mp-715
print Print Back Back

Gene Expression Profiling for Cutaneous Melanoma

Policy Number: MP-715

Latest Review Date: May 2019

Category: Laboratory

Policy Grade: C

DESCRIPTION OF PROCEDURE OR SERVICE:

Laboratory tests have been developed that detect the expression of different genes in pigmented lesions or melanoma tumor tissue. Test results may help providers and patients decide whether to biopsy suspicious pigmented lesions, aid in diagnosis lesions with indeterminate histopathologic lesions or determine whether to perform sentinel lymph node biopsy in patients diagnosed with stage I or II cutaneous melanoma. This report summarizes the evidence of three tests.

Cutaneous Melanoma

Cutaneous melanoma accounts for more than 90% of cases of melanoma. For many decades, melanoma incidence was rapidly increasing in the United States. However, recent estimates have suggested the rise may be slowing. In 2018, more than 90,000 new cases of melanoma are expected to be diagnosed, and more than 9000 people are expected to die of melanoma.

Risk Factors

Exposure to solar ultraviolet radiation is a major risk factor for melanoma. Most melanomas occur on the sun-exposed skin, particularly those areas most susceptible to sunburn. Likewise, features that are associated with an individual’s sensitivity to sunlight, such as light skin pigmentation, red or blond hair, blue or green eyes, freckling tendency, and poor tanning ability are well-known risk factors for melanoma. There is also a strong association between high total body nevus counts and melanoma.

Several genes appear to contribute to melanoma predisposition such as tumor suppressor gene CDKN2A, melanocortin-1 receptor (MC1R) gene, and BAP1 variants. Individuals with either familial or sporadic melanoma have a two to three times increased risk of developing a subsequent primary melanoma. Several occupational exposures and lifestyle factors, such as body mass index and smoking, have been evaluated as possible risk factors for melanoma.

Gene Expression Profiling

Gene expression profiling measures the activity of thousands genes simultaneously and creates a snapshot of cellular function. Data for gene expression profiles are generated by several molecular technologies including DNA microarrays that measures activity relative to previously identified genes and RNA-Seq that directly sequences and quantifies RNA molecules. Clinical applications of gene expression profiling include disease diagnosis, disease classification, prediction of drug response, and prognosis.

POLICY:

Gene expression testing, including but not limited to the Pigmented Lesion Assay, in the evaluation of patients with suspicious pigmented lesions is considered not medically necessary and investigational.

Gene expression testing, including but not limited to the myPath Melanoma test, in the evaluation of patients with melanocytic lesions with indeterminate histopathologic features is considered not medically necessary and investigational.

Gene expression testing, including but not limited to DecisionDx-Melanoma, in the evaluation of patients with cutaneous melanoma is considered not medically necessary and investigational for all indications.

KEY POINTS:

This evidence review was created in May 2018 with a search of the MEDLINE database. The literature update was performed through November 1, 2018.

Evidence reviews assess whether a medical test is clinically useful. A useful test provides information to make a clinical management decision that improves the net health outcome. That is, the balance of benefits and harms is better when the test is used to manage the condition than when another test or no test is used to manage the condition.

The first step in assessing a medical test is to formulate the clinical context and purpose of the test. The test must be technically reliable, clinically valid, and clinically useful for that purpose. Evidence reviews assess the evidence on whether a test is clinically valid and clinically useful. Technical reliability is outside the scope of these reviews, and credible information on technical reliability is available from other sources.

Gene Expression Profiling to Guide Initial Biopsy Decisions

Clinical Context and Test Purpose

Primary care providers evaluate suspicious pigmented lesions to determine who should be referred to dermatology. Factors considered include both a patient’s risk for melanoma as well as a visual examination of the lesion. The visual examination assesses whether the lesion has features suggestive of melanoma.

Criteria for features suggestive of melanoma have been developed. One checklist is the ABCDE checklist:

  • Asymmetry;
  • Border irregularities;
  • Color variegation;
  • Diameter ≥6 mm;
  • Evolution.

Another criterion commonly used is the “ugly duckling” sign. An ugly duckling is a nevus that is obviously different from others in a given patient. Primary care providers generally have a low threshold for referral to dermatology.

Melanoma is difficult to diagnose based on visual examination, and the criterion standard for diagnosis is histopathology. There is a low threshold for excisional biopsy of suspicious lesions for histopathologic examination due to the procedure’s ease and low risk as well as the high probability of missing melanoma. However, the yield of biopsy is fairly low. The number of biopsies performed to yield one melanoma diagnosis has been estimated to be about 15 for U.S. dermatologists. Therefore a test that could accurately identify those lesions not needing a biopsy (i.e., a rule-out test for biopsy) could be clinically useful.

The purpose of gene expression profiling (GEP) in patients who have suspicious pigmented lesions being considered for biopsy is to inform a decision about whether to biopsy.

The question addressed in this section of the evidence review is: Does GEP improve the net health outcome in individuals with suspicious pigmented lesions?

The following PICOTS were used to select literature to inform this review.

Patients

The relevant population of interest is patients with suspicious pigmented lesions being considered for referral for biopsy, specifically those lesions meeting one or more ABCDE criteria.

Interventions

The test being considered is the DermTech Pigmented Lesion Assay (PLA). The PLA test measures expression of six genes (PRAME, LINC00518, CMIP, B2M, ACTB, PPIA). The PRAME (PReferentially expressed Antigen in MElanoma) gene encodes an antigen that is preferentially expressed in human melanomas, and that is not expressed in normal tissues (except testis). LINC00518 (Long Intergenic Non-protein Coding RNA518) is a regulatory RNA molecule. The other four genes provide normalization values. The feasibility of a test like PLA was first described in Wachsman et al (2011) and Gerami et al (2014) and development of the specific PLA test was described in Gerami et al (2017).

The test is performed on skin samples of lesions at least five mm in diameter obtained via noninvasive, proprietary adhesive patch biopsies of a stratum corneum specimen. The test does not work on the palms of hands, soles of feet, nails, or mucous membranes, and it should not be used on bleeding or ulcerated lesions.

The PLA test report includes two results. The first result is called the PLA MAGE (Melanoma Associated Gene Expression), which indicates low risk (neither PRAME nor LINC00518 expression was detected), moderate risk (expression of either PRAME or LINC00518 was detected), or high risk (expression of both PRAME and LINC00518 was detected). The second result is as an algorithmic PLA score that ranges from zero to 100, with higher scores indicating higher suspicion of malignant disease.

It is not clear whether the PLA test is meant to be used as a replacement, triage, or add-on test with respect to dermoscopy. The PLA sample report states that for low-risk lesions, physicians should “consider surveillance,” while for moderate- and high-risk lesions, physicians should “recommend a biopsy.” It does not state whether lesions with negative results should be further evaluated with dermoscopy or other techniques to confirm the lesion should not be biopsied. Therefore, this evidence review evaluates the test as a replacement for dermoscopy. As mentioned previously, there is a low threshold for biopsy of suspicious lesions. As such, tests that can rule-out need for biopsy could be useful and thus sensitivity and negative predictive value are the performance characteristics of most interest.

Comparators

After a referral from primary care to dermatology settings, dermatologists use visual examination as well as tools such as dermoscopy to make decisions regarding biopsy of suspicious lesions. A meta-analysis of nine studies (8487 lesions with 375 melanomas) compared dermoscopy with visual examination alone for the diagnosis of melanoma; it reported that, for clinicians with training in dermoscopy, adding dermoscopy to visual examination increased the sensitivity from 71% to 90%. The specificity numerically increased from 80% to 90%, but the difference was not statistically significant. Although dermoscopy is noninvasive and may aid in decision making regarding biopsy, it is only used by approximately 50% to 80% of dermatologists in the United States due to lack of training, interest, or time required for the examination.

The reference standard for diagnosis of melanoma is histopathology.

Outcomes

The beneficial outcomes of a true positive test result are appropriate biopsy and diagnosis of melanoma. The beneficial outcome of a true negative test result is potentially avoiding unnecessary biopsy.

The harmful outcome of a false-positive result is having an unnecessary biopsy. The harmful outcome of a false-negative result is potential delay in diagnosis and treatment.

The timeframe of interest for calculating performance characteristics is time to biopsy result. Patients who forgo biopsy based on test results could miss or delay diagnosis of cancer. Longer follow-up would be necessary to determine the effects on overall survival.

Technically Reliable

Assessment of technical reliability focuses on specific tests and operators and requires review of unpublished and often proprietary information. Review of specific tests, operators, and unpublished data are outside the scope of this evidence review, and alternative sources exist. This evidence review focuses on the clinical validity and clinical utility.

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

Determining whether a test can guide biopsy decisions is not based only on its sensitivity and specificity, but also on how the accuracy of the existing pathway for making biopsy decisions is changed by the test. Therefore, the appropriate design for evaluating performance characteristics depends on the role of the new test in the pathway for making biopsy decisions. New tests may be used as replacements for existing tests, to triage who proceeds for existing tests or add-on tests after existing tests. For replacement tests, the diagnostic accuracy of both tests should be concurrently compared, preferably in a paired design (i.e., patients receive both tests), and all patients receive the reference standard. For a triage test, a paired design is also needed, with the reference standard being performed preferably on all patients but at least for all discordant results. For an add-on test, the included patients can be limited to those who were negative after existing tests with verification of the reference standard in patients who are positive on the new test.

Study Selection Criteria

For the evaluation of clinical validity of the PLA test, studies that meet the following eligibility criteria were considered:

  • Reported on a validation cohort that was independent of the development cohort;
  • Reported on the accuracy of the marketed version of the technology;
  • Included a suitable reference standard (histopathology);
  • Patient/sample clinical characteristics were described;
  • Patient/sample selection criteria were described.

