Pharmacogenomic Testing

This LCD supplements but does not replace, modify or supersede existing Medicare applicable National Coverage Determinations (NCDs) or payment policy rules and regulations for pharmacogenomics testing. Federal statute and subsequent Medicare regulations regarding provision and payment for medical services are lengthy. They are not repeated in this LCD. Neither Medicare payment policy rules nor this LCD replace, modify or supersede applicable state statutes regarding medical practice or other health practice professions acts, definitions and/or scopes of practice. All providers who report services for Medicare payment must fully understand and follow all existing laws, regulations and rules for Medicare payment for pharmacogenomics testing and must properly submit only valid claims for them. Please review and understand them and apply the medical necessity provisions in the policy within the context of the manual rules. Relevant CMS manual instructions and policies may be found in the following Internet-Only Manuals (IOMs) published on the CMS Web site:

IOM Citations:

• CMS IOM Publication 100-02, Medicare Benefit Policy Manual,
  • Chapter 15, Section 80.1 Clinical Laboratory Services, Section 80.1.1 Certification Changes, Section 80.1.2 A/B MAC (B) Contacts With Independent Clinical Laboratories, Section 80.1.3 Independent Laboratory Service to a Patient in the Patient’s Home or an Institution, Section 80.6 Requirements for Ordering and Following Orders for Diagnostic Tests, Section 80.6.1 Definitions, and Section 280 Preventive and Screening Services
• CMS IOM Publication 100-03, Medicare National Coverage Determinations (NCD) Manual,
  • Chapter 1, Part 2, Section 90.1 Pharmacogenomic Testing to Predict Warfarin Responsiveness and Section 90.2 Next Generation Sequencing for Patients with Advanced Cancer
• CMS IOM Publication 100-08, Medicare Program Integrity Manual,
  • Chapter 13, Section 13.5.4 Reasonable and Necessary Provision in an LCD

Social Security Act (Title XVIII) Standard References:

• Title XVIII of the Social Security Act, Section 1861(ww)(1). This section defines the initial preventative physical examination which does not include laboratory tests.
• Title XVIII of the Social Security Act, Section 1861(xx)(1). This section defines cardiovascular screening blood test.
• Title XVIII of the Social Security Act, Section 1861(ddd)(1). This section defines additional preventative services. Section 1861(ddd)(2). This section describes the process for making national coverage determinations. Section 1861(ddd)(3). This section defines preventative services.
• Title XVIII of the Social Security Act, Section 1861(hhh) defines the annual wellness visit services.
• Title XVIII of the Social Security Act, Section 1862(a)(1)(A) states that no Medicare payment shall be made for items or services which are not reasonable and necessary for the diagnosis or treatment of illness or injury.
• Title XVIII of the Social Security Act, Section 1862(a)(7). This section excludes routine physical examinations.

Code of Federal Regulations (CFR) References:

• CFR, Title 42, Volume 2, Chapter IV, Part 410.32 Diagnostic x-ray tests, diagnostic laboratory tests, and other diagnostic tests: Conditions
• CFR, Title 42, Volume 2, Chapter IV, Part 410.64 Additional preventive services
• CFR, Title 42, Volume 2, Chapter IV, Part 411.15(k) Particular services excluded from coverage
• CFR, Title 42, Volume 5, Chapter IV, Part 493 Laboratory Requirements

Compliance with the provisions in this LCD may be monitored and addressed through post payment data analysis and subsequent medical review audits.

History/Background and/or General Information

Genetic testing holds the potential to provide great value in improving health outcomes for all individuals. The scope of this LCD includes testing to determine how genes affect the body's response to certain medicines, known as pharmacogenetic, or pharmacogenomic testing. Clinicians face a daunting task to individualize therapies to maximize beneficial outcomes and minimize adverse events and lack of effect. Pharmacogenomic (PGx) testing holds the hope of improved choice of drug therapy for multiple conditions for which drug therapy is appropriate.

A person’s genetic code can influence various steps in drug response. Examples of these steps where genetic variation may influence response include drug receptor type and number, increased or decreased drug uptake, and increased or decreased drug metabolism. Depending on the specific situation, these interactions can result in increased or decreased drug effectiveness as well as adverse drug reactions.

