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  
  
** With advancement in science and technology comes the ability to incorporate
genetic testing for oncology biomarkers into clinical care, with the goal of
improved patient outcomes. The scope of this LCD is DNA and RNA genetic
testing in the practice of oncology in the Medicare population.  
  
As defined by the Food and Drug Administration (FDA) and National Institutes
of Health (NIH) Biomarker Working Group, a biomarker is "A defined
characteristic that is measured as an indicator of normal biological
processes, pathogenic processes, or biological responses to an exposure or
intervention, including therapeutic interventions," and may include molecular,
histologic, radiographic, or physiologic characteristics.1 (p.45)  
  
Cancer is a disease caused by changes or alterations to a person's genome.
Some genetic changes or alterations can be inherited (also known as germline
mutations). About 5-10% of all cancer diagnoses result from germline
mutations, and over 50 hereditary cancer syndromes are known. Other cancer-
causing (oncogenic) genetic changes or alterations result from acquired
genetic damage (also known as somatic mutations). Somatic mutations can arise
in numerous scenarios, including exposure to chemicals that alter DNA
(carcinogens) or ultraviolet (UV) radiation from the sun.2  
  
Biomarker testing is a part of personalized laboratory medicine (also known as
precision medicine). Precision medicine is a tailored approach to medical care
and treatment. Because each patient has a unique combination of genetic
changes, and therefore, a unique pattern of biomarkers, precision medicine for
oncology involves the use of biomarker testing to pinpoint the disease
management needs of individual patients (and avoid the use of treatments which
are unlikely to be successful).3 Much of this testing involves direct
evaluation of the genetics of the malignancy through various testing
methodologies. These methodologies can include high level genetic evaluations
such as karyotyping (analysis of chromosomes) to more detailed evaluations
such as identifying specific pathogenic point variations (analysis of specific
nucleotide changes).  
  
Additionally, testing may be used to check for a single biomarker or multiple
biomarkers at the same time via a multigene test or panel.3 As a result, the
growing compendium of products described as biomarkers requires careful
evaluation to determine what testing configurations are medically reasonable
and necessary under Medicare.  
  
Biomarkers for oncology can be generally classified into four functional
types4:  
  

  1. **Diagnostic** biomarkers detect or confirm the presence of a disease or condition
  2. **Prognostic** biomarkers provide information about the likely course of a disease process and potential patient outcomes if left untreated
  3. ******Predictive** biomarkers forecast a patient's response and/or benefit to a specific treatment
  4. ******Therapeutic** biomarkers identify potential targets for a medical intervention (e.g., targeted drug therapy)

****

In certain circumstances, genetic testing for oncology biomarkers in patients
with the corresponding appropriate medical condition could have the potential
to assist patient management in the Medicare population. However, given the
complexity and rapidly expanding knowledge in this topic area, there is also a
potential for testing that does not help the patient or leads to confusion. In
order for services to be considered medically reasonable and necessary, they
must impact the management of the patient. Specialized clinical expertise in
oncology in addition to advanced knowledge in both genetic variation and
effect on gene function is required to facilitate optimal outcomes for
patients.  
  
 **Definitions  
  
** **Actionable use** describes a scenario when the genotype information
identified via genetic testing may lead to selection of or avoidance of a
specific intervention.  
  
 **Analytical validation** is a process intended to determine if a test, tool,
or instrument has acceptable technical performance (sensitivity, specificity,
accuracy, precision, etc.). Analytical validation is an assessment of the
test's technical performance (that it measures what it was intended to
measure), not its usefulness or clinical significance.1  
  
 **Clinical validity** is defined as the ability of a test to classify a
patient's specific circumstance into a diagnostic, prognostic, or predictive
functional category. It should be noted that clinical validity is not a fixed
value.5  
  
 **Clinical utility** can be defined as the ability of a test to provide
information related to the patient's care and management, and thus, its
ability to inform treatment decisions.5  
  
 **Covered Indications  
  
** Three evidence-based databases and/or knowledge bases have been identified
as valid and reliable sources. Note that a specific genetic test may be listed
in one database or knowledge base, but not others; therefore, providers may
choose to utilize guidelines from any of the three databases/knowledge bases.
However, **for services to be considered medically reasonable and necessary,
#1 below is required regardless of which guidelines are utilized.** Genetic
testing for oncology will be considered medically reasonable and necessary if:

****

  1. The provider has either established a diagnosis of cancer or found significant evidence to create suspicion for cancer in their patient via a clinical evaluation and abnormal results (cancer or suspicious for cancer) from histologic and/or cytologic examination. If then, as a next step in the clinical management of the patient, genetic testing would directly impact the management of the patient's condition, the testing would be indicated.