Studies were excluded from the evaluation of the clinical validity of the PLA test because they reported results of the development cohort, they did not use the marketed version of the test, did not include the reference standard test on PLA negative patients, did not adequately describe the patient characteristics, or did not adequately describe patient selection criteria.

The validation cohort from the Gerami et al (2017) publication was included. The study characteristics are described in Table 1. The report stated that included lesions were selected by dermatologists experienced in pigmented lesion management from 28 sites in the United States, Europe, and Australia; therefore, the samples were likely not consecutive or random. Information regarding the previous testing was not provided. The flow of potential and included samples was not clear, and whether the samples were all independent or, multiple samples from the same patient were not described. Diagnosis of melanoma was based on consensus among a primary reader and three expert dermatopathologists. The report did not state whether the histopathologic diagnosis was blinded to the results of the PLA test but did state the diagnosis was “routinely” assessed. Interpretation of the PLA result does not depend on a reader, so it is blinded to histopathologic results. In 11% of cases originally selected, a consensus diagnosis was not reached, and these samples were not included in the training or validation cohorts. Dates of data collection were not reported. Sex and anatomic location of biopsy were reported, but other clinical characteristics (e.g., risk factors for melanoma, presenting symptoms) were not. Study results are shown in Table 2. The study training cohort included 157 samples with 80 melanomas and 77 non-melanomas. The study validation cohort included 398 samples with 87 melanomas and 311 non-melanomas. Study relevance, design, and conduct gaps are in Tables 3 and 4.

Section Summary: PLA Clinical Validity

Multiple high-quality studies are needed to establish the clinical validity of a test. The PLA test has one clinical validity study with many methodologic and reporting limitations. Therefore, performance characteristics are not well-characterized. Also, the test has not been compared with dermoscopy, another tool frequently used to make biopsy decisions.

Table 1. Clinical Validity Study Characteristics of the PLA Test for Diagnosing Melanoma

Study

Study Population

Design

Reference Standard for Dx of Melanoma

Threshold Score for PLA Test

Timing of Reference and PLA Tests

Blinding of Assessors

Gerami et al (2017)

  • Adults
  • Suspicious pigmented lesion ≥4 mm in diameter
  • Without obvious or suspicious nodular melanoma
  • 24% from extremities, 13% from head and neck, 62% from trunk
  • 55% of samples from men
  • Median age, 49 y (range, 19-97 y)
  • Retrospective
  • Not consecutive or random

Histopathology; consensus diagnosis

  • Quantitative PCR yielded an amplification curve and a measurable cycle threshold value
  • Either LINC00518or PRAME detected

PLA patch before surgical biopsy; timing between patch and surgical biopsy unclear

Not clear

Dx: diagnosis; PCR: polymerase chain reaction.

Table 2. Clinical Validity Study Results of the PLA Test for Diagnosing Melanoma

Study

Initial N

Final N

Excluded Samples

Melanoma Prevalence

Sensitivityb

Specificityb

PPVb

NPVb

Gerami et al (2017)

398a

398

Before allocation to training and validation cohorts, 11% of original samples excluded due to lack of consensus diagnosis

22%

91

(83 to 96)

69

(64 to 74)

45

(38 to 53)c

96

(93 to 98)c

NPV: negative predictive value; PPV: positive predictive value.

a 398 samples were included in the validation cohort; the number of independent patients is unclear.
b Values are percentages with 95% confidence interval.

c Confidence intervals provided in the report; calculated from data provided.

Table 3. Clinical Validity Study Relevance Gaps of the PLA Test

Study

Populationa

Interventionb

Comparatorc

Outcomesd

Duration of Follow-Upe

Gerami et al (2017)

3. Study population characteristics not adequately described

 

3. No comparison to dermoscopy

3. Predictive values were not reported but were calculated based on data provided

 

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.

a Population key: 1. Intended use population unclear; 2. Clinical context is unclear; 3. Study population is unclear; 4. Study population not representative of intended use.

b Intervention key: 1. Classification thresholds not defined; 2. Version used unclear; 3. Not intervention of interest.

c Comparator key: 1. Classification thresholds not defined; 2. Not compared to credible reference standard; 3. Not compared to other tests in use for same purpose.

d Outcomes key: 1. Study does not directly assess a key health outcome; 2. Evidence chain or decision model not explicated; 3. Key clinical validity outcomes not reported (sensitivity, specificity and predictive values); 4. Reclassification of diagnostic or risk categories not reported; 5. Adverse events of the test not described (excluding minor discomforts and inconvenience of venipuncture or noninvasive tests).

e Follow-Up key: 1. Follow-up duration not sufficient with respect to natural history of disease (true positives, true negatives, false positives, false negatives cannot be determined).

Table 4. Clinical Validity Study Design and Conduct Gaps of the PLA Test

Study

Selectiona

Blindingb

Delivery of Testc

Selective Reportingd

Completeness of Follow-Upe

Statisticalf

Gerami et al (2017)

1,2. Not clear what criteria used to select samples but it does not appear to have been random or consecutive

1. Blinding of histopathology readers not described

1. Patch biopsy administered before surgical biopsy but timing between procedures not described

1. No registration reported

   

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.

a Selection key: 1. Selection not described; 2. Selection not random or consecutive (i.e., convenience).

b Blinding key: 1. Not blinded to results of reference or other comparator tests.

c Test Delivery key: 1. Timing of delivery of index or reference test not described; 2. Timing of index and comparator tests not same; 3. Procedure for interpreting tests not described; 4. Expertise of evaluators not described.

d Selective Reporting key: 1. Not registered; 2. Evidence of selective reporting; 3. Evidence of selective publication.

e Follow-Up key: 1. Inadequate description of indeterminate and missing samples; 2. High number of samples excluded; 3. High loss to follow-up or missing data.

f Statistical key: 1. Confidence intervals and/or p values not reported; 2. Comparison to other tests not reported.’’

Clinically Useful

A test is clinically useful if the results inform management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

Direct Evidence

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.

No direct evidence of clinical utility was identified.

Chain of Evidence

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility through a chain of evidence.

A decision-impact study by Ferris et al (2017) assessed the potential impact of PLA on physicians’ biopsy decisions in patients. Forty-five dermatologists evaluated 60 clinical and dermoscopic images of atypical pigmented lesions (eight melanoma, 52 nonmelanoma). In the first round, dermatologists did not have PLA test results and, in the second round, dermatologists had access to PLA test results with the order of cases being scrambled. The dermatologists were asked whether the lesions should be biopsied after each round. Therefore, the corresponding number of biopsy decisions should be 45×60×2=5400. Data were collected in 2014 and 2015. Results were reported for 4680 decisions with no description of the disposition of the remaining decisions. Of the 4680 reported decisions, 750 correct biopsy decisions were made without PLA results while 1331 were made with PLA results and 1590 incorrect biopsy decisions were made without PLA results while 1009 incorrect biopsy decisions were made with PLA results.

Section Summary: Clinically Useful

There is no direct evidence of clinical utility. A chain of evidence for clinical utility cannot be constructed due to lack of robust evidence of clinical validity.

GEP for Diagnosing Lesions with Indeterminate Histopathology

Clinical Context and Test Purpose

The diagnosis of melanoma was described in the previous section. The diagnosis of melanoma is histopathologic and when the histopathologic diagnosis is straightforward, ancillary methods such as comparative genomic hybridization (CGH), florescence in situ hybridization (FISH), and GEP are not recommended. Therefore the usefulness of an ancillary test is its ability to predict biologic behavior (metastasis) of lesions that are indeterminate by histopathology.

The purpose of GEP in patients whose melanocytic lesion is indeterminate after histopathology is to aid in the diagnosis of melanoma and decisions regarding treatment and surveillance.

The question addressed in this section of the evidence review is: Does GEP improve the net health outcome in individuals with indeterminate melanocytic lesions?

The following PICOTS were used to select literature to inform this review.

Patients

The relevant population of interest is patients whose melanocytic lesion is indeterminate based on clinical and histopathologic features.

Interventions

The test being considered is the Myriad myPath Melanoma test. The myPath test measures expression of 23 genes using quantitative reverse-transcription polymerase chain reaction. Fourteen genes are involved in melanoma pathogenesis and are grouped into three components related to cell differentiation, cell signaling, and the immune response, and nine housekeeper genes are also included. The test is performed on five standard tissue sections from an existing formalin-fixed, paraffin-embedded biopsy specimen.

The myPath test report includes an algorithmic myPath score ranging from -16.7 to 11.1, with higher, positive scores indicating higher suspicion of malignant disease. The myPath report also classifies these scores: -16.7 to -2.1 are “benign”; -2.0 to -0.1 are “indeterminate”; and 0.0 to +11.1 are “malignant”. Development of the test has been described by Clarke et al (2015).

The myPath test is meant as an add-on test to standard histopathology. Studies have evaluated the performance characteristics of the test when histopathology is used as the reference standard but are not the focus of this evidence review given that the test's potential usefulness is in evaluation of indeterminate lesions.

No recommendations for treatment or surveillance are given on the report.

Comparators

The reference standard for diagnosis of melanoma is histopathology. However, in cases of indeterminate histopathology, long-term follow-up is needed to evaluate the clinical outcome, specifically metastasis.

CGH and FISH are also used to diagnosis indeterminate lesions although neither has been fully validated. Fluorescence in situ hybridization (FISH) has been evaluated as a tool to aid in the diagnosis of lesions that are indeterminate, following histopathology in two studies that included histologically ambiguous lesions and a clinical, long-term follow-up. One study reported by Gaiser et al (2010) included 22 melanocytic lesions (12 indeterminate) followed for a mean of 65 months (range, ten-156 months) and reported a FISH sensitivity of 60% and a specificity of 50% for development of metastases during follow-up. A second study, reported by Vergier et al (2011), included 90 indeterminate melanocytic lesions of which 69 had no recurrence for at least five years of follow-up (mean, nine years; range, five-19 years) and 21 lesions that exhibited metastases. The sensitivity and specificity rates of the histopathologic review combined with FISH for the clinical outcome were 76% and 90%, respectively.