This LCD addresses single gene, multi-gene panels, and combinatorial tests aimed at determining an individual’s drug response.

Definitions

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

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

Covered Indications

Pharmacogenetics testing will be considered medically reasonable and necessary if:

1. The patient has a condition where clinical evaluation has determined the need for a medication that has a known gene-drug interaction(s) for which the test results would directly impact the drug management of the patient’s condition; AND

2. The test meets evidence standards for genetic testing as evaluated by a scientific, transparent, peer-reviewed process and determined to demonstrate actionability in clinical decision making by CPIC guideline level A or B¹; or is listed in the FDA table of known gene-drug interactions where data support therapeutic recommendations or a potential impact on safety or response or the FDA label; https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling; https://www.fda.gov/medical-devices/precision-medicine/table-pharmacogenetic-associations

Some panel/combinatorial tests may include content that has demonstrated actionability and some that has not. In these circumstances, the components of the tests that have demonstrated actionability as noted in #2 will be considered medically reasonable and necessary. Refer to the related billing and coding article for coding information.

Please refer to National Coverage Determination (NCD) 90.1 for anticoagulation dosing with warfarin.

Limitations

The following is considered not medically reasonable and necessary:

• Genetic testing where either analytical validity, clinical validity, or clinical utility has not been established.
• Germline testing may be performed once in a lifetime per beneficiary.
  • Any laboratory test that investigates the same germline genetic content, for the same genetic information, that has already been tested in the same Medicare beneficiary is not medically reasonable and necessary as it is duplicative. The germline sequence of an individual does not change over time, and therefore repeat testing of the same germline content for the same genetic information does not provide new clinical information.

Provider Qualifications

The ordering provider of a PGx test for a patient with a medical condition:

• Must be the treating clinician who is responsible for the pharmacologic management of the patient’s condition. The ordering provider of a PGx test is restricted to providers who have the licensure, qualifications, and necessary experience/training to both diagnose the condition being treated and to prescribe medications (the provider must be able to do both) for the condition either independently or in an arrangement as required by all the applicable state laws; and
• is considering or has already prescribed a pharmacologic treatment with actionable gene-drug interactions; and
• understands the actionability of the ordered test.

Notice: Services performed for any given diagnosis must meet all of the indications and limitations stated in this LCD, the general requirements for medical necessity as stated in CMS payment policy manuals, any and all existing CMS national coverage determinations, and all Medicare payment rules.

Introduction

The purpose of this evidence review is to examine genetic testing used to inform drug therapies and determine if the evidence is sufficient to draw conclusions about better health outcomes for the Medicare population. Generally, key health outcomes include patient survival and disease incidence, along with quality of life and daily functioning. A standardized assessment of analytical validity, clinical validity, and clinical utility should be thoroughly explained and should indicate the confidence level that the test's performance will directly benefit patients. Tests that prove analytical and clinical validity, along with demonstrated clinical utility that inspires confidence in enhancing clinician decision-making, have the potential to change clinical management and improve patient outcomes. Optimal patient outcomes show reduced mortality and morbidity, as well as enhanced quality of life and functionality.

Pharmacogenomic (PGx) testing aims to enhance patient outcomes by optimizing medication selection, thus minimizing ineffective medication use and reducing adverse events. The desired outcomes remain the same patient-centered results mentioned above.

Internal Technology Assessment

The U.S. sources of PGx test recommendations available to provide guidance to clinicians as to how available genetic test results should be interpreted for drug therapy improvement include the U.S. FDA drug labels, FDA Table of Pharmacogenetic Associations, and the CPIC.

Hertz 2024

This narrative review article investigates the current status of PGx testing recommendations within clinical practice guidelines (CPGs) in the United States. The authors aim to understand how PGx testing is integrated into these guidelines, focusing on 21 gene-drug pairs that are recognized as clinically actionable by CPIC¹.

The methodology involved a targeted review of CPGs from U.S.-based clinical organizations. The selection of guidelines was informed by subject matter experts in various therapeutic areas, ensuring that the most prominent guidelines for each gene-drug pair were included. Although a systematic search for all possible CPGs was not conducted due to practical challenges, the review focused on those guidelines that explicitly discussed PGx testing. The article does not involve new clinical trials or participant recruitment but rather synthesizes existing guidelines and the evidence they present.