**AND ONE OF THE FOLLOWING:**

  2. The evidence for the gene-disease association is evaluated by the evidence-based, transparent, peer-reviewed process of the National Institutes of Health (NIH) sponsored Clinical Genome Resource (ClinGen)6 and is determined to demonstrate actionability in clinical decision making, **meeting the criteria for all 5 categories below.** At least **one** of the items listed under each of the categories (severity, likelihood of disease, effectiveness, nature of the intervention, and validity) must be satisfied:

  *     * **Disease severity equal to:**
      * Sudden death (Level 3), or
      * Possible death or major morbidity (Level 2), or
      * Modest morbidity (Level 1)
    * **Likelihood of disease equal to:**
      * Substantial evidence of a >40% chance (Level 3A), or
      * Moderate evidence of a >40% chance (Level 3B)
    * **Effectiveness equal to:**
      * Substantial evidence of a highly effective intervention (Level 3A), or
      * Moderate evidence of a highly effective intervention (Level 3B), or
      * Substantial evidence of a moderately effective intervention (Level 2A), or
      * Moderate evidence of a moderately effective intervention (Level 2B)
    * **Nature of the intervention is equal to:**
      * Low risk/medically acceptable/low intensity (Level 3), or
      * Moderately acceptable/risk/intensive (Level 2)
    * **Validity of the gene-disease relationship equal to:**
      * Definitive, or
      * Strong, or
      * Moderate

**OR**

****

  3. The evidence for the intervention is evaluated by the National Comprehensive Cancer Network (NCCN)7 and is determined to demonstrate actionability in clinical decision making, meeting the following metric: 
    * Based upon high-level evidence, there is uniform NCCN consensus that the intervention is appropriate (Category 1), or
    * Based upon lower-level evidence, there is uniform NCCN consensus that the intervention is appropriate (Category 2A)

**OR**

****

  4. The evidence for the intervention is evaluated by the Memorial Sloan Kettering Cancer Center-sponsored Oncology Knowledge Base (OncoKB)8 and is determined to demonstrate actionability in clinical decision making, meeting one of the following metrics: 
    * **For therapeutic use cases** : 
      * The intervention is an FDA-recognized biomarker predictive of response to an FDA-approved drug in this indication (Level 1)

**OR**

  *     *       * The intervention is a standard care biomarker recommended by the NCCN or other professional guidelines predictive of response to an FDA-approved drug in this indication (Level 2)

**OR**

  *     *       * The intervention is a standard care biomarker predictive of resistance to an FDA-approved drug in this indication (Level R1)  
  

  * **For diagnostic use cases** : 
    *       * The intervention is an FDA and/or professional guideline-recognized biomarker required for diagnosis in this indication (Level Dx1)

**OR**

  *     *       * The intervention is an FDA and/or professional guideline-recognized biomarker that supports diagnosis in this indication (Level Dx2)  
  

  * **For prognostic use cases** : 
    *       * The intervention is an FDA and/or professional guideline-recognized biomarker prognostic in this indication based on a well-powered study (or studies) (Level Px1)

**OR**

  *     *       * The intervention is an FDA and/or professional guideline-recognized biomarker prognostic in this indication based on a single study or multiple small studies (Level Px2)

****

**Limitations  
  
** The following are considered not medically reasonable and necessary:

  1. A genetic test where either analytical validity, clinical validity, or clinical utility has not been established.
  2. Interventions with levels of evidence not identified by either ClinGen, NCCN, or OncoKB as demonstrating actionability in clinical decision making as noted in Covered Indications.
  3. Genetic testing in patients who do not have either an established diagnosis of cancer or substantiated suspicion of cancer as determined by a clinical evaluation and abnormal results (cancer or suspicious for cancer) from histologic and/or cytologic examination.
  4. Genetic testing of asymptomatic patients for the purposes of screening the patient or their relatives.
  5. Repetitions of the same genetic test on the same genetic material.

Genetic tests for hereditary cancer syndromes, which are considered germline
testing, may only be performed once per beneficiary's lifecycle.  
  