Outcomes

The beneficial outcomes of a true positive test result are a diagnosis of melanoma and corresponding appropriate treatment and surveillance. The beneficial outcome of a true negative test result is avoiding unnecessary surgery.

The harmful outcome of a false-positive result is having an unnecessary surgery and surveillance. The harmful outcome of a false-negative result is a delay in diagnosis and treatment.

NCCN guidelines state that even in the presence of node metastasis, indeterminate neoplasms can demonstrate benign biologic behavior, making it difficult to define a fully malignant lesion and also states that events in the group of indeterminate lesions tend to occur late. Therefore, the guidelines suggest that long-term follow-up is necessary to validate a test for this purpose.

Recurrence and metastases can occur may years after treatment of melanoma. In the two studies evaluating long-term outcomes of FISH (described above), the mean follow-up was approximately 5.5 and nine years. In Vergier et al (2011), metastases in the FISH-negative group generally occurred by five years.

For this section of the review, at least five years of event-free follow-up is required to confirm negative tests. The event of interest is metastasis.

Technically Reliable

Assessment of technical reliability focuses on specific tests and operators and requires review of unpublished and often proprietary information. Review of specific tests, operators, and unpublished data are outside the scope of this evidence review, and alternative sources exist. This evidence review focuses on the clinical validity and clinical utility.

Clinically Valid

A test must detect the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse).

Study Selection Criteria

For the evaluation of clinical validity of the myPath test, studies that meet the following eligibility criteria were considered:

  • Reported on a validation cohort that was independent of the development cohort;
  • Reported on the accuracy of the marketed version of the technology;
  • Included a suitable reference standard (clinical outcome with at least five years of follow-up for negatives);
  • Patient/sample clinical characteristics were described
  • Patient/sample selection criteria were described.

Studies were excluded from the evaluation of the clinical validity of the myPath test because authors did not use the specified reference standard of long term (at least five years) follow-up, and/or did not adequately describe patient characteristics.

The Ko et al (2017) clinical validity study met selection criteria. The study characteristics are described in Table 5. In Ko et al (2017), archived melanocytic neoplasms were submitted for myPath testing from university clinics in the United States and United Kingdom with additional samples acquired from Avaden BioSciences.33 Stage I, II, and III primary cutaneous melanomas that produced distant metastases subsequent to the diagnosis and benign lesions with clinical follow-up and no evidence of recurrence of metastases were included. For benign samples, a disease-free time of at least five years was recommended. Information on the previous testing was not provided. It is not clear if any of the samples originally had indeterminate histopathology results. Dates of data collection were not reported. Sex, age, Breslow depth, and anatomic location were described; presenting symptoms were not reported. A total of 293 samples were submitted; of these 53 did not meet inclusion criteria and 58 (24% of those tested) failed to produce a valid test score. An additional seven samples with indeterminate results were excluded from the calculations of performance characteristics.

Study results are shown in Table 6. Study relevance, design, and conduct gaps are in Tables 7 and 8.

Table 5. Clinical Validity Study Characteristics of the myPath Test for Predicting Metastasis

Study

Study Population

Design

Reference Standard

Threshold Score for Positive myPath Test

Timing of Reference and myPath Tests

Blinding of Assessors

Ko et al (2017)

  • Primary cutaneous melanomas or benign melanocytic nevi
  • Mean age, 53 y
  • 55% of samples from men
  • Retrospective
  • Not consecutive or randomly selected
  • Positive: malignant lesions that produced distant metastases
  • Negative: Event-free follow-up, recommended 5 y (median, 6.2 y)
  • Scores from 0.0 to 11.1 (i.e., “malignant”)
  • Final clinical diagnosis established before myPath test
  • Length of time between biopsy and myPath test unclear

Yes

Table 6. Clinical Validity Study Results of the myPath Test for Predicting Metastasis

Study

Initial N

Final N

Excluded Samples

Melanoma Prevalence

Sensitivitya

Specificitya

PPVa

NPVa

Ko et al (2017)

240

175

  • 58 failed to produce test result
  • 7 with indeterminate results

54

94
(87 to 98)b

96
(89 to 99)b

97
(91 to 99)b

93
(85 to 97)b

NPV: negative predictive value; PPV: positive predictive value.

a Values are percentages with 95% confidence interval.

b Confidence intervals not provided in the report; calculated from data provided.

Table 7. Clinical Validity Study Relevance Gaps of the myPath Test

Study

Populationa

Interventionb

Comparatorc

Outcomesd

Duration of Follow-Upe

Ko et al (2017)

4. Study population is not limited to lesions that are indeterminate following histopathology

     

None noted

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.
CGH: comparative genomic hybridization; FISH: fluorescence in situ hybridization.

a Population key: 1. Intended use population unclear; 2. Clinical context is unclear; 3. Study population is unclear; 4. Study population not representative of intended use.

b Intervention key: 1. Classification thresholds not defined; 2. Version used unclear; 3. Not intervention of interest.

c Comparator key: 1. Classification thresholds not defined; 2. Not compared to credible reference standard; 3. Not compared to other tests in use for same purpose.

d Outcomes key: 1. Study does not directly assess a key health outcome; 2. Evidence chain or decision model not explicated; 3. Key clinical validity outcomes not reported (sensitivity, specificity and predictive values); 4. Reclassification of diagnostic or risk categories not reported; 5. Adverse events of the test not described (excluding minor discomforts and inconvenience of venipuncture or noninvasive tests).

e Follow-Up key: 1. Follow-up duration not sufficient with respect to natural history of disease (true positives, true negatives, false positives, false negatives cannot be determined).

Table 8. Clinical Validity Study Design and Conduct Gaps of the myPath Test

Study

Selectiona

Blindingb

Delivery of Testc

Selective Reportingd

Completeness of Follow-Upe

Statisticalf

Ko et al (2017)

2. Samples not consecutive or random

 

1. Unclear how much time elapsed between biopsy and myPath test

1. No registration reported

2. More than 25% of samples tested did not produce results or produced indeterminate results

1. CIs for sensitivity and specificity not reported but were calculated based on data provided. NPV, PPV were not reported

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.
CI: confidence interval; NPV: negative predictive value; PPV: positive predictive value.

a Selection key: 1. Selection not described; 2. Selection not random or consecutive (i.e., convenience).

b Blinding key: 1. Not blinded to results of reference or other comparator tests.

c Test Delivery key: 1. Timing of delivery of index or reference test not described; 2. Timing of index and comparator tests not same; 3. Procedure for interpreting tests not described; 4. Expertise of evaluators not described.

d Selective Reporting key: 1. Not registered; 2. Evidence of selective reporting; 3. Evidence of selective publication.

e Follow-Up key: 1. Inadequate description of indeterminate and missing samples; 2. High number of samples excluded; 3. High loss to follow-up or missing data.

f Statistical key: 1. Confidence intervals and/or p values not reported; 2. Comparison to other tests not reported.

Section Summary: Clinically Valid

Multiple high-quality studies are needed to establish the clinical validity of a test. The myPath test has one clinical validity study including long-term follow-up for metastasis as the reference standard. However, it is not clear whether the study population included lesions that were indeterminate following histopathology and the study had other methodologic and reporting limitations. Therefore, performance characteristics are not well-characterized.

Clinically Useful

A test is clinically useful if the results inform management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

Direct Evidence

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.

No direct evidence of clinical utility was identified.

Chain of Evidence

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

Two decision-impact studies assessed the potential impact of myPath on physicians’ treatment decisions in patients with diagnostically challenging lesions. Given the lack of outcomes, it is not known whether any treatment changes were clinically appropriate.

Section Summary: Clinically Useful

There is no direct evidence of clinical utility. A chain of evidence for clinical utility cannot be constructed due to lack of robust evidence of clinical validity

GEP to Guide Decisions in Melanoma

Clinical Context and Test Purpose

Many treatments and surveillance decisions are determined by a patient’s prognostic stage group based the American Joint Committee on Cancer tumor, node, and metastasis staging system. The prognostic groups are as follows: stage I, T1a through T2a primary melanomas without evidence of regional or distant metastases; stage II, T2b through T4b primary melanomas without evidence of lymphatic disease or distant metastases; stage III: pathologically documented involvement of regional lymph nodes or in transit or satellite metastases (N1 to N3); stage IV: distant metastases.

Patients may also undergo sentinel lymph node biopsy to gain more definitive information about the status of the regional nodes.

Wide local excision is the definitive surgical treatment of melanoma. Following surgery, patients with American Joint Committee on Cancer stage I or II (node-negative) melanoma do not generally receive adjuvant therapy. Patients with higher risk melanoma receive adjuvant immunotherapy or targeted therapy. Ipilimumab has been shown to prolong recurrence-free survival by approximately 25% compared with placebo at a median of 5.3 years in patients with resected, stage III disease. Nivolumab has been shown to further prolong survival compared with ipilimumab by approximately 35% at 18 months. For patients who are BRAF V600 variant-positive with stage III melanoma, the combination of dabrafenib plus trametinib has been estimated to prolong relapse-free survival by approximately 50% over three years.

Patients with stage I and II disease should undergo an annual routine physical and dermatologic examination. However, follow-up strategies and intervals have not been standardized or tested, and there is no consensus. These patients typically do not receive surveillance imaging. Patients with stage III melanoma may be managed with more frequent follow-up and imaging surveillance following therapy.