The authors identified inconsistencies both within and between organizations regarding PGx testing recommendations, particularly in how different guidelines approach the same gene-drug pairs. For instance, while some guidelines consistently recommend testing, such as HLA-B*57:01 before abacavir therapy, others show variability, like those for CYP2C19 with clopidogrel. This variability underscores the need for a more standardized approach to evaluating the clinical utility of PGx testing¹.

In conclusion, the article calls for more consistent inclusion of PGx testing recommendations in CPGs, suggesting that such consistency could enhance clinical adoption of PGx testing and ultimately improve patient outcomes. The review highlights the importance of a standardized methodology for evaluating the evidence that supports these recommendations, which could help align guidelines across different clinical organizations¹.

Morris 2022

The systematic review analyzed 108 studies evaluating the cost-effectiveness of PGx testing for drugs with CPIC guidelines. The review found that 71% of these studies demonstrated PGx-guided treatment to be either cost-effective (44%) or cost-saving (27%), with the majority of these studies (87%) being of high quality as indicated by a Quality of Health Economic Studies (QHES) score of 75 or higher. Specifically, the drugs clopidogrel and warfarin were the most studied, with 96% of clopidogrel-related studies showing cost-effectiveness or cost-saving outcomes². In contrast, only 44% of warfarin studies showed cost-effectiveness, with none reporting cost savings².

Moreover, the review highlighted that the majority of studies (69%) were based on hypothetical populations, and most were conducted in North America (47%) and Europe (24%)². The findings underscore that while PGx testing is generally considered cost-effective or cost-saving, there are significant variations depending on the drug, gene, and study design. Additionally, studies from Asia were more likely to report PGx testing as not cost-effective (36%), suggesting geographical and methodological factors may influence cost-effectiveness outcomes². This variability emphasizes the need for region-specific evaluations when considering the adoption of PGx testing in clinical practice².

Caudle 2016

This study addresses the slow integration of pharmacogenetics into clinical practice despite considerable scientific advancements. One significant barrier is the uncertainty around the necessary evidence threshold for applying genetic test results to patient care. Large randomized controlled trials (RCTs) are often impractical or unnecessary for many pharmacogenetic applications, particularly when robust mechanistic evidence exists³. The authors note that, in many cases, clinical decisions can be made based on pharmacokinetic studies and other forms of evidence without requiring extensive RCTs³.

The study highlights the crucial role of resources like CPIC and the Pharmacogenomics Knowledgebase (PharmGKB). These platforms provide evidence-based guidelines that help clinicians translate genetic test results into actionable prescribing recommendations³. By offering standardized approaches to evaluate the literature, CPIC and PharmGKB facilitate the application of pharmacogenetic knowledge in clinical settings, ensuring that genetic information is used effectively in patient care³.

A key component of the study is the discussion of CPIC's level system, detailed in a table below. The CPIC levels range from A to D, categorizing the strength of evidence and recommendations for using genetic information in prescribing decisions³. Level A represents the highest confidence, where genetic information should be used to alter prescribing, while Level D indicates insufficient evidence or conflicting data, suggesting no need for action³. This classification system helps clinicians make informed decisions about when and how to incorporate pharmacogenetic data into their practice³.

In conclusion, the study underscores the importance of standardized guidelines and evidence-based resources in advancing the implementation of pharmacogenetics in clinical practice³. By using tools like CPIC and PharmGKB, clinicians can navigate the complexities of genetic data, making informed decisions that enhance patient outcomes³. The transparent and dynamic nature of these guidelines allows for continuous refinement as new evidence emerges, supporting the broader integration of precision medicine into healthcare³. CPIC levels of evidence for genes and drugs, Table 1:

Table 1. CPIC Level Definitions for Genes and Drugs

Caudle 2014

This article reviews the development and implementation of CPIC guidelines, which are designed to integrate pharmacogenomic data into clinical practice. The authors provide an overview of the CPIC guideline development process, highlighting the systematic approach used to translate genetic test results into actionable prescribing decisions4. The review compares this process with the Institute of Medicine’s (IOM) standards for developing trustworthy CPGs, emphasizing areas of alignment and opportunities for improvement4.