 **Provider Qualifications  
  
** The following provider qualification requirements must be met for the
service to be considered medically reasonable and necessary. **The ordering
provider of a genetic test for a patient with an established diagnosis of
cancer or substantiated suspicion of cancer:  
**

  * Must be the treating clinician who is responsible for the management of the patient's cancer; and,
  * Understands how the test result will impact the patient's condition; and,
  * Has presented this information to the patient eliciting patient understanding.

**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  
  
** Please refer to the "History/Background and/or General Information" section
for general information on testing of RNA and DNA as it applies to oncology.  
  
This evidence review focuses on genetic testing used to guide oncologic
treatment and whether the evidence behind this testing is adequate to draw
conclusions about improved health outcomes for the Medicare population. In
general, health outcomes of interest include patient mortality, morbidity,
quality of life, and function.  
  
For use in the Medicare population, tests themselves must demonstrate analytic
validity, clinical validity, and clinical utility. Tests should enhance
clinical decision-making, directly informing clinical management and improving
patient outcomes.  
  
In the context of oncology, genetic testing endeavors to improve patient
outcomes through both prognostic and predictive means. For instance, oncologic
genetic testing can optimize treatment choice (predictive), avoiding
ineffective treatments and reducing adverse events. Ultimately, patient-
centered outcomes must be the underlying justification for oncologic testing.  
  
 **Internal Technology Assessment  
  
** PubMed and Google Scholar were searched for peer-reviewed, evidence-based
databases and/or knowledge bases which provide information regarding analytic
and clinical validity and clinical utility for genetic testing. As identified
in the Institute of Medicine's seminal work _Clinical Practice Guidelines:
Directions for a New Program_ _,_ 9 there are eight recommended attributes for
clinical practice guidelines. These include validity,
reliability/reproducibility, clinical applicability, clinical flexibility,
clarity, development via a multidisciplinary process, scheduled review, and
documentation. These attributes were referenced in the selection of
databases/knowledge bases for genetic testing.  
  
In order to be included, the database/knowledge base was required to be
evidence-based, widely available, and created and/or facilitated by an
organization with a focus on either oncology or genetics. Each
database/knowledge base was also required to include a scoring metric which
could be utilized to determine clinical actionability for specific genetic
tests. Additionally, the database/knowledge bases and their scoring metrics
were required to demonstrate the attributes listed in the _Clinical Practice
Guidelines_. All countries of origin were included as long as the
database/knowledge base met the criteria, with only sources in English
considered. Based on the above criteria, three databases/knowledge bases were
identified that ideally met the needs of this LCD.  
  
 **Databases and Knowledge Bases  
  
** **National Comprehensive Cancer Network (NCCN)  
  
** The NCCN is a nonprofit alliance of U.S. National Cancer Institute-
designated comprehensive cancer centers. NCCN strives to improve the
effectiveness and quality of care for patients with cancer and has published
clinical practice guidelines applying to more than 97% of cancers affecting
individuals in the U.S.10 According to the organization, their guidelines are
"intended to assist all individuals who impact decision-making in cancer care
including physicians, nurses, pharmacists, payers, patients and their
families, and many others."10 (p.1)  
  
In addition to a Guidelines Steering Committee (which provides oversight and
planning), and a Guidelines Panel Chair and Vice Chair (who provide oversight
of content development activities), each NCCN guideline has an individual
Guidelines Panel including multidisciplinary representation from all of the
core medical specialties relevant to the guideline, a primary care physician,
and a patient advocate. NCCN notes that "any Panel Member with a meaningful
conflict of interest is excluded from participating in Panel presentations,
reviews, discussions, and voting relevant to the area of the conflict of
interest."10(p.2)  
  
The development and update of NCCN guidelines is an ongoing process which
includes "critical evaluation of evidence, integrated with the clinical
expertise and consensus of a multidisciplinary panel of cancer specialists,
clinical experts and researchers in those situations where high-level evidence
does not exist."10 (p.5) Recommendations for treatment are based on the level
of clinical evidence available as well as consensus among the Guidelines Panel
regarding the efficacy and safety of the intervention. Active NCCN guidelines
are reviewed and updated at least annually.  
  