The purpose of GEP in patients with melanoma is to identify low and high-risk patients classified as stage I or II according to the American Joint Committee on Cancer (AJCC) criteria. Current guidelines do not recommend adjuvant therapy or imaging surveillance for AJCC stage I or II patients following surgery. Patients initially staged as I or II who have positive lymph nodes following sentinel lymph node biopsy (SLNB) are then eligible to be treated with adjuvant therapy as stage III patients.

At least three uses for the test have been suggested. The manufacturer’s website indicates that physicians can use DecisionDx-Melanoma information to “consider upstaging” patients for “active systemic surveillance or referral to medical oncology for consideration of systemic drug therapy or clinical trials.” Similarly, in one clinical validity study (described below), the authors stated that “high-risk patients with stage I and II disease may benefit from adjuvant therapy and/or enhanced imaging protocols to allow for early detection of metastasis.” In another clinical validity study, the authors concluded that the test’s “role in consideration of patients for adjuvant therapy should be examined prospectively.” This use of the test would be as a replacement for SLNB since SLNB is currently used to identify patients clinically diagnosed as stage I and II who have node involvement.

However, the use of the test reviewed for the Medicare population is to select patients at low risk of being lymph node-positive who can avoid an SLNB (i.e., a triage test for SLNB).

The question addressed in this section of the evidence review is: Does GEP improve the net health outcome in individuals with AJCC stage I or II melanoma?

The following PICOTS were used to select literature to inform this review.

Patients

To select patients for adjuvant therapy and/or enhanced surveillance, the relevant population of interest is patients with AJCC stage I/II cutaneous melanoma.

To select patients who can avoid SLNB, the relevant population of interest is patients with AJCC stage I or II cutaneous melanoma who are being considered for SLNB.

Interventions

The test being considered is the Castle Biosciences DecisionDx-Melanoma test. The DecisionDx test measures expression of 31 genes using quantitative reverse-transcription polymerase chain reaction. The test includes 28 prognostic gene targets and three endogenous control genes. The test is performed on standard tissue sections from an existing formalin-fixed, paraffin-embedded biopsy or wide local excision specimen.

Development of the test was described in Gerami et al (2015). To develop the DecisionDx-Melanoma gene panel, Gerami et al (2015) conducted a meta-analysis of published studies that identified differential gene expression in metastatic vs nonmetastatic primary cutaneous melanoma. Of 54 identified genes, investigators selected 20 for further polymerase chain reaction analysis based on chromosomal location. Five genes from Castle Biosciences’ DecisionDx-UM gene panel were added based on analysis of metastatic and nonmetastatic primary cutaneous melanoma, and two probes of the BRCA1-associated protein 1 gene, BAP1, which has been associated with the metastatic potential of uveal melanoma, also were added. Finally, four genes with minimal variation in expression level between metastatic and nonmetastatic primary cutaneous melanoma were added as controls. Patients had a minimum follow-up of five years unless there was a well-documented metastatic event, including positive SLNB. Information about treatments received was not provided.

The DecisionDx test report provides two results: a class and a probability score. The class stratifies tumors as low risk (class 1) or high risk (class 2), with subclassifications within each class (A or B) based on how close the probability score is to the threshold between class 1 and class 2. The probability score ranges from zero to one and appears to be the risk of recurrence within five years.

Comparators

Treatment and surveillance recommendations are based on AJCC staging. SLNB may be used to get more definitive information about the status of the regional nodes compared with a physical examination. The American Society of Clinical Oncology and National Comprehensive Cancer Network have similar but not identical recommendations on which patients should undergo SLNB (based on thickness and other high-risk features).

SLNB has a low rate of complications; in the Sunbelt Melanoma Trial, a prospective multi-institutional study of SLNB for melanoma reported by Wrightson et al (2003), less than 5% of the 2120 patients developed major or minor complications associated with SLNB.

Online tools are available to predict prognosis based on the AJCC guidelines. The original AJCC tool was developed by Soong et al (n.d.). Callender et al (2012) incorporated SLNB results into a revised tool (http://www.melanomacalculator.com/)

Outcomes

Regarding selecting patients for adjuvant therapy and/or enhanced surveillance:

A negative DecisionDx (class 1) test result would not change outcomes. Per guidelines, the patients would not receive adjuvant therapy or enhanced surveillance, just as without the DecisionDx test. A positive DecisionDx (class 2) test result would indicate that a patient might benefit from adjuvant therapy or enhanced surveillance. Therefore, the potential beneficial outcomes of a true positive result are additional treatment and surveillance and potentially prolonged survival. The potential harmful outcomes of a false positive result are unnecessary adverse effects and burdens of adjuvant therapy and enhanced surveillance.

Regarding selecting patients who can avoid SLNB:

For patients meeting guideline-recommended criteria for SLNB, a positive DecisionDx (class 2) test result would not change outcomes. The patients would proceed to SLNB, as they would have without the DecisionDx test, and treatment and imaging decisions would depend on SLNB results. A negative DecisionDx (class 1) test result would indicate that a patient could avoid an SLNB. Therefore, the potential beneficial outcomes of a true negative result are avoidance of an SLNB and related adverse effects and burdens. The potential harmful outcomes of a false negative result are reduced time to recurrence due to not identifying node-positive patients that would be eligible for beneficial adjuvant treatment and potentially reduces survival.

The risk of recurrence decreases over time but does not reach zero. In a study of 1568 patients with stage I melanoma, Dicker et al (1999) found that 80% of the recurrences occurred within the first three years. A prospective study by Garbe et al (2003) reported that, for stage I and II patients, the risk of recurrence was low after 4.4 years. Among 4731 patients treated for more than ten years at one institution, Faries et al (2013) found the majority of recurrences occurred in the first five years. However, 7% of patients experienced recurrence after ten years (median, 16 years). Even among stage I/II patients, recurrence after ten years occurred in 2% of patients.

Five-year recurrence-free survival (RFS) is the outcome and time-point of interest.

Technically Reliable

Assessment of technical reliability focuses on specific tests and operators and requires review of unpublished and often proprietary information. Review of specific tests, operators, and unpublished data are outside the scope of this evidence review, and alternative sources exist. This evidence review focuses on the clinical validity and clinical utility.

Clinically Valid

Study Selection Criteria

For the evaluation of clinical validity of the DecisionDx test, studies that meet the following eligibility criteria were considered:

  • Reported on a validation cohort that was independent of the development cohort;
  • Reported on the accuracy of the marketed version of the technology;
  • Included a suitable reference standard (five-year RFS or five-year MFS);
  • Patient/sample clinical characteristics were described
  • Patient/sample selection criteria were described.

Several papers were excluded from the evaluation of clinical validity. Hsueh et al (2017) and Podlipnik et al (2019) were excluded from the evaluation of the clinical validity of the DecisionDx test because they did not report five-year outcomes (median follow-up, 1.5 years and two years respectively). Samples used in Gerami et al (2015) and Ferris et al (2017) appear to overlap with the samples from Gerami et al (2015) and each other and will not be considered independent validation studies for inclusion in the tables. They are described briefly following the clinical validity tables. Samples used in both papers by Gastman et al (2018) are stated to overlap previous validation studies. Vetto et al (2019) included a retrospective cohort that was used to develop the model and is thus not eligible for inclusion, as well a prospective cohort with some overlapping samples and without report of five-year outcomes.

Three independent clinical validity studies meeting eligibility criteria have been conducted. Characteristics and results are summarized in Tables 9 and 10 and briefly in the paragraphs that follow.

Table 9. Clinical Validity Study Characteristics of the DecisionDx Test for Diagnosing Melanoma

Study

Study Population

Design

Reference Standard / Outcome Measure

Threshold Score for Positive DecisionDx Test

Timing of Reference and DecisionDx Tests

Blinding of Assessors

Gerami et al (2015); Validation subset

  • Adults
  • Stage I-IV cutaneous melanoma (87% stage I/II)
  • At least 5 y of FU (median, 7.0 y)
  • Retrospective
  • Not consecutive or randomly selected

5-y RFS

  • Class 2 is high risk
  • Risk threshold not provided
  • Patient diagnosed between 1998 and 2009
  • Timing of DecisionDx not described

Yes

Zager et al (2018)

  • Stage I-III cutaneous melanoma (68% stage I/II)
  • At least 5 y of FU (median, 7.5 y)
  • Retrospective
  • Not consecutive or randomly selected

5-y RFS

  • Class 2 is high risk
  • Class 1: probability score 0 to 0.49
  • Class 2: probability score 0.5 to 1
  • Patients diagnosed between 2000 and 2014
  • Timing of DecisionDx not described

Yes

Greenhaw et al (2018)

  • Patients who were treated for primary invasive CM of any Breslow depth within the last five years and had had GEP testing (86% stage I, 14% stage II)
  • Mean follow-up of 23 months, only 20 patients had five year follow-up
  • Retrospective
  • Consecutive

5-y RFS

Commercial test cutoffs used

Institution offered DecisionDx testing to newly diagnosed and those treated within the previous five years

Yes

DFS: disease-free survival; FU: follow-up; RFS: recurrence-free survival; MFS: metastasis-free survival

Table 10. Clinical Validity Study Results of the DecisionDx Test for Diagnosing Melanoma

Study

Initial / Final N

Excluded Samples

Events and Kaplan-Meier 5-Year RFSa

Sensitivitya

Specificitya

PPVa

NPVa

     

Class 1

Class 2

       

Gerami et al (2015); Validation subset

 

Samples excluded if melanoma dx not confirmed, dissectible area not acceptable

           

