after tramadol (maximum decrease in pupillary diameter after tramadol: 1 mm, 1.4 mm, and 2.2 mm for PM, EM, and UM groups, respectively). The authors conclude that UMs were more sensitive to the effects of tramadol.
In an earlier case control study, Wang et al reported an association between CYP2D6 *10 C188T polymorphisms and post-operative tramadol consumption in 71 patients following gastrectomy (Wang, 2006).
CYP450 and Metabolism of Codeine. Kirschheiner et al evaluated the association between CYP2D6 genotype and codeine metabolism among 25 healthy volunteers given a single 30-mg dose of codeine (11 UMs, 11 EMs, and 5 PMs based on CYP2D6 genotype) (Kirchheiner, 2007). The area under the curve (AUC) for plasma concentration of morphine (the active metabolite of codeine) versus time was significantly greater for UMs (16 μg hour/L vs 11 μg hour/L; p=0.02). UMs were more likely to report sedation than EMs (91% vs 50%; p=0.03).
CYP450 and Metabolism of Oxycodone. In another, case-control study, Zwisler et al evaluated the association between CYP2D6 polymorphisms and intravenous oxycodone requirements following surgery (primarily thyroid or hysterectomy) in 270 patients (Zwisler, 2010). The authors found no difference between total oxycodone consumption between CYP2D6 EMs and PMs (EM, 14.7 mg vs PM, 13 mg; p=0.42).
CYP450 and Metabolism of Fentanyl. Liao et al evaluated the association between CYP3A4 polymorphisms and interactions with OPRM1 A118G polymorphisms and post-operative fentanyl requirements among 97 patients undergoing radical gastrectomy (Liao, 2013). Patients with the CYP3A4 *18B/*18B genotype used less fentanyl via PCA in the 48 hours after surgery compared with patients in the *1/*1 group (16.3 μg/kg vs 22.5 μ/kg; p=0.032). Although OPRM A118G polymorphisms were not significantly associated with cumulative fentanyl dose at 24 or 48 hours post-surgery, the joint genotype combination between CYP3A4 and OPRM1 was significantly associated with 48-hour cumulative fentanyl dose (p=0.021). VAS scores and frequency of AEs (nausea, vomiting, dizziness) did not differ significantly across CYP3A4 groups.
Zhang et al reported no association between CYP3A5*3 polymorphisms and 24-hour post-operative fentanyl consumption in 203 women following total abdominal hysterectomy or myomectomy (Zhang, 2011).
Genetic Variants and Analgesic Requirements: Other Gene Associations
While the largest body of research related to the clinical validity of genetic testing for pain management appears to be related to OPRM1 and CYP450 SNPs, the association of multiple other genes and response to analgesics has been reported.
Genetic Variants and Medication-Related AEs
Some studies have evaluated the association between genetic variants and medication-related AEs, which translate to a clinical use of dose optimization (to avoid an unwanted effect) OR to drug selection or avoidance (to identify individuals at high risk of AEs).
Genetic Variants and Medication-Related AEs: CYP2D6 and Respiratory Depression/CNS Depression
There has been particular interest in the evaluation of the role of CYP2D6 in the metabolism of codeine and other narcotics in children, particularly after tonsillectomy/adenoidectomy, and in nursing mothers after several cases of fatal overdoses. Codeine is metabolized to its active metabolite, morphine, via CYP2D6 activity. Individuals with higher than average CYP2D6 activity may have increased morphine formation, leading to higher toxicity risk, whereas those with lower than average CYP2D6 activity may have reduced morphine formation, leading to insufficient pain relief.
Madadi et al reported the results of a case-control study evaluating the association of maternal CYP2D6 polymorphisms and respiratory depression among infants of breastfeeding mothers treated with codeine (Madadi, 2009). The study included 72 mother-child pairs whose mothers used codeine while breastfeeding, of which 17 (24%) of breastfed infants were reported to exhibit central nervous system (CNS) depression while their mothers used codeine. CNS depression was by maternal report. Two (11.8%) mothers of symptomatic infants were CYP2D6 UMs (in combination with a UGT2B7*2/*2 genotype), compared with 0% of mothers among nonsymptomatic infants. Mothers of symptomatic cases were more likely to have a combined CYP2D6 UM and UGT2B7*2/*2 genotype than expected based on the average expected frequency (OR 8.4; 95% CI, 4.7 to 47; p<0.001).