NCCN evidence and consensus categories are as follows: **Category 1** (high
level of evidence with uniform Panel consensus that the intervention is
appropriate); **Category 2A** (lower level of evidence with uniform Panel
consensus that the intervention is appropriate); **Category 2B** (lower level
of evidence with at least 50% [but less than 85%] panel consensus); and
**Category 3** (any level of evidence, but major Panel disagreement regarding
whether the intervention is appropriate).10 As discussed by Birkeland and
McClure, the majority of recommendations in the NCCN guidelines fall into
Category 2A "because high-level evidence is not available for most decisions
across the continuum of care." 11(p.608)  
  
Due to rapid development of biomarker and companion diagnostic testing in the
field of oncology, the NCCN Biomarkers Compendium was established "to
facilitate identification of biomarker tests recommended for use by NCCN
guideline panels." 11(p.609) As discussed by Birkeland and McClure11, the
Biomarkers Compendium "focuses on the clinical usefulness of biomarker testing
rather than specific tests or test kits,"11(p.611) and therefore includes all
tests measuring genes or gene products, regardless of their functional
category (predictive, prognostic, diagnostic, screening, monitoring,
surveillance). NCCN assigns a category of evidence and consensus to individual
alterations (as opposed to the entire gene). Furthermore, NCCN states
guideline recommendations (including those relative to the Biomarkers
Compendium) are "intended to apply to the vast majority of patients in a
particular clinical situation"10(p.6) and are therefore not exhaustive or
expected to apply to all patients or all situations.  
  
NCCN is a widely available resource, which is frequently utilized by
oncologists and other clinicians. Poonacha and Go discuss that clinical
practice guidelines published by NCCN are "the most comprehensive and widely
used standard in clinical practice in the world."12(p.187) In their study, the
authors investigated the level of scientific evidence behind NCCN guidelines
for the ten most common types of cancer in the U.S. (breast, prostate, lung
[both small-cell and non-small cell subtypes], colorectal, melanoma, non-
Hodgkin's lymphoma, kidney, pancreas, urinary bladder, and uterus). Of the ten
clinical practice guidelines reviewed, Poonacha and Go12 identified that on
average, guidelines contained over 100 intervention recommendations; the NCCN
lung cancer guideline included the most recommendations (238) while the kidney
cancer guideline had the least (45).  
  
Of the ten guidelines reviewed, most intervention recommendations (83%) were
from Category 2A, and only 6% were from Category 1.12 Categories of evidence
were found to be highly variable based on diagnosis; the authors identified
that the guidelines for kidney and breast cancers included the highest
proportion of recommendations with Category 1 evidence (20% and 19%,
respectively), eight of the cancer types had between 1% and 6% recommendations
with Category 1 evidence, and neither urinary bladder nor uterine cancer had
any recommendations with Category 1 evidence in their respective NCCN
guidelines. Poonacha and Go12 also noted that of the ten guidelines reviewed,
Category 3 evidence (major panel disagreement regarding whether the
intervention is appropriate) was rare.  
  
 **National Institute of Health funded Clinical Genome Resource (ClinGen)  
  
** The NIH-funded ClinGen was designed as an open-access resource to support
clinical decision making by aggregating, curating, and defining the clinical
relevance and actionability of gene-disease relationships.13 As an open-access
resource, ClinGen is publicly available to all clinicians and patients. Their
database "provides a structure to enable research and clinical communities to
make clear, streamlined, and consistent determinations of clinical
actionability based on transparent criteria to guide analysis and reporting of
genomic variation."14 ClinGen is also included in the FDA's Recognition of
Public Human Genetic Variant Databases.15  
  
ClinGen's consortium of experts includes a Steering Committee (responsible for
establishing standards and overseeing all ClinGen processes), a Clinical
Domain Working Groups Oversight Committee (responsible for overseeing the
development and approval of variant curation), and a Sequence Variant
Interpretation (SVI) workgroup (comprised of industry experts responsible for
providing guidance relevant to variant assessment activities, including
education tasks).13 ClinGen's Variant Curation Expert Panels (VCEPs) are
comprised of "individuals with scientific expertise regarding gene function,
clinical expertise regarding disease manifestations, and biocurators who are
trained in evaluating evidence sources that support a variant
assertion."13(p.2) VCEPs follow a standard operating procedure (SOP) during
the process of gene curation and assessment; this SOP is publicly available
via their website. Among other things, the SOP details the organization's
transparency and public accessibility (all variant assertions and summary
evidence are publicly available), as well as conflict of interest disclosures
(all conflicts are publicly declared).  
  