The CPIC guidelines focus on well-established gene-drug pairs with strong evidence linking genetic variations to drug response4. Each guideline follows a standardized format that includes a rigorous review of scientific literature, grading of evidence, and assignment of the strength of recommendations4. The guidelines are designed to help clinicians interpret patient-specific genetic information and apply it to optimize drug therapy, without advising on whether genetic testing should be conducted4.

The article identifies several key challenges and considerations in the guideline development process, such as managing conflicts of interest and ensuring transparency4. The authors also discuss the importance of electronic health records (EHRs) and clinical decision support (CDS) systems in facilitating the use of CPIC guidelines in clinical settings4. To this end, efforts are being made to enhance the machine-readability of these guidelines, enabling seamless integration with EHRs4.

In conclusion, the authors emphasize the critical role of CPIC guidelines in advancing the clinical adoption of pharmacogenomics4. They call for continued efforts to refine the guideline development process, address existing challenges, and expand the reach of these guidelines to improve patient outcomes4.

U.S. Food and Drug Administration (FDA)

The FDA describes pharmacogenetic testing as a critical tool in personalizing medical treatment by identifying patients who are likely to respond well or poorly to specific medications5. This testing helps to avoid adverse drug reactions and optimizes drug dosing by taking into account individual genetic variations5. Pharmacogenomic information is integrated into drug labeling and may provide insights into the variability of drug exposure and clinical responses, the risk of adverse events, and the need for genotype-specific dosing5. Additionally, it can inform the mechanisms of drug action, highlight polymorphic drug target and disposition genes, and guide trial design features5.

The FDA's approach to pharmacogenomic information in drug labeling is nuanced, allowing for its inclusion in various sections depending on the specific actions required based on the biomarker data5. This information may pertain to germline or somatic gene variants, functional deficiencies with a genetic origin, gene expression differences, and chromosomal abnormalities5. Selected protein biomarkers that play a role in treatment decisions are also included5. However, the FDA excludes non-human genetic biomarkers, those used exclusively for diagnostic purposes unrelated to drug activity, and biomarkers linked to drugs other than the one in question5.

The FDA recognizes the significant advancements and potential benefits of genetic testing, particularly in informing individuals about their health risks and guiding medical decisions6. Direct-to-consumer genetic tests are becoming increasingly popular among consumers seeking insights into their ancestry or disease risks, while healthcare providers use genetic testing to tailor patient care6. Pharmacogenetics, a field exploring the role of genetics in drug response, is particularly promising, with some drugs like clopidogrel (Plavix) having established links between genetic variants and drug efficacy6. However, the FDA warns against the use of pharmacogenetic tests that have not undergone FDA review, as they may lack the necessary scientific and clinical evidence to support their claims, potentially leading to harmful changes in patient treatment6.

The FDA is particularly concerned about unapproved genetic tests marketed directly to consumers or offered through healthcare providers that claim to predict a patient's response to specific medications6. Such tests may inaccurately suggest changes in drug treatment based on unsubstantiated genetic links, posing serious health risks6.

In 2018, the FDA issued a warning regarding the use of genetic tests that claim to predict a patient's response to specific medications, emphasizing that many of these tests lack FDA review and scientific support7. The agency is concerned that such tests, which may be marketed directly to consumers or through healthcare providers, could lead to inappropriate treatment decisions and potentially serious health consequences7. For instance, some tests claim to determine the effectiveness of antidepressants based on genetic variations, but the FDA has found no established link between DNA variations and the efficacy of these medications7. The agency advises patients and healthcare providers not to alter medication regimens based on the results of unverified genetic tests7.

In 2023, the FDA issued a draft guidance intended for industry stakeholders involved in drug development and aims to provide updated recommendations on the submission of pharmacogenomic data to the FDA8. The agency's expectations for pharmacogenomic data submissions in drug development are centered on four key themes: relevance to drug safety and efficacy, level of detail in reporting, integration into regulatory processes, and standardization of data formats8.