Overall

Unclear/104

 
  • 4 events
  • RFS=97 (NR)
  • 31 events
  • RFS=31 (NR)
  • p<0.001 vs class 1

89

(73 to 97)b

83

(72 to 91)b

72

(56 to 85)b

93

(84 to 98)b

AJCC stage I and II

Unclear/78

 
  • 3 events
  • RFS=98 (NR)
  • 18 events
  • RFS=37 (NR)
  • p<0.001 vs class 1

86

(64 to 97)b

84

(72 to 93)b

67

(46 to 83)b

94

(84 to 99)b

Zager et al (2018)

 

Did not meet analytic quality control thresholds

           

Overall

601 / 523

 
  • 42 events
  • RFS=88 (85 to 92)
  • 100 events
  • RFS=52 (46 to 60)

70

(62 to 78)

71

(67 to 76)

48

(41 to 55)

87

(82 to 90)

AJCC stage I

Unclear / 264

 
  • 11 events
  • RFS=96 (94 to 99)
  • 6 events
  • RFS=85 (74 to 97)

35

(14 to 62)b

87

(82 to 91)b

15

(6 to 31)b

95

(91 to 98)b

AJCC stage II

Unclear / 93

 
  • 9 events
  • RFS=74 (60 to 91)
  • 30 events
  • RFS=55 (44 to 69)

77

(61 to 89)b

43

(29 to 57)b

49

(36 to 62)b

72

(53 to 86)b

Greenhaw et al

256/256

None excluded but only 20 had five-year follow up

  • 3 events
  • MFS=93 (82 to 100)
  • 8 events
  • MFS=69 (52 to 90)

77 (46 to 94)

87 (82 to 91)

24 (13 to 40)

99 (96 to 100)

AJCC: American Joint Committee on Cancer; CI: confidence interval; Dx: diagnosis; NPV: negative predictive value; NR: not reported; PPV: positive predictive value; RFS: recurrence-free survival; MFS: metastasis-free survival

a Values are percentages with 95% confidence interval.

b Confidence intervals not provided in the report; calculated from data provided.

The validation cohort in Gerami et al (2015) included patients with stage 0, I, II, III, or IV disease from six U.S. centers (N=104). A complete disposition of samples received from the institutions and those included in the analysis was not provided. For 78 patients in the validation cohort with AJCC stage I or II cutaneous melanoma who had either a metastatic event or had more than five years of follow-up without metastasis, five-year disease-free survival was 98% (CIs not reported) for DecisionDx class I patients and 37% for DecisionDx class II patients. The positive predictive value (PPV) and negative predictive value (NPV) were 67% and 94%, respectively. CIs for performance characteristics were calculated in Table 10 based on data provided. Reclassification of patients in AJCC stages to DecisionDx classes is shown in Table 11.

Table 11. Reclassification of Patients Based on AJCC Stages to DecisionDx Classes in the Gerami Validation Cohort

AJCC Stage

DecisionDx Class

 

Class 1 (Low Risk), N (row %)

Class 2 (High Risk), N (row %)

Total

0

0

0

 

Total stage I

50 (89%)a

6 (11%)

56

IA

37

1

 

IB

10

5

 

Total stage II

10 (29%)

24 (71%)

34

IIA

5

8

 

IIB

5

12

 

IIC

0

4

 

Total stage III

1 (8%)

11 (92%)

12

Total stage IV

0 (0%)

2 (100%)

2

Total

61

43

104

Adapted from Gerami et al (2015).

AJCC: American Joint Committee on Cancer.

a The subclass for n=3 class 1 samples are not reported.

Zager et al (2018) reported results of a second clinical validity study including AJCC stage I, II, or III primary melanoma tumors from 16 U.S. sites. The samples were independent of the other validation studies. Of the 601 cases submitted from the institutions, 523 were included in the analysis (357 stage I/II). The excluded samples did not meet pre- and post-analytic quality control thresholds. SLN status was untested in 36% of the patients, negative in 34%, and positive in 30%. The report did not describe any adjuvant therapy that the patients received. Overall, 42 (13%) recurrence events occurred in DecisionDx class 1 patients and 100 (48%) recurrence events occurred in DecisionDx class 2 patients. The five-year RFS estimated by Kaplan-Meier was 88% (95% CI, 85% to 92%) in class 1 and 52% (95% CI, 46% to 60%) in class 2. The reported sensitivity and specificity were 70% (95% CI, 62% to 78%) and 71% (95% CI, 67% to 76%), respectively, with a PPV of 48% (95% CI, 41% to 55%) and a NPV of 87% (95% CI, 82% to 90%). For comparison, the performance characteristics for five-year RFS for sentinel lymph node status among those with SLNB were: sensitivity, 66% (95% CI, 57% to 74%); specificity, 65% (95% CI, 58% to 71%); PPV, 52% (95% CI, 44% to 60%); and NPV, 76% (95% CI, 69% to 82%). Estimates stratified by AJCC stage I or II are shown in Table 10. The reclassification of patients based on SLNB status using DecisionDx classes is shown in Table 12. If DecisionDx were used as a triage test such that only class 2 received SLNB, then 159 class 1 patients would not have undergone SLNB. Of the 159 patients in class 1, 56 were SLNB-positive and were therefore eligible for adjuvant therapy. It is not clear if the SLNB-positive patients in this study received adjuvant therapy. Of the 56 patients who were DecisionDx class 1 and SLNB-positive, 22 recurrence events occurred by five years.

Relevance, design, and conduct gaps are summarized in Tables 13 and 14.

Table 12. Reclassification of Patients Based on SLNB Status to DecisionDx Classes

SLNB

DecisionDx Class 1 (Low Risk)

DecisionDx Class 1 (High Risk)

Total

 

n (%)

Events

5-Year RFS (95% CI), %

n (%)

Events

5-Year RFS (95% CI), %

 

Negative

103 (65)

15

87 (81 to 94)

77 (43)

28

67 (57 to 79)

180

Positive

56 (35)

22

61 (49 to 76)

101 (57)

60

37 (28 to 49)

157

Total

159

   

178

   

337a

Adapted from Zager et al (2017).

RFS: recurrence-free survival; SLNB: sentinel lymph node biopsy.

a 337 patients had DecisionDx results and SLNB results.

Greenhaw et al (2018) reported results of an independent study of the DecisionDx test using their institution’s melanoma registry and including patients who had been treated for cutaneous melanoma within the last five years and undergone DecisionDx testing. Study characteristics and results were reported in the preceding Tables 9 and 10. Two-hundred fifty-six patients were tested; 84% were categorized as DecisionDx class 1 (low risk) and 16% were DecisionDx class 2 (high risk). 219 (86%) of tumors were AJCC stage I and 37 (14%) were AJCC stage II. None of the 18 stage I/class 2 tumors metastasized but 1 (0.5%) of 201 stage I/class 1 tumors metastasized. Ten (42%) of the stage II/class 2 tumors metastasized and two (15%) of the 13 stage II/class 1 tumors metastasized.

Table 13. Clinical Validity Study Relevance Gaps of the DecisionDx Test

Study

Populationa

Interventionb

Comparatorc

Outcomesd

Duration of Follow-Upe

Gerami et al (2015); Validation subset

4. Study population includes AJCC stage III/IV lesions (13%), although analysis for only stage I/II was provided

1. Risk threshold for classification into class 1 or 2 not provided.

3. Not compared to other prediction tools

2. Evidence-based treatment or surveillance pathway using the test is not described

 

Zager et al (2018)

4. Study population includes AJCC stage III lesions (32%), although analysis for only stage I/II was provided

   

2. Evidence-based treatment or surveillance pathway using the test is not described

 

Greenhaw et al (2018)

3. Not compared to other prediction tools

2. Evidence-based treatment or surveillance pathway using the test is not described

1. Only 20 patients had 5-year follow-up

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.
AJCC: American Joint Committee on Cancer.

a Population key: 1. Intended use population unclear; 2. Clinical context is unclear; 3. Study population is unclear; 4. Study population not representative of intended use.

b Intervention key: 1. Classification thresholds not defined; 2. Version used unclear; 3. Not intervention of interest.

c Comparator key: 1. Classification thresholds not defined; 2. Not compared to credible reference standard; 3. Not compared to other tests in use for same purpose.

d Outcomes key: 1. Study does not directly assess a key health outcome; 2. Evidence chain or decision model not explicated; 3. Key clinical validity outcomes not reported (sensitivity, specificity and predictive values); 4. Reclassification of diagnostic or risk categories not reported; 5. Adverse events of the test not described (excluding minor discomforts and inconvenience of venipuncture or noninvasive tests).

e Follow-Up key: 1. Follow-up duration not sufficient with respect to natural history of disease (true positives, true negatives, false positives, false negatives cannot be determined).

Table 14. Clinical Validity Study Design and Conduct Gaps of the DecisionDx Test

Study

Selectiona

Blindingb

Delivery of Testc

Selective Reportingd

Completeness of Follow-Upe

Statisticalf

Gerami et al (2015); Validation subset

2. Not consecutive or random

 

1. Time between collection of biopsy and DecisionDx not described

1. No registration reported

1. No description of number of samples (if any) that failed to produce results or were indeterminate

1. CIs not reported but were calculated based on data provided

Zager et al (2018)

2. Not consecutive or random

 

1. Time between collection of biopsy and DecisionDx not described

1. No registration reported

1. No description of number of samples (if any) that failed to produce results or were indeterminate

 

Greenhaw et al (2018)

1. Some samples collected after treatment

1. No registration reported

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.

CI: confidence interval; NPV: negative predictive value; PPV: positive predictive value.

a Selection key: 1. Selection not described; 2. Selection not random or consecutive (i.e., convenience).

b Blinding key: 1. Not blinded to results of reference or other comparator tests.

c Test Delivery key: 1. Timing of delivery of index or reference test not described; 2. Timing of index and comparator tests not same; 3. Procedure for interpreting tests not described; 4. Expertise of evaluators not described.

d Selective Reporting key: 1. Not registered; 2. Evidence of selective reporting; 3. Evidence of selective publication.

e Follow-Up key: 1. Inadequate description of indeterminate and missing samples; 2. High number of samples excluded; 3. High loss to follow-up or missing data.

f Statistical key: 1. Confidence intervals and/or p values not reported; 2. Comparison to other tests not reported.