ClinGen has taken great measures to ensure staff involved in variant curation
and evaluation are adequately trained.13 ClinGen expects their VCEPs to
demonstrate the diversity of expertise in the field of genetics (including the
major areas of clinical, diagnostic laboratory, and research). While VCEPs
include disease/gene experts, they also include biocurators, who are not
required to be experts (and are primarily responsible for assembling evidence
for expert review). Regardless of their level of expertise, each VCEP member
is required to demonstrate competence through completion of extensive training
and an evaluation of their proficiency. All individuals are also required to
obtain HIPAA and human subjects training (based on their level of access to
human subjects' data). Finally, the SVI workgroup provides organization-wide
guidance regarding the evaluation and curation of human variant data.  
  
ClinGen requires that variant curation and preliminary evaluation must be
conducted by at least two reviewers.13 The requirements for variant evaluation
are described in the ClinGen Variant Curation Expert Panel Protocol, publicly
available via ClinGen's website. Part of this process includes evaluating
supporting data against rules and criteria developed by the VCEP, and ranking
them as either standalone, very strong, strong, moderate, or supporting. These
ranks are then used to determine a classification assertion (pathogenic [P],
likely pathogenic [LP], benign [B], likely benign [LB], or uncertain
significance [VUS]). Final evaluation and decisions about variant assertions
are made by consensus of the relevant VCEP. Consensus can be indicated by
either unanimous agreement by all members of the VCEP or a majority vote. In
order to be published as an approved assertion, variant classifications must
have at least a majority vote. If a majority vote cannot be obtained, the
variant may be considered an unclassified variant (which are reevaluated every
two years to determine if additional evidence has been made available to
support a classification) or may be classified as a lower-ranking class (for
instance, a variant may be considered VUS if a majority vote cannot be
obtained for a LP or LB classification). In order to receive final approval
and publication, all variant interpretations are reviewed by the full VCEP
membership (which includes non-biocurator, clinical, and disease experts).
Furthermore, all evidence curated by the ClinGen team is readily accessible
via their website.  
  
The framework established by ClinGen attempts to define and evaluate the
clinical validity of gene-disease relationships by evaluating the evidence
supporting or contradicting them.16 This standardized framework was developed
because there is substantial variability in the level of evidence supporting
claims of gene-disease relationships. As noted by Strande et al, "This
framework aims to provide a systematic, transparent method to evaluate a gene-
disease relationship in an efficient and consistent manner suitable for a
diverse set of users." 16(p.905)  
  
ClinGen's database validates gene-disease relationships by evaluating both
quantity and quality of evidence.16 Gene-disease relationships are then
identified under one of the following levels, with each level building upon
the previous: **Definitive** (requires that the relationship has been
repeatedly demonstrated in research and clinical diagnostic settings, as well
as upheld over time), **Strong** (requires that the relationship has been
featured in two or more independent studies with multiple unrelated probands
with pathogenic variants, as well as several types of supporting experimental
data), **Moderate** (requires that the relationship has been featured in at
least one independent study with several unrelated probands with pathogenic
variants, as well as having some supporting experimental data), **Limited**
(requires that the relationship has been featured in at least one independent
study with more than three unrelated probands with pathogenic variants, or
multiple unrelated probands without pathogenicity), and **No Known Disease
Relationship** (where no pathogenic variants have been identified to date,
therefore no evidence supports a causal role).  
  
There are additionally two levels of evidence reserved for when conflicting
evidence has been reported - **Disputed** (which suggests that disputing
evidence has been discovered but does not necessarily outweigh existing
evidence in support of the gene-disease association) and **Refuted** (which
suggests that disputing evidence has been discovered, and significantly
outweighs existing evidence in support of the gene-disease association). The
refuted status is applied at the discretion of clinical experts, after
analysis of all available evidence. Experimental evidence is scored based on a
separate framework.  
  