Genetic Variants and Medication-Related AEs: CYP2D6 and Other AEs
The effect of CYP450 genotype on outcomes other than respiratory depression has also been evaluated. Prows et al conducted a prospective study to evaluate factors, including CYP26 genotype, associated with codeine-related adverse drug events in children following tonsillectomy (Prows, 2014). The study enrolled 249 children aged 5 to 19 scheduled to undergo tonsillectomy. Symptoms were recorded in a symptom diary. Of 134 children who were given codeine, 106 (79%) reported at least 1 AE, most commonly lightheadedness and dizziness in white children and nausea and vomiting in African American children. The presence of a high risk CYP2D6 gene (EM or IM), compared with a low risk CYP2D6 gene (IM or PM), was associated with a higher ADR risk (p=0.044).
Candiotti et al evaluated the association of CYP2D6 gene copy number and the presence of postoperative nausea and vomiting after prophylaxis with the antiemetic ondansetron among 243 women undergoing general anesthesia (Candiotti, 2005). Eighty-eight women experienced postoperative nausea and/or vomiting requiring breakthrough medication. Metabolizer status based on number of functioning CYP2D6 copy numbers (PM, IM, EM, UM) was significantly associated with vomiting incidence, with vomiting occurring in 5/11 UMs (45.5%), compared with 1/12 PMs (8.3%), 5/30 IMs (16.7%), and 26/176 EMs (14.7%) (p=0.007 for UMs vs all other groups). However, nausea was not associated with genotype.
Genetic Variants and Medication-Related AEs: OPRM1 and Fentanyl-Associated Nausea and Vomiting
The association of other genes with analgesic-related AEs has also been reported. Zhang et al evaluated the association between the OPRM1 A118G polymorphism and fentanyl-associated postoperative nausea and vomiting among 165 women undergoing elective total abdominal hysterectomy or myomectomy who received fentanyl intravenous PCA post-operatively (Zhang, 2011). The study found no statistically significant differences between genotype groups in terms of frequencies or scores of nausea and vomiting. Tsai et al evaluated the association between the OPRM1 A118G polymorphism and pruritus associated with epidural morphine used for postoperative analgesia among 212 women who received epidural morphine for post-Caesarian section analgesia (Tsai, 2010). Pruritus was evaluated by the Itching Severity Scale (ISS 0–4), with significant pruritus considered to be an ISS score of 2 to 4. Among the 25 patients with OPRM1 genotype of GG, 3 (12%) had pruritus with ISS grade 2 to 4, while among the 187 patients with OPRM genotype AA or AG, 59 (31.6%) had significant pruritus (p=0.031). While this suggesting that OPRM1 genotype is associated with morphine-related pruritus, the study does not report morphine dose requirements for the different genotypes, making it difficult to exclude confounding by drug dose.
Genetic Variants and Addiction Risk
A number of studies have reported on the association between various genes and risk of addiction to or abuse of opioid pain medications and nonprescription opioids and other nonprescription substances, with some overlap between the two categories. Studies with a focus on genes associated with risk of addiction to or abuse of prescription medications, rather than cocaine, nicotine, or other substances, are outlined next. These studies would translate to a clinical use of drug selection or avoidance (to identify individuals in whom opioids should be used with caution). Other studies have evaluated the role of genotype in the efficacy of methadone therapy for a variety of addictions; while there is likely overlap between the genes involved in methadone metabolism and response and those involved in the metabolism and response of other opioids, studies evaluating methadone as a treatment for addiction are not included here.
Genetic Variants and Addiction Risk: OPRM1 and Opioid Dependence
In 2013, Haerian et al published a meta-analysis of studies evaluating the association between the OPRM1 A118G (rs1799971) polymorphism and opioid dependence (Haerian, 2013). The authors identified 13 studies including 9385 subjects (N=4601 with opioid dependence and N=4784 controls), which reported OPRM1 genotypes for cases and controls. Most of the included studies (N=17) evaluated dependence on heroin, while the remaining evaluated dependence on opioids in general or opioids and cocaine. In pooled analysis of all included studies, the presence of the A allele (compared with the G allele) was not significantly associated with heroin dependence risk (pooled odds ratio [OR]=0.95; 95% CI, 0.77 to 1.17). In pooled analysis evaluating risk of addiction to all opioids (excluding African-American subjects), the presence of the AA or AG genotype (compared with the GG genotype) was significantly associated with opioid dependence (pooled OR=0.78; 95% CI, 0.63 to 0.97). The authors conclude that OPRM1 polymorphisms may be associated with opioid dependence among Asians.