In a subsequent analysis of patients with melanoma who had undergone SLNB, Gerami et al (2015) compared prognostic classification by DecisionDx-Melanoma with biopsy results. A total of 217 patients comprised a convenience sample from a database of 406 patients previously tested with DecisionDx-Melanoma. Patients who had undergone SLNB appear to overlap with patients in Gerami et al (2015) discussed previously. Most (73%) patients had a negative SLNB, and 27% had a positive SLNB. DecisionDx-Melanoma classified 76 (35%) tumors as low risk (class I) and 141 (65%) tumors as high risk (class II). Within the group of SLNB-negative patients, the 5-year overall survival rate was 91% in class I patients and 55% in class II patients. Within the group of SLNB-positive patients, the five-year overall survival rate was 77% in class I patients and 57% in class II patients.

Ferris et al (2017) compared the accuracy of DecisionDx-Melanoma with the web-based AJCC Individualized Melanoma Patient Outcome Prediction Tool. The study included 205 patients who appear to overlap with the patients in the second Gerami et al (2015) study described above. AJCC-predicted five-year survival for each patient was categorized into low and high risk based on both a 68% predicted five-year survival and a 79% predicted five-year survival. The 68% and 79% cut points were reported to correspond to five-year survival in patients with stage IIA and IIB, respectively, although it is unclear whether those cut points were prespecified, whether they were based on internal or external estimates of risk, or whether they are commonly used in practice. The prognostic sensitivity and specificity for death (median follow-up, seven years) of the Decision-Dx Melanoma were 78% and 69%, respectively (CIs not reported). The sensitivity and specificity for the AJCC calculator with the 79% cut point were 60% and 74%, respectively. The combination of the DecisionDx-Melanoma and AJCC tools had a sensitivity of 82% and specificity of 62%. The cross-classification for the DecisionDx-Melanoma and AJCC tools for five-year overall survival is shown in Table 15.

Table 15. Cross-Classification for the DecisionDx-Melanoma and AJCC Tool (79% Cut point) for 5-Year Overall Survival

Risk Classification (DecisionDx-Melanoma vs AJCC)

N

No. of Events

5-Year Overall Survival, %

Low/low

105

9

96

Low/high

13

2

83

High/low

30

11

71

High/high

57

28

44

Adapted from Ferris et al (2017).

AJCC: American Joint Committee on Cancer.

Section Summary: Clinically Valid

To use prognostic information for decision-making, performance characteristics should be consistent and precise. Two independent studies, using archived tumor specimens, have reported five-year RFS in AJCC stage I or II patients.

If the test is to be used to select stage I and II patients for adjuvant therapy or enhanced surveillance then it should identify a group with high risk of recurrence. Gerami et al (2015) reported RFS rates of 37% for DecisionDx class 2 (high risk) in patients in AJCC stage I and II patients. However, Zager et al (2018) reported RFS rates of 85% (95% CI, 74% to 97%) for DecisionDx class 2 patients in AJCC stage 1 and 55% (95% CI, 44% to 69%) for DecisionDx class 2 in AJCC stage II disease. In addition, to 'rule-in' patients for additional treatment or surveillance, the test should have specificity and PPV. Zager et al (2018) and Greenhaw et al (2018) the specificities were 71% and 87% respectively while the PPV were only 48% and 24%, respectively. The low PPV suggests that the majority of patients identified as high risk by the DecisionDx test would not develop metastasis and would be unnecessarily subjected to additional treatment or surveillance.

If the test is to be used to select stage I and II patients who can avoid SLNB, then it should identify a group who are eligible for SLNB but have low risk of recurrence. Gerami et al (2015) reported RFS rates of 98% in DecisionDx class 1 (low risk) without CIs in AJCC stage I or II patients. Zager et al (2018) reported RFS rates of 96% (95% CI, 94% to 99%) for DecisionDx class 1 in patients with AJCC stage I disease and RFS rates of 74% (95% CI, 60% to 91%) for DecisionDx class 1 n patients with AJCC stage II disease.

Although CIs were not available for the first study, RFS does not appear to be well-characterized in either DecisionDx risk group as evidenced by the variation in estimates across studies.

Zager et al (2017) also reported that 56 of 159 (35%) patients who were DecisionDx class 1 (low risk) were SLNB-positive and in those patients 22 recurrences (39%) occurred over five years. If the DecisionDx test were used as a triage for SLNB, these patients would not undergo SLNB and would likely not receive adjuvant therapy, which has shown to be effective at prolonging time to recurrence in node-positive patients.

Greenhaw et al (2018) also reported that in 219 AJCC stage I patients, 201 had DecisionDx class 1 (low risk) scores and 18 had DecisionDx class 2 (high risk) scores. The only metastasis in stage I patients occurred in a patient with a DecisionDx class 1 score. Therefore with respect to the proposed uses of identifying higher risk patients that should receive adjuvant therapy or enhanced surveillance, none of their stage 1 patients benefited from DecisionDx testing but 18 (8%) were incorrectly identified as high-risk for metastasis and could have received unnecessary treatment or surveillance

Clinically Useful

A test is clinically useful if the results inform management decisions that improve the net health outcome of care. The net health outcome can be improved if patients receive correct therapy, or more effective therapy, or avoid unnecessary therapy, or avoid unnecessary testing.

Direct Evidence

Direct evidence of clinical utility is provided by studies that have compared health outcomes for patients managed with and without the test. Because these are intervention studies, the preferred evidence would be from randomized controlled trials.

No direct evidence of clinical utility was identified.

Chain of Evidence

Indirect evidence on clinical utility rests on clinical validity. If the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility.

Four decision-impact studies have been published reporting on the impact of DecisionDx on physicians’ management decisions. Given the lack of established clinical validity and no reported long-term outcomes of the test used to select patients for active surveillance, it is not known whether any management changes were clinically appropriate.

For the proposed use of the test as a triage for SLNB (identify patients who can avoid SLNB), performance characteristics are not well-characterized.

For the proposed use of the test as a replacement for SLNB (identify patients who are AJCC stage I/II who should receive adjuvant therapy), performance characteristics are also not well-characterized. In addition, an evidence-based management pathway would be needed to support the chain of evidence. The existing RCTs demonstrating that adjuvant therapy reduces recurrence included node positive patients.

For the proposed use of the test to identify patients who are AJCC stage I/II who should receive enhanced surveillance, there is also a lack of evidence that imaging surveillance or increased frequency of surveillance improves outcomes in stage I//I patients. NCCN guidelines state that imaging surveillance is not recommended for stage I-IIA and can be ‘considered’ for IIB-IV but that there is an absence of meaningful data on the association of rigorous routine surveillance imaging with improved long-term outcome for stage IIB-IIC and the recommendations regarding consideration of imaging surveillance remain controversial. While earlier detection of recurrence is thought to be beneficial because lower tumor burden and younger age are associated with improved treatment response and survival, this has not been proven and RCTs are needed to assess whether enhanced surveillance improves survival. The optimal frequency and duration of follow-up surveillance are not standardized and how the surveillance would be altered for DecisionDx class 2 patients has not be defined.

No evidence was identified that demonstrated that adjuvant therapy or increased surveillance improves net health outcomes in AJCC stage I or II patients who are DecisionDx class 2.

Section Summary: Clinically Useful

There is no direct evidence of clinical utility. A chain of evidence for clinical utility cannot be created due to lack of robust evidence of clinical validity and lack of evidence-based management pathway.

Summary of Evidence

For individuals with suspicious pigmented lesions (based on ABCDE and/or ugly duckling criteria) being considered for biopsy who receive gene expression profiling with the DermTech Pigmented Lesion Assay to determine which lesions should proceed to biopsy, the evidence includes observational studies. Relevant outcomes are overall survival, disease-specific survival, validity, and resource utilization. The Pigmented Lesion Assay has one clinical validity study with many methodologic and reporting limitations. Therefore, performance characteristics are not well-characterized. Also, the test has not been compared with dermoscopy, another tool frequently used to make biopsy decisions. No direct evidence of clinical utility was identified. Given that the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility through a chain of evidence. The evidence is insufficient to determine the effects of the technology on health outcomes.

For individuals who have melanocytic lesions with indeterminate histopathologic features who receive gene expression profiling with the myPath Melanoma test added to histopathology to aid in the diagnosis of melanoma, the evidence includes observational studies. Relevant outcomes are overall survival, disease-specific survival, test validity, change in disease status, treatment-related morbidity. The myPath test has one clinical validity study, which includes long-term follow-up to for metastasis as the reference standard. However, it is not clear if the study population included lesions that were indeterminate following histopathology and the study had other methodologic and reporting limitations. Therefore, performance characteristics are not well-characterized. No direct evidence of clinical utility was identified. Given that the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility through a chain of evidence. The evidence is insufficient to determine the effects of the technology on health outcomes.