The FDA emphasized the importance of submitting pharmacogenomic data that is directly relevant to understanding a drug's safety profile or efficacy8. This includes findings that indicate substantial differences in treatment response across genomic subgroups, identify significant safety risks in certain populations, or relate to the drug's mechanism of action or pharmacokinetics8. The agency requires detailed reports for genomic biomarkers used in clinical trial design or analysis, and expects sponsors to submit data on biomarkers proposed for inclusion in drug labeling8. This focus on relevance ensures that the submitted pharmacogenomic information contributes meaningfully to the overall evaluation of the drug's benefits and risks8.

Coverage of items and services in the Medicare program is based on reasonable and necessary services, operationalized through the application of evidentiary standards. These standards carefully balance benefits and harms in considering net health outcomes.

Pharmacogenomic (PGx) testing has emerged as a potentially valuable tool in personalizing medical treatment. However, its integration into clinical practice faces several challenges. The rapidly evolving nature of PGx knowledge and testing approaches necessitates a careful evaluation of its use in improving health outcomes for Medicare patients.

To be considered medically reasonable and necessary for coverage, PGx tests must demonstrate analytical validity, clinical validity, and clinical utility. However, these factors alone are insufficient to guarantee improved health outcomes. The test results must be actionable and successfully integrated into patient care by clinicians.

Several key issues complicate the widespread adoption of PGx testing:

1. Inconsistencies in recommendations: As highlighted by Hertz 2024, there are variations in PGx testing recommendations both within and between clinical practice guidelines (CPGs). This inconsistency can create confusion for clinicians and potentially lead to differential health outcomes across patient populations.

2. Evidence threshold debate: Caudle 2016 notes the ongoing controversy regarding the necessary evidence threshold for clinical application of PGx testing. While large randomized controlled trials (RCTs) are often impractical, alternative study designs must still maintain rigorous standards to demonstrate improved health outcomes.

3. Cost-effectiveness variability: Morris 2022 shows that while many PGx tests are cost-effective or cost-saving, outcomes vary significantly depending on the drug, gene, and study design. This variability emphasizes the need for careful evaluation of each PGx application.

4. Clinical implementation challenges: Caudle 2014 highlights the importance of standardized guidelines and resources like CPIC in translating genetic test results into actionable prescribing decisions. However, the integration of these guidelines into electronic health records and clinical decision support systems remains an ongoing process.

5. Regulatory concerns: The FDA has issued warnings about unapproved genetic tests that claim to predict medication responses without sufficient scientific evidence. This underscores the need for rigorous validation of PGx tests to ensure patient safety.

Given these considerations, a standardized, rigorous approach to evaluating PGx testing evidence is crucial. The CPIC guidelines, which align with the Institute of Medicine's standards for developing trustworthy clinical practice guidelines, provide a reliable framework for assessing gene-drug interactions and their clinical actionability.

Additionally, the FDA's guidance on pharmacogenomic information in drug labeling offers a trusted source of information on how genetic variations may impact drug safety and effectiveness. The FDA Table of Pharmacogenetic Associations provides validated gene-drug interactions that can inform clinical decision-making.

In conclusion, while PGx testing shows promise in improving patient outcomes, its adoption in the Medicare population requires careful consideration of the evidence. At present, only the FDA label (including the FDA Table of Pharmacogenetic Associations) and CPIC guidelines meet the necessary criteria for rigorous, standardized evaluation of PGx testing. These sources provide the most reliable basis for coverage determinations, ensuring that PGx testing is used in a manner that is most likely to improve health outcomes for Medicare beneficiaries.

Please refer to the related Local Coverage Article: Billing and Coding: Pharmacogenomics Testing (A58801) for documentation requirements, utilization parameters and all coding information as applicable.