In 2009, Coller et al published a meta-analysis of case-control studies evaluating the association between the OPRM1 A118G SNP allelic and genotypic frequencies and opioid dependence (Coller, 2009). The authors included 16 case-control studies (including 5169 subjects), which reported A118G genotype frequencies, included a group with opioid dependence and a control group, and had genotype samples which were in Hardy-Weinberg equilibrium. Similar to the Haerian et al meta-analysis, most studies (N=11) included evaluated the association between A118G genotype and heroin dependence, with 5 studies reporting associations with opioids in general. In pooled analysis, no difference in A118G SNP genotype frequencies between opioid-dependent and control groups was observed, with a pooled OR of 1.28 (95% CI, 0.77 to 2.11; p=0.34). No difference in A118G SNP allelic frequencies between opioid-dependence and control groups was observed, with a pooled OR of 1.16 (95% CI, 0.91 to 1.47; p=0.23).
Other earlier meta-analyses of OPRM1 A118G SNP and substance dependence similarly reported no significant association between A118G SNPs and dependence (Glatt, 2007; Arias, 2006).
Section Summary
The evidence on the clinical validity of pharmacogenetic testing for pain management is characterized by a large number of studies that evaluate associations of many different genetic variants and response to analgesic medication, risk of AEs, and addiction risk. For tests that are available in currently-available genetic panel tests, the largest body of evidence is related to the association of the OPRM1 A118G SNP with analgesic response and addiction risk. Studies evaluating OPRM1’s role in analgesic response are generally relatively small cross-sectional studies conducted in the postoperative setting and have had mixed findings, with some studies showing an association between OPRM1 genotype and analgesic dose and/or measures of pain intensity, and others showing no significant association. Results of several meta-analyses have not consistently demonstrated an association between OPRM1 polymorphisms and addiction risk.
For other genes, the body of evidence evaluating associations between polymorphism and analgesic response, AEs, or addiction risk is small.
Clinical Utility
Pharmacogenetic testing for pain management has a potential role for clinical utility in several settings, including drug selection or avoidance or in dose optimization. For drug selection, pharmacogenetic testing could potentially be used to identify individuals not likely to respond to a particular drug, or to identify individuals at high risk of an adverse drug reaction. For dose optimization, pharmacogenetic testing could potentially be used to identify individuals who are likely to be sensitive or resistant to a particular drug, or to estimate dose and dosing frequency.
For a testing for a given gene or panel of genes to demonstrate clinical utility, evidence is needed that testing for genetic variants leads to changes in clinical management that improve outcomes, such as improved pain control, shorter time to pain control, reduced frequency of AEs, or reduced rates of addiction. No published studies were identified that reported management changes or patient outcomes for patients managed with pharmacogenetic testing for pain management. Therefore, the clinical utility of such testing cannot be determined.
Ongoing and Unpublished Clinical Trials
A search of online database ClinicalTrials.gov in December 2014 identified several ongoing studies related to genetic testing for pain management that are currently enrolling subjects:
· Predisposition to Persistent Pain After Orthopaedic Surgery: Genetic Aspects (NCT01989351) – This is an observational study to assess the relationship between several genetic polymorphisms (ADBR2, OPRM1, COMT, IL1Ra) and the presence of persistent pain 4 months after orthopedic surgery. Enrollment is planned for 130 subjects; the estimated study completion date is March 2015.
· Acute Pain Genomic Study (NCT01557751) – This is a GWAS to evaluate the association of genetic markers and acute perioperative pain following total knee arthroplasty. Enrollment is planned for 400 subjects; the estimated study completion date is December 2015.
· A Prospective Trial to Identify Biomarkers Involved in the Transition From Acute to Persistent Chronic Low Back Pain (NCT02037763) – This is a prospective observational cohort study to evaluate genetic polymorphisms associated with the presence of persistent low back pain in patients presenting with an episode of acute low back pain. Enrollment is planned for 5000 subjects; the estimated study completion date is August 2018.