The evidence supporting clinical actionability for genetic disorders varies
significantly. Therefore, ClinGen developed and implemented a standardized,
evidence-based method to determine actionability of genomic testing. Hunter et
al explains that the assessment of clinical actionability is part of the
effort to create a central resource of information for the clinical relevance
of genomic variation.14 As discussed by Strande et al, the ultimate goal of
the ClinGen database is to "enhance the incorporation of genomic information
into clinical care."16(p.905) That said, ClinGen has also created a semi-
quantitative scoring metric to be utilized to assess actionability for
clinical decision making. As discussed by Berg et al, it should be noted that
clinical actionability "is a continuum, not a binary state."17(p.467-468) That
said, the ClinGen semi-quantitative scoring metric is used to score
interventions, not genes; ClinGen assigns a level of evidence to individual
alterations (rather than the entire gene). The scoring metric assesses four
categories: disease severity, likelihood of disease, effectiveness of the
intervention, and nature of the intervention. The scoring matrix also assesses
level of available evidence for two categories: likelihood of disease and
intervention effectiveness.  
  
Using the ClinGen framework, Strande et al evaluated a number of gene-disease
pairs and examined reproducibility of the scoring metric by having two
independent clinical domain experts evaluate each gene-disease relationship.16
Clinical domain experts agreed with the preliminary classifications for 87.1%
of ClinGen's gene-disease relationship curations with published evidence.
Discrepancies between expert and curator classification were discussed and
explained; additionally, it was noted that when the expert and curator
classifications differed, they did so by only a single category (moderate
versus limited). The authors concluded that ClinGen's evidence-based method
for evaluating gene-disease associations "will provide a strong foundation for
genomic medicine."16(p.902)  
  
As concluded by Hunter et al, "The ClinGen framework for actionability
assessment will assist research and clinical communities in making clear,
efficient, and consistent determinations of actionability based on transparent
criteria to guide analysis and reporting of findings from clinical genome-
scale sequencing."14(p.10)  
  
 **Memorial Sloan Kettering Cancer Center Oncology Knowledge Base (OncoKB)  
  
** OncoKB was established as a comprehensive precision oncology tool to
deliver evidence-based information about tumor mutations and alterations and
distill NCCN guidelines, expert recommendations, and scientific literature, in
order to support treatment decisions.8 OncoKB provides a resource which is
available to all clinicians and patients. The database is publicly available
through their website, organized by gene, alteration, tumor type, and clinical
implication, and is searchable by any of the above. OncoKB has received FDA
recognition for a portion of the database and is also included in the FDA's
Recognition of Public Human Genetic Variant Databases.15  
  
OncoKB's staff is made up of highly qualified scientists, physicians, and
engineers, each meeting specific qualifications criteria including educational
background, professional training, and skills.18 Individuals with Lead
Scientist, Clinical Genomics Annotation Committee (CGAC), or Scientific
Content Management Team (SCMT) roles are required to be physicians or
Ph.D-level scientists who are considered experts in their field and disease
specialty. These individuals' responsibilities include "coordinating and
monitoring training and proficiency of curators in procuring the appropriate
data, assessing the data in the context of variant interpretation, and
entering the data with sufficient detail into the OncoKB curation
platform."18(p.5) Curators, who are responsible for assessing and curating
gene alterations, their biological effects, and associated treatment
implications, can be either pre-doctoral graduate students, postdoctoral
fellows, or clinical fellows. Curators receive extensive in-person training in
variant classification, including mapping variants to FDA levels. All OncoKB
staff are also evaluated for potential conflicts of interest, with financial
conflicts being publicly disclosed on the OncoKB website. Any CGAC member with
a conflict of interest relevant to a specific Level of Evidence assignment is
not permitted to work on the assignment.  
  
CGAC reviews and approves all OncoKB/FDA level associations prior to internal
review.18(p.3-5) Additionally, data curated by OncoKB staff does not become
publicly available until it has undergone an internal, independent review by a
different OncoKB staff member. Specific protocols exist to manage conflicting
data or conflicting assertations regarding alterations, including an
independent review of curated data, as well as evaluation and discussion of
decisions until a consensus has been reached.18(p.20-21) In instances where a
consensus is reached, the alteration is accepted into the knowledge base with
a notation that there was majority but not uniform consensus; in instances
where consensus cannot be reached, the alteration is not assigned a level of
evidence within the knowledge base.  
  
As discussed by Chakravarty et al8, OncoKB contains a classification system
for clinical utility and potentially actionable alterations. "Potentially
actionable alterations in a specific cancer type are assigned to one of four
levels that are based on the strength of evidence that the mutation is a
predictive biomarker of drug sensitivity to FDA-approved or investigational
agents for a specific indication."8(p.2) OncoKB delineates separate levels of
evidence for therapeutic, diagnostic, and prognostic use cases. OncoKB assigns
a level of evidence to individual alterations (as opposed to the entire gene).  
  