For individuals with American Joint Committee on Cancer (AJCC) stage I or II cutaneous melanoma who receive gene expression profiling with the DecisionDx-Melanoma test to inform management decisions regarding enhanced surveillance, the evidence includes retrospective observational studies. Relevant outcomes are overall survival, disease-specific survival, test validity, change in disease status, resource utilization and treatment-related morbidity. The DecisionDx-Melanoma test has three independent clinical validity studies that have reported five-year recurrence-free survival (RFS) in AJCC stage I or II patients. Gerami et al (2015) reported RFS rates of 37% for DecisionDx class 2 (high risk) in patients in AJCC stage I and II patients combined. Zager et al (2018) reported RFS rates of 85% (95% CI, 74% to 97%) for DecisionDx class 2 patients in AJCC stage 1 and 55% (95% CI, 44% to 69%) for DecisionDx class 2 in AJCC stage II disease. RFS does not appear to be well characterized as evidenced by the variation in estimates across studies. This indication is to 'rule-in' patients for enhanced surveillance; therefore, specificity and positive predictive value are key performance characteristics. Zager et al (2018) and Greenhaw et al (2018) the specificities were 71% and 87% respectively while the PPV were 48% and 24%, respectively. The PPV suggests that the majority of patients identified as high risk by the DecisionDx test would not develop metastasis and would be unnecessarily subjected to additional surveillance. Greenhaw et al (2018) also reported that in 219 AJCC stage I patients, 201 had DecisionDx class 1 (low risk) scores and 18 had DecisionDx class 2 (high risk) scores. The only metastasis in stage I patients occurred in a patient with a DecisionDx class 1 score. Therefore none of their stage 1 patients benefited from DecisionDx testing but 18 (8%) were incorrectly identified as high-risk for metastasis and could have received unnecessary surveillance. There is no evidence that changes to the frequency and methods for surveillance improve outcomes. Given that the evidence is insufficient to demonstrate test performance and there is no evidence that changes in surveillance improve outcomes, no inferences can be made about clinical utility through a chain of evidence. The evidence is insufficient to determine the effects of the technology on health outcomes.

For individuals with American Joint Committee on Cancer (AJCC) stage I or II cutaneous melanoma who receive gene expression profiling with the DecisionDx-Melanoma test to inform management decisions regarding adjuvant therapy, the evidence includes retrospective observational studies. Relevant outcomes are overall survival, disease-specific survival, test validity, change in disease status, resource utilization and treatment-related morbidity. The DecisionDx-Melanoma test has 3 independent clinical validity studies that have reported 5-year recurrence-free survival (RFS) in AJCC stage I or II patients. Gerami et al (2015) reported RFS rates of 37% for DecisionDx class 2 (high risk) in patients in AJCC stage I and II patients combined. Zager et al (2018) reported RFS rates of 85% (95% CI, 74% to 97%) for DecisionDx class 2 patients in AJCC stage 1 and 55% (95% CI, 44% to 69%) for DecisionDx class 2 in AJCC stage II disease. RFS does not appear to be well characterized as evidenced by the variation in estimates across studies. This indication is to 'rule-in' patients for adjuvant therapy; therefore, specificity and positive predictive value are key performance characteristics. Zager et al (2018) and Greenhaw et al (2018) the specificities were 71% and 87% respectively while the PPV were 48% and 24%, respectively. The PPV suggests that the majority of patients identified as high risk by the DecisionDx test would not develop metastasis and would be unnecessarily subjected to additional treatment. Greenhaw et al (2018) also reported that in 219 AJCC stage I patients, 201 had DecisionDx class 1 (low risk) scores and 18 had DecisionDx class 2 (high risk) scores. The only metastasis in stage I patients occurred in a patient with a DecisionDx class 1 score. Therefore none of their stage 1 patients benefited from DecisionDx testing but 18 (8%) were incorrectly identified as high-risk for metastasis and could have received unnecessary treatment. There is no evidence that adjuvant therapy improves outcomes in these patients. Given that the evidence is insufficient to demonstrate test performance and there is no evidence that adjuvant therapy improves outcomes, no inferences can be made about clinical utility through a chain of evidence. The evidence is insufficient to determine the effects of the technology on health outcomes.

For individuals with cutaneous melanoma with clinically negative sentinel node basins who are being considered for sentinel lymph node biopsy who receive gene expression profiling with the DecisionDx-Melanoma test to determine whether to perform SLNB, evidence includes retrospective observational studies. Relevant outcomes are overall survival, disease-specific survival, test validity, change in disease status, resource utilization and treatment-related morbidity. The DecisionDx-Melanoma test has three independent clinical validity studies that have reported five-year recurrence-free survival (RFS) in AJCC stage I or II patients. Gerami et al (2015) reported RFS rates of 98% in DecisionDx class 1 (low risk) without CIs, in AJCC stage I or II patients. Zager et al (2017) reported RFS rates of 96% (95% CI, 94% to 99%) for DecisionDx class 1 in patients with AJCC stage I disease; they also reported RFS rates of 74% (95% CI, 60% to 91%) for DecisionDx class 1 in patients with AJCC stage II disease. Although CIs were not available for the first study, RFS does not appear to be well-characterized as evidenced by the variation in estimates across studies. Zager et al (2017) also reported that in 56 patients who were DecisionDx class 1 (low risk) but SLNB-positive, 22 recurrences (39%) occurred over five years. If the DecisionDx test were used as a triage for SLNB, these patients would not undergo SLNB and would likely not receive adjuvant therapy, which has shown to be effective at prolonging time to recurrence in node-positive patients. No direct evidence of clinical utility was identified. Given that the evidence is insufficient to demonstrate test performance, no inferences can be made about clinical utility through a chain of evidence. The evidence is insufficient to determine the effects of the technology on health outcomes.

Practice Guidelines and Position Statements

National Comprehensive Cancer Network

The National Comprehensive Cancer Network guidelines (v.2.2019) for melanoma made the following statements on use of gene expression profiling. “While there is interest in newer prognostic molecular techniques such as gene expression profiling to differentiate melanomas at low versus high risk for metastasis, routine (baseline) prognostic genetic testing of primary cutaneous melanomas (before or following sentinel lymph node biopsy) is not recommended outside of a clinical study (trial).”

The guidelines state the following regarding diagnostic testing for indeterminate melanocytic neoplasms following histopathology: "They may be used on a case-by-case basis in ambiguous melanocytic tumors; however, their utility is still under evaluation, and more data are needed before they can be routinely recommended." Specifically regarding the GEP test, the guidelines state that '... long-term follow-up is required to validate the prognostic significance of this test'.

The guidelines state the following regarding prognostic testing: "Commercially available GEP tests are marketed as being able to classify cutaneous melanoma into separate categories based on metastasis. However, it remains unclear whether these tests provide clinically actionable prognostic information when used in addition to or in comparison with known clinicopathologic factors or multivariable nomgrams that incorporate patient sex, age, tumor location and thickness, ulceration, mitotic rate, lymphovascular invasion, microsatellites, and SLNB status. Furthermore, the impact of these tests on treatment outcomes or follow-up schedules has not been established.

American Academy of Dermatology

The American Academy of Dermatology (AAD) published guidelines of care for the management of primary cutaneous melanoma in 2019. The guidelines state the following regarding GEP tests:

  • Regarding diagnostic GEP tests:
    • "Diagnostic molecular techniques are still largely investigative and may be appropriate as ancillary tests in equivocal melanocytic neoplasms, but they are not recommended for routine diagnostic use in CM. These include comparative genomic hybridization, fluorescence in situ hybridization, gene expression profiling (GEP), and (potentially) next-generation sequencing."
    • "Ancillary diagnostic molecular techniques (e.g., CGH, FISH, GEP) may be used for equivocal melanocytic neoplasms."

  • Regarding prognostic GEP tests:
    • "...there is also insufficient evidence of benefit to recommend routine use of currently available prognostic molecular tests, including GEP, to provide more accurate prognosis beyond currently known clinicopathologic factors" (Strength of evidence: C, Level of evidence II/III)
    • "Going forward, GEP assays should be tested against all known histopathologic prognostic factors and contemporary eighth edition of AJCC CM staging to assess their additive value in prognostication."
    • "Routine molecular testing, including GEP, for prognostication is discouraged until better use criteria are defined. The application of molecular information for clinical management (e.g., sentinel lymph node eligibility, follow-up, and/or therapeutic choice) is not recommended outside of a clinical study or trial."

U.S. Preventive Services Task Force Recommendations

Not applicable

KEY WORDS:

Cutaneous melanoma, gene expression profiling, GEP, DermTech Pigmented Lesion Assay, myPath Melanoma, DecisionDx-Melanoma, PLA, pigmented lesion assay, Merkel SmT, MerkelVirus VP1

APPROVED BY GOVERNING BODIES:

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. The Pigmented Lesion Assay, myPath Melanoma, and DecisionDx-Melanoma tests are available under the auspices of the Clinical Laboratory Improvement Amendments. Laboratories that offer laboratory-developed tests must be licensed by the Clinical Laboratory Improvement Amendments for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

BENEFIT APPLICATION:

Coverage is subject to member’s specific benefits. Group specific policy will supersede this policy when applicable.

ITS: Home Policy provisions apply.

FEP: Special benefit consideration may apply. Refer to member’s benefit plan. FEP does not consider investigational if FDA approved and will be reviewed for medical necessity.

CURRENT CODING:

CPT Codes:

81479

Unlisted molecular pathology procedure

81599

Unlisted multianalyte assay with algorithmic analysis

84999

Unlisted chemistry procedure

0058U

Oncology (Merkel cell carcinoma), detection of antibodies to the Merkel cell polyoma virus oncoprotein (small T antigen), serum, quantitative (Effective 07/01/2018)

0059U

Oncology (Merkel cell carcinoma), detection of antibodies to the Merkel cell polyoma virus capsid protein (VP1), serum, reported as positive or negative (Effective 07/01/2018)

 

 

Prior to 7/1/2019, there were no specific codes for DermTech PLA or MyPath Melanoma.  Effective for dates of service on and after 7/1/19:

0089U

Oncology (melanoma), gene expression profiling by RTqPCR, PRAME and LINC00518, superficial collection using adhesive patch(es) (Effective 07/1/19)

0090U

Oncology (cutaneous melanoma) mRNA gene expression profiling by RT-PCR of 23 genes (14 content and 9 housekeeping), utilizing formalin-fixed paraffin embedded tissue, algorithm reported as a categorical result (i.e., benign, indeterminate, or malignant) (Effective 07/1/19)

Previous Coding:

CPT:

There are currently no specific codes for the panel tests which are applicable to this policy. There are two genes which are included in the DermTech PLA test which are included in:

81401

LINC00518 and PRAME

81401 does not include the remaining genes however, so this code does not represent “DermTech PLA”, “MyPath Melanoma” or “DecisionDx UM Melanoma”.