· Utility of PharmacoGenomics for Reducing Adverse Drug Effects (UPGRADE) (NCT02081872) – This is an observational cohort study to assess whether pharmacogenomic testing is associated with changes in how physicians manage patient medication regimens and changes in rates of adverse drug reactions, hospitalizations, and emergency department visits. The enrollment target is not specified; the estimated study completion date is July 2017.
· Pharmacogenomics Analysis of Morphine Pharmacokinetics in Pediatric Tonsillectomy and Adenoidectomy (NCT00836264) – This is an observational cohort study to assess whether gene polymorphisms are associated with variability in response to morphine among pediatric patients who undergo outpatient tonsillectomy/adenoidectomy. Enrollment is planned for 1650 subjects; the estimated study completion date is December 2017, with follow-up through June 2018.
Summary of Evidence
Panels of genetic tests for genes that have shown some association with the pharmacokinetics or pharmacodynamics of analgesic medications have been developed to aid in the management of pain. The evidence on the clinical validity of pharmacogenetic testing for pain management is characterized by a large number of studies that evaluate associations of many different genetic variants and response to analgesic medication, risk of adverse events, and addiction risk. The largest body of evidence is to be related to the association of the OPRM1 A118G single nucleotide polymorphism with analgesic response and addiction risk, which have not consistently demonstrated significant associations. For other genes included in commercially-available pain management panels, the body of evidence evaluating associations between polymorphism and analgesic response, adverse effects, or addiction risk is small.
At present, the clinical utility of pharmacogenetic testing in pain management is poorly defined. No published studies were identified that report on ways that clinical management of pain and/or patient outcomes are associated with pharmacogenetic testing.
Clinical Pharmacogenetics Implementation Consortium
In 2012, the Clinical Pharmacogenetics Implementation Consortium issued guidelines for the management of codeine therapy in the context of CYP2D6 genotype, which were updated in 2014 to reflect U.S. Food and Drug Administration (FDA) labeling about codeine in children status post tonsillectomy with or without adenoidectomy and to include other opioids metabolized by CYP2D6 (Crews, 2012; Crews, 2014).
American Academy of Neurology
In 2014, the American Academy of Neurology published a position paper on the use of opioids for chronic noncancer pain (Franklin, 2014). Regarding pharmacogenetic testing, the guidelines state that genotyping to determine whether response to opioid therapy can or should be more individualized is an emerging issue that will “require critical original research to determine effectiveness and appropriateness of use.”
2017 Update
A literature search conducted using the MEDLINE database through November 2017 did not reveal any new information that would prompt a change in the coverage statement. The key identified literature is summarized below.
Gammal et al (2016) reported on the feasibility of implementing a pre-emptive genetic test for CYP2D6 metabolizer status into their electronic clinical decision support system to guide prescribing of codeine with the goal of preventing its use after tonsillectomy or adenoidectomy and in CYP2D6 UM and PM (high-risk) genotypes (Gammal, 2016). The authors did not report on any clinical outcomes, and did they report any outcomes pre or post implementation of the clinical decision support system for genetic testing for CYP2D6. Results were reported for a subset of 621 patients with sickle cell disease who had a CYP2D6 genotype result. Of these, 7.1% were UMs or possible UMs, and 1.4% were PMs. None of the patients with an UM or PM genotype were prescribed codeine. The authors acknowledged the need for future studies to demonstrate the impact of their genetic testing algorithm on clinical end points such as adverse effects and pain control.