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1. Hertz DL, Bousman CA, McLeod HL, et al. Recommendations for pharmacogenetic testing in clinical practice guidelines in the US. Am J Health-Syst Pharm. 2024;81(16):672-683. doi:10.1093/ajhp/zxae110.
2. Morris SA, Alsaidi AT, Verbyla A, Cruz A, Macfarlane C, Bauer J, Patel JN. Cost Effectiveness of Pharmacogenetic Testing for Drugs with Clinical Pharmacogenetics Implementation Consortium (CPIC) Guidelines: A Systematic Review. Clin Pharmacol Ther. 2022;112(6):1318-1327. doi:10.1002/cpt.2754.
3. Caudle KE, Gammal RS, Whirl-Carrillo M, Hoffman JM, Relling MV, Klein TE. Evidence and resources to implement pharmacogenetic knowledge for precision medicine. Am J Health Sys Pharm. 2016;73(23)1977-1985. doi:10.2146/ajhp150977.
4. Caudle KE, Klein TE, Hoffman JM, et al. Incorporation of pharmacogenomics into routine clinical practice: the Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline development process. Curr Drug Metab. 2014;15(2):209-217. doi:10.2174/1389200215666140130124910.
5. U.S. Food and Drug Administration. Table of Pharmacogenomic Biomarkers in Drug Labeling. 2024. https://www.fda.gov/drugs/science-and-research-drugs/table-pharmacogenomic-biomarkers-drug-labeling. Accessed August 27, 2024.
6. U.S. Food and Drug Administration. FDA Statement: Jeffrey Shuren, M.D., J.D., Director of the FDA’s Center for Devices and Radiological Health, and Janet Woodcock, M.D., Director of the FDA’s Center for Drug Evaluation and Research on the Agency’s Warning to Consumers About Genetic Tests That Claim to Predict Patients’ Responses to Specific Medications. Published April 4, 2019. Accessed August 27, 2024. https://www.fda.gov/news-events/press-announcements/jeffrey-shuren-md-jd-director-fdas-center-devices-and-radiological-health-and-janet-woodcock-md.
7. U.S. Food and Drug Administration. The FDA Warns Against the use of Many Genetic Tests with Unapproved Claims to Predict Patient Response to Specific Medications: FDA Safety Communication. 2018. https://www.fda.gov/medical-devices/safety-communications/fda-warns-against-use-many-genetic-tests-unapproved-claims-predict-patient-response-specific#actions. Archived in 2020. Accessed August 27, 2024 via archival link.
8. U.S. Food and Drug Administration. Pharmacogenomic data submissions: draft guidance for industry. Silver Spring, MD: U.S. Food and Drug Administration; March 2023. https://www.fda.gov/media/166258/download. Accessed August 27, 2024.
9. U.S. Food and Drug Administration. Pharmacogenomics: Overview of the Genomics and Targeted Therapy Group. 2018. https://www.fda.gov/drugs/science-and-research-drugs/pharmacogenomics-overview-genomics-and-targeted-therapy-group. Accessed August 27, 2024.
10. Shugg T, Pasternak AL, London B, Luzum JA. Prevalence and types of inconsistencies in clinical pharmacogenetic recommendations among major U.S. sources. NPJ Genom Med. 2020;5:48. doi:10.1038/s41525-020-00156-7.
11. Roden DM, McLeod HL, Relling MV, et al. Pharmacogenomics. Lancet. 2019;394(10197):521-532. doi:10.1016/S0140-6736(19)31276-0.
12. National Human Genome Research Institute. Coverage and Reimbursement of Genetic Tests. 2019. https://www.genome.gov/. Accessed November 5, 2020.
13. Manolio TA, Rowley R, Williams MS, et al. Opportunities, Resources, and Techniques for Implementing Genomics in Clinical Care. Lancet. 2019;394(10197):511-520. doi:10.1016/S0140-6736(19)31140-7.
14. Peterson JF, Roden DM, Orlando LA, Ramirez AH, Mensah GA, Williams MS. Building evidence and measuring clinical outcomes for genomic medicine. Lancet. 2019;394(10198):604-610. doi:10.1016/S0140-6736(19)31278-4.
15. National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Health Care Services; Board on the Health of Select Populations; Committee on the Evidence Base for Genetic Testing. An Evidence Framework for Genetic Testing. Washington (DC): National Academies Press (US); 2017 Mar 27. https://doi.org/10.17226/24632.
16. Institute of Medicine (US) Committee on Standards for Developing Trustworthy Clinical Practice Guidelines. Clinical Practice Guidelines We Can Trust. Graham R, Mancher M, Miller Wolman D, Greenfield S, Steinberg E, editors. Washington (DC): National Academies Press (US); 2011.
17. Clinical Pharmacogenetics Implementation Consortium (CPIC). Guidelines. 2024: https://cpicpgx.org/. Accessed August 27, 2024.

• Provider Education/Guidance