The OncoKB therapeutic levels of evidence are as follows: **Level 1** gene
alterations have been recognized by the FDA as "predictive of response to an
FDA-approved drug in a particular disease context."8(p.2) **Level 2** gene
alterations are considered "standard care" predictive biomarkers. They are not
FDA-recognized but are recommended by professional guidelines (including NCCN)
and predict response to FDA-approved therapy in a particular disease context.
**Level 3A and 3B** are considered investigational; **3A** requires compelling
clinical evidence to support the biomarker as predictive of response to a drug
in a particular disease context and only applies to investigational biomarkers
for which there has been clinical activity (such as a clinical or preclinical
trial). **3B** could be either a standard care or investigational biomarker
predictive of response to an FDA-approved or investigational drug in another
indication. **Level 4** is considered hypothetical and requires compelling
biological evidence to support the biomarker as predictive of response to a
drug.  
  
Additionally, there are two therapeutic levels of evidence for treatment
resistance; **Level R1** __ is for standard care biomarkers predictive of
resistance to an FDA-approved drug in a particular disease context, while
**Level R2** requires compelling clinical evidence to support the biomarker as
being predictive of resistance to a drug.  
  
OncoKB also offers scoring of evidence for both diagnostic and prognostic use
cases. For diagnostic indications, level **Dx1** biomarkers have been
recognized by the FDA or professional guidelines as a requirement for
diagnosis in a particular disease context. Level **Dx2** biomarkers have been
recognized by the FDA or professional guidelines as supportive of diagnosis in
a particular disease context. Biomarkers in level **Dx3** may assist disease
diagnosis based upon clinical evidence. Similarly, for prognostic indications,
Level **Px1** biomarkers have been recognized by the FDA or professional
guidelines as prognostic for a particular disease context based on at least
one well-powered study. Level **Px2** biomarkers have been recognized by the
FDA or professional guidelines as prognostic for a particular disease context
based on at least one small study. Biomarkers in level **Px3** are considered
prognostic for a particular disease context based on clinical evidence from
well-powered studies.  
  
As a portion of the OncoKB database has been approved by the FDA, the
therapeutic levels of evidence indicated above can be mapped to one of three
FDA Levels of Evidence within the database.19 **FDA Level 1** requires
companion diagnostics (CDx) tests, which "are supported by analytical validity
of the test for each specific biomarker and a clinical study establishing
either the link between the result of that test and patient outcomes or
clinical concordance to a previously approved CDx."19 Level 1 is the highest
level of recognition by the FDA; however, OncoKB does not include any
companion diagnostic claims, and therefore no genes or variants are currently
considered Level 1. **FDA Level 2** is designated for mutations with evidence
of clinical significance, which allows providers to utilize information about
their patients' health alongside clinical evidence presented in professional
guidelines. "Such claims are supported by a demonstration of analytical
validity (either on the mutation itself or via a representative approach, when
appropriate) and clinical validity (typically based on publicly available
clinical evidence, such as professional guidelines and/or peer-reviewed
publications)."19 **FDA Level 3** is reserved for mutations with potential
clinical significance, but not identified as a higher level. "Such claims are
supported by analytical validation, principally through a representative
approach, when appropriate, and clinical or mechanistic rationale for
inclusion in the panel" (to include peer-reviewed publications or in vitro
pre-clinical models).19 OncoKB has a validation protocol in place to assess
the consistency of variant classification to FDA levels of evidence; mapping
OncoKB levels of evidence to FDA levels ranges from 85.7% to 100%.18(p.20)

Genetic testing for oncology endeavors to improve health through more accurate
and precise patient management. Consistent with the evidence framework for all
genetic testing, genetic tests for oncologic conditions must demonstrate
analytical validity, clinical validity, and clinical utility to be considered
medically reasonable and necessary for coverage. For truly improved health
outcomes, the test must be actionable and then be successfully integrated into
patient care by the clinician. Ultimately, in order to improve patient
outcomes, tests must enhance clinical decision-making by directly informing
treatment decisions and disease management.  
  