Senagore et al (2017) reported on results of a prospective cohort study of 50 consecutive patients undergoing open or laparoscopic colorectal and major ventral hernia surgery (Senagore, 2017). Prior to surgery, all patients underwent genetic testing using the NeuroIDgenetix pain panel that that analyzes 9 genes, including CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4/ CYP3A5, ABCB1, COMT, and OPRM1. Results of the panel were reported along with a list of medications classified as “Use as Directed” or “Use with Caution and/or Increased Monitoring.” Investigators used these results to guide selection of analgesics using a standard 1-to-10 VAS pain score in accordance with the results of genetic panel results. The primary outcome measure was Overall Benefit of Analgesia Score (OBAS), which assesses the combined impact on analgesia, patient satisfaction, and the impact of drug-associated side effects. The lower the score, the better is overall analgesia. The authors compared the findings with a historical cohort of 47 patients who underwent similar surgeries but were managed with standard enhanced recovery protocol. Results showed that OBASs were significantly lower in patients managed via genotype testing than those given no testing on postoperative day 1 (3.8 vs 5.4; 1.8 vs 2.3) and day 5 (3.0 vs 4.5; 1.2 vs 2.0), all respectively (all p<0.05). Need for narcotic-equivalent analgesics in the genotype tested group was lower in the group of genotype-tested patients (104.5 mg, SD=122.1) than in the historical controls (222.1 mg, SD=221.1;p<0.05). Although the authors reported that the 2 groups were similar in terms of patients characteristics, details of disease status and other known prognostic factors were lacking in the published paper. The authors did not report how the historical cohort was selected nor did they describe efforts to control for known confounders using statistical adjustments. Furthermore, no attempt was made to assess the magnitude of any specific genetic variant combinations on drug efficacy or potency in our study population. This study was funded by the test manufacturer. Thus, multiple methodologic limitations do not permit conclusions from this study.
The results of these studies do not affect the coverage intent of this policy. Because of the lack of established clinical validity, it is not possible to establish the clinical utility of genetic testing for pain management through a chain of evidence.
2018 Update
A literature search was conducted through November 2018. There was no new information identified that would prompt a change in the coverage statement.
2020 Update
Annual policy review completed with a literature search using the MEDLINE database through October 2020. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
According to an analysis of 2016 National Health Interview Survey (NHIS) data, an estimated 20.4% (50 million) U.S. adults experience chronic pain and 8% (19.6 million) have high-impact chronic pain (ie, pain that frequently limits life or work activities (Dahlhamer, 2018).
In February 2020, the FDA expressed "concerns with firms offering genetic tests making claims about how to use the genetic test results to manage medication treatment that are not supported by recommendations in the FDA-approved drug labeling or other scientific evidence" (USFDA, 2020). Due to these concerns, the FDA announced a collaboration between the FDA’s Center for Devices and Radiological Health and Center for Drug Evaluation and Research intended to provide the agency’s view of the state of the current science in pharmacogenetics. This collaborative effort includes a web resource, that describes "some of the gene-drug interactions for which the FDA believes there is sufficient scientific evidence to support the described associations between certain genetic variants, or genetic variant-inferred phenotypes, and altered drug metabolism, and in certain cases, differential therapeutic effects, including differences in risks of adverse events" (USFDA, 2020).
For chronic pain management, a multimodal, multidisciplinary approach that is individualized to the patient is recommended (USDHHS, 2019). A multimodal approach to pain management consists of using treatments (ie, nonpharmacologic and pharmacologic) from 1 or more clinical disciplines incorporated into an overall treatment plan. This allows for different avenues to address the pain condition, often enabling a synergistic approach that impacts various aspects of pain, including functionality. The efficacy of such a coordinated, integrated approach has been documented to reduce pain severity, improve mood and overall quality of life, and increase function.
The Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) recommends that chronic pain trials should consider assessing outcomes representing 6 core domains: pain, physical functioning, emotional functioning, participant ratings of improvement and satisfaction with treatment, symptoms and adverse events, and participant disposition (Dworkin, 2005).
Regarding optimal timing of outcome assessment, this varies with pain setting (Gewandter, 2015). Per IMMPACT, recommended assessment timing includes at 3, 6, and 12 months in patients with chronic low back pain, 3 to 4 months after rash onset in postherpetic neuralgia, 3 and 6 months in patients with painful chemotherapy-induced peripheral neuropathy, and at various timepoints in the chronic post-surgical pain setting (ie, 24 to 48 hours after surgery; 3, 6, and 12 months; or surgery-specific times based on the natural history of acute to chronic pain transition).
In 2020, the Clinical Pharmacogenomics Implementation Consortium published a guideline for CYP2C9 and NSAIDs, which was developed to provide interpretation of CYP2C9 genotype tests so that the results could potentially guide dosing and/or appropriate NSAID use (Theken, 2020). The guideline notes that CYP2C9 genotyping information may provide an opportunity "to prescribe NSAIDs for acute or chronic pain conditions at genetically-informed doses to limit long-term drug exposure and secondary adverse events for patients who may be at increased risk." However, the authors also acknowledge that "while traditional pharmacogenetic studies have provided evidence associating common CYP2C9 genetic variation with NSAID pharmacokinetics, there is sparse prospective evidence showing that genetically-guided NSAID prescribing improves clinical outcomes.