Coverage of items and services in the Medicare program is based on reasonable
and necessary services. The decision to perform genetic testing should be
reserved for circumstances when the treating provider has evaluated the
patient and either 1) established diagnosis of cancer or 2) found significant
evidence to create suspicion for cancer. Under these circumstances, if as a
next step in the clinical management of the patient, genetic testing would
directly impact the management of the patient's condition, then the testing
would be indicated. It should be noted that Medicare does not cover genetic
testing for the purposes of screening. In circumstances where the patient is
asymptomatic and genetic testing would be conducted for the purpose of
screening the patient or their relatives, the testing would not be considered
medically reasonable and necessary.  
  
It is important to assess genetic testing in the context of oncology with a
rigorous, evidence-based approach. This should not be seen as a barrier, but a
facilitator of appropriate testing for all eligible Medicare beneficiaries.
The Institute of Medicine's seminal work _Clinical Practice Guidelines:
Directions for a New Program_ 9 provides a rigorous, standardized approach for
guideline development. The Institute of Medicine highlights eight recommended
attributes for clinical practice guidelines: validity,
reliability/reproducibility, clinical applicability, clinical flexibility,
clarity, development via a multidisciplinary process, scheduled review, and
documentation. This approach and recommended attributes are consistent with
the databases/knowledge bases established by NCCN, ClinGen, and OncoKB.  
  
The National Comprehensive Cancer Network (NCCN) Biomarkers Compendium
supports clinical decision making by aggregating and curating NCCN guidelines
and treatment recommendations relevant to oncology. Poonacha and Go12 assess
the level of scientific evidence upon which NCCN guidelines are based, as well
as the guideline development process and methodology. Likewise, Birkeland and
McClure11 outline the standardized process for NCCN review of evidence and
establishment of Panel consensus. Recommendations for treatment are
categorized based on the level of clinical evidence available as well as
consensus among the multidisciplinary Guidelines Panel regarding the efficacy
and safety of the intervention. Highly recommended treatments and
interventions (Category 1) are associated with high levels of evidence and
uniform Panel consensus that the intervention is appropriate.10  
  
The open-access NIH-funded Clinical Genome Resource (ClinGen) supports
clinical decision making by aggregating, curating, and defining the clinical
relevance and actionability of gene-disease relationships. Strande et al16
outlines the standardized approach used by ClinGen to define and evaluate the
clinical validity of these gene-disease pairs, with evaluation being completed
by a broad base of experts. Likewise, Hunter et al14 outlines work by the
ClinGen Actionability Working Group (AWG), which presents the method of
systematic evidence assessment, and provides the standardized framework for
clinical actionability of genes and associated disorders. The strength of
evidence of a gene-disease relationship is determined based on a standard
semiquantitative approach to evaluate available evidence, the result of which
is a defined classification. The strongest gene-disease relationships
(classified as Definitive) are those for which the relationship has been
repeatedly demonstrated in research and clinical diagnostic settings, and
upheld over time (usually a period of at least three years).13  
  
The Memorial Sloan Kettering Cancer Center Oncology Knowledge Base (OncoKB)
supports clinical decision making by curating evidence-based information about
tumor mutations and alterations, NCCN guidelines, expert recommendations, and
scientific literature into one publicly available database. Chakravarty et al8
discusses the OncoKB classification system for clinical utility and
potentially actionable alterations, delineating separate levels of evidence
for therapeutic, diagnostic, and prognostic use cases. For therapeutic use
cases, interventions with the highest levels of evidence (Level 1) are those
which have been recognized by the U.S. FDA as "predictive of response to an
FDA-approved drug in a particular disease context."8(p.2) In diagnostic and
prognostic use cases, interventions with the highest level of evidence (levels
Dx1 and Px1, respectively) are those which have been recognized by the FDA
and/or professional guidelines.  
  
It should be noted that ClinGen and OncoKB have both received recognition by
the FDA for a portion of their databases. Both databases are listed in the
FDA's Recognition of Public Human Genetic Variant Databases15 (they are
currently the only databases to have received this recognition). The FDA is
regarded as a reliable source of information.  
  
In summary, genetic testing in the context of oncology has the potential to
improve patient outcomes through assisting the clinician in treatment
decision-making; however, given the rapidly evolving test climate, a reliable,
rigorous, standardized approach to evidence is necessary to improve health
outcomes in the Medicare population. At this time, because guidelines and
treatment recommendations set forth by NCCN, ClinGen, and OncoKB are
consistent with the Institute of Medicine's recommended attributes for
clinical guidelines, they are being used to establish medically reasonable and
necessary services as outlined in this LCD.