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2021. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Thomas et al completed a hybrid implementation-effectiveness randomized trial of CYP2D6-guided postoperative pain management versus usual care in 260 adults undergoing joint arthroplasty (Thomas, 2021). In this open-label trial, the authors evaluated the feasibility of clinically implementing CYP2D6-guided post-surgical pain management via the collection of feasibility metrics and pain control through measures of opioid consumption and pain intensity. In the genotype-guided arm, 20% had a high-risk phenotype (intermediate, poor, or ultrarapid metabolizer). Of these, 72% were administered an alternative opioid versus 0% of usual care participants (p<.001). Effectiveness outcomes were collected 2 weeks postsurgery and results of the exploratory analysis revealed reduced opioid consumption and similar pain intensity between the 2 groups.
Although Thomas et al reported a reduction in opioid consumption and similar pain control between the genotype-guided and usual care groups at 2 weeks postsurgical intervention, the evaluation of the clinical outcomes was exploratory in nature.
In 2021, the Consortium published an updated guideline for CYP2D6, μ-opioid receptor gene 1 (OPRM1), and catechol O-methyl-transferase (COMT) genotypes and select opioid therapy (Crews, 2021). These recommendations state that codeine and tramadol should be avoided in CYP2D6 poor metabolizers due to diminished efficacy and in ultra-rapid metabolizers due to toxicity potential. In both situations, if opioid use is warranted, a non-codeine opioid should be considered. Regarding hydrocodone, there is insufficient evidence and confidence to provide a recommendation to guide clinical practice for CYP2D6 ultra-rapid metabolizers. For CYP2D6 poor metabolizers, the use of hydrocodone label age- or weight-specific dosing is recommended; however, if no response is observed and opioid use is warranted, a non-codeine and non-tramadol opioid option is warranted. There is insufficient evidence and confidence to provide a recommendation to guide clinical practice at this time for oxycodone or methadone based on CYP2D6 genotype. Additionally, there are no therapeutic recommendations for dosing opioids based on either OPRM1 or COMT genotype.
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
Hamilton et al conducted a randomized trial of genotype-guided postoperative pain control compared to usual care in 107 patients who underwent hip or knee arthroplasty (Hamilton, 2022). All patients underwent preoperative genetic testing using a 16-gene panel, then patients were randomized in a single-blind manner to genotype-guided opioid therapy or usual care (oxycodone, tramadol, celecoxib, acetaminophen). Self-reported pain scores and opioid usage were recorded for 10 days after surgery. The gene panel showed that 22.4% of patients had relevant genetic variations. Among the patients with genetic variants, patients in the genotype-guided group consumed 86.7 mg morphine equivalents during the 10-day study period versus 162.6 mg morphine equivalents (p=.126). Ten-day average pain levels in both groups were 3.1 versus 4.2, respectively (p=.026).
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2023. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
During 2021, an estimated 20.9% (51.6million) of U.S adults experienced chronic pain and 6.9% (17.1 million) had high-impact chronic pain (i.e., chronic pain that limits daily activities) (Rikard, 2023).
Genelex offers several pharmacogenomic panels, one of which (the YouScript® Analgesic Panel) focuses on genes relevant to pain management (Genelex, 2023)..
A prospective non-randomized pragmatic trial of 375 patients who either underwent a CYP2D6-guided approach to opioid prescribing for pain control at 4 primary care clinics or standard of care pain management at 3 clinics without assessment of CYP2D6 was conducted (Smith, 2019). Based on genotyping alone, 10% of the CYP2D6-guided group were considered intermediate or poor metabolizers (IM/PM). The percentage of patients who were considered IM or PM increased to 35% after drug interactions were considered. In the CYP2D6-guided IM/PM group, there was a more frequent change to a nonopioid therapy.
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Group specific policy will supersede this policy when applicable. This policy does not apply to the Wal-Mart Associates Group Health Plan participants or to the Tyson Group Health Plan participants.
CPT Codes Copyright © 2024 American Medical Association. |
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