REFERENCES:

  1. Abbasi NR, Shaw HM, Rigel DS, et al. Early diagnosis of cutaneous melanoma: revisiting the ABCD criteria. Jama. Dec 8 2004; 292(22):2771-2776.
  2. Berger AC, Davidson RS, Poitras JK, et al. Clinical impact of a 31-gene expression profile test for cutaneous melanoma in 156 prospectively and consecutively tested patients. Curr Med Res Opin. Sep 2016; 32(9):1599-1604.
  3. Bossuyt PM, Irwig L, Craig J, et al. Comparative accuracy: assessing new tests against existing diagnostic pathways. Bmj. May 6 2006; 332(7549):1089-1092.
  4. Caini S, Gandini S, Sera F, et al. Meta-analysis of risk factors for cutaneous melanoma according to anatomical site and clinico-pathological variant. Eur J Cancer. Nov 2009; 45(17):3054-3063.
  5. Callender GG, Gershenwald JE, Egger ME, et al. A novel and accurate computer model of melanoma prognosis for patients staged by sentinel lymph node biopsy: comparison with the American Joint Committee on Cancer model. J Am Coll Surg. Apr 2012; 214(4):608-617; discussion 617-609.
  6. Castle Biosciences. Cutaneous Melanoma: DecisionDx-Melanoma Overview. n.d.; castlebiosciences.com/tests/cutaneous-melanoma/. Accessed March 30, 2018.
  7. Chang AE, Karnell LH, Menck HR. The National Cancer Data Base report on cutaneous and noncutaneous melanoma: a summary of 84,836 cases from the past decade. The American College of Surgeons Commission on Cancer and the American Cancer Society. Cancer. Oct 15 1998;83(8):1664-1678.
  8. Chen T, Fallah M, Forsti A, et al. Risk of next melanoma in patients with familial and sporadic melanoma by number of previous melanomas. JAMA Dermatol. Jun 2015; 151(6):607-615.
  9. Clarke LE, Flake DD, 2nd, Busam K, et al. An independent validation of a gene expression signature to differentiate malignant melanoma from benign melanocytic nevi. Cancer. Feb 15 2017; 123(4):617-628.
  10. Clarke LE, Warf MB, Flake DD, 2nd, et al. Clinical validation of a gene expression signature that differentiates benign nevi from malignant melanoma. J Cutan Pathol. Apr 2015; 42(4):244-252.
  11. Cockerell C, Tschen J, Billings SD, et al. The influence of a gene-expression signature on the treatment of diagnostically challenging melanocytic lesions. Per Med. Mar 2017; 14(2):123-130.
  12. Cockerell CJ, Tschen J, Evans B, et al. The influence of a gene expression signature on the diagnosis and recommended treatment of melanocytic tumors by dermatopathologists. Medicine (Baltimore). Oct 2016; 95(40):e4887.
  13. DermTech. Pigmented Lesion Assay: Non-invasive gene expression analysis of pigmented skin lesions. Performance and Development Notes. 2015; www.dermtech.com/wp-content/uploads/2015/10/White-Paper-DermTech-Melanoma-Assay-.pdf. Accessed March 16, 2018.
  14. Dicker TJ, Kavanagh GM, Herd RM, et al. A rational approach to melanoma follow-up in patients with primary cutaneous melanoma. Scottish Melanoma Group. Br J Dermatol. Feb 1999; 140(2):249-254.
  15. Dillon LD, Gadzia JE, Davidson RS, et al. Prospective, multicenter clinical impact evaluation of a 31-gene expression profile test for management of melanoma patients. Skin. 2018; 2(2):111-121.
  16. Engasser HC, Warshaw EM. Dermatoscopy use by US dermatologists: a cross-sectional survey. J Am Acad Dermatol. Sep 2010; 63(3):412-419, 419.e411-412.
  17. Eggermont AM, Chiarion-Sileni V, Grob JJ, et al. Prolonged survival in stage III melanoma with ipilimumab adjuvant therap. N Engl J Med. Nov 10 2016; 375(19):1845-1855.
  18. Farberg AS, Glazer AM, White R, et al. Impact of a 31-gene expression profiling test for cutaneous melanoma on dermatologists' clinical management decisions. J Drugs Dermatol. May 1 2017; 16(5):428-431.
  19. Faries MB, Steen S, Ye X, et al. Late recurrence in melanoma: clinical implications of lost dormancy. J Am Coll Surg. Jul 2013; 217(1):27-34; discussion 34-26.
  20. Ferris LK, Jansen B, Ho J, et al. Utility of a noninvasive 2-gene molecular assay for cutaneous melanoma and effect on the decision to biopsy. JAMA Dermatol. Jul 1 2017; 153(7):675-680.
  21. Gaiser T, Kutzner H, Palmedo G, et al. Classifying ambiguous melanocytic lesions with FISH and correlation with clinical long-term follow up. Mod Pathol. Mar 2010; 23(3):413-419.
  22. Gandini S, Sera F, Cattaruzza MS, et al. Meta-analysis of risk factors for cutaneous melanoma: III. Family history, actinic damage and phenotypic factors. Eur J Cancer. Sep 2005; 41(14):2040-2059.
  23. Garbe C, Paul A, Kohler-Spath H, et al. Prospective evaluation of a follow-up schedule in cutaneous melanoma patients: recommendations for an effective follow-up strategy. J Clin Oncol. Feb 1 2003; 21(3):520-529.
  24. Gerami P, Alsobrook JP, 2nd, Palmer TJ, et al. Development of a novel noninvasive adhesive patch test for the evaluation of pigmented lesions of the skin. J Am Acad Dermatol. Aug 2014; 71(2):237-244.
  25. Gerami P, Cook RW, Russell MC, et al. Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy. J Am Acad Dermatol. May 2015; 72(5):780-785 e783.
  26. Gerami P, Cook RW, Wilkinson J, et al. Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res. Jan 1 2015; 21(1):175-183.
  27. Gerami P, Yao Z, Polsky D, et al. Development and validation of a noninvasive 2-gene molecular assay for cutaneous melanoma. J Am Acad Dermatol. Jan 2017; 76(1):114-120 e112.
  28. Gershenwald JES, R.A.; Hess, K.R.; et al. Melanoma of the Skin. Chicago, IL: American Joint Committee on Cancer; 2017
  29. Gilchrest BA, Eller MS, Geller AC, et al. The pathogenesis of melanoma induced by ultraviolet radiation. N Engl J Med. Apr 29 1999; 340(17):1341-1348.
  30. Goldstein AM, Chan M, Harland M, et al. Features associated with germline CDKN2A mutations: a GenoMEL study of melanoma-prone families from three continents. J Med Genet. Feb 2007; 44(2):99-106.
  31. Greenhaw, BB, Zitelli, JJ, Brodland, DD. Estimation of Prognosis in Invasive Cutaneous Melanoma: An Independent Study of the Accuracy of a Gene Expression Profile Test.. Dermatol Surg, 2018 Jul 12;44(12).
  32. Grob JJ, Bonerandi JJ. The 'ugly duckling' sign: identification of the common characteristics of nevi in an individual as a basis for melanoma screening. Arch Dermatol. Jan 1998; 134(1):103-104.
  33. Hsueh EC, DeBloom JR, Lee J, et al. Interim analysis of survival in a prospective, multi-center registry cohort of cutaneous melanoma tested with a prognostic 31-gene expression profile test. J Hematol Oncol. Aug 29 2017; 10(1):152
  34. Jiang AJ, Rambhatla PV, Eide MJ. Socioeconomic and lifestyle factors and melanoma: a systematic review. Br J Dermatol. Apr 2015; 172(4):885-915.
  35. Ko JS, Matharoo-Ball B, Billings SD, et al. Diagnostic distinction of malignant melanoma and benign nevi by a gene expression signature and correlation to clinical outcomes. Cancer Epidemiol Biomarkers Prev. Jul 2017; 26(7):1107-1113.
  36. Long GV, Hauschild A, Santinami M, et al. Adjuvant dabrafenib plus trametinib in stage III BRAF-mutated melanomas. N Engl J Med. Nov 9 2017; 377(19):1813-1823.
  37. Murzaku EC, Hayan S, Rao BK. Methods and rates of dermoscopy usage: a cross-sectional survey of US dermatologists stratified by years in practice. J Am Acad Dermatol. Aug 2014; 71(2):393-395.
  38. Myriad. n.d. Understanding the myPath® Melanoma Results; www.mypathmelanoma.com/about-mypath-melanoma/understanding-the-mypath-melanoma-results/. Accessed March 30, 2018.
  39. National Center for Biotechnology Information. PRAME preferentially expressed antigen in melanoma. 2018; www.ncbi.nlm.nih.gov/gene/23532. Accessed March 30, 2018.
  40. National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology: Melanoma. Version 2.2018. www.nccn.org/professionals/physician_gls/pdf/melanoma.pdf. Accessed March 23, 2018.
  41. Schuitevoerder D, Heath M, Cook RW, et al. Impact of gene expression profiling on decision-making in clinically node negative melanoma patients after surgical staging. J Drugs Dermatol. Feb 1 2018; 17(2):196-199.
  42. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. Jan 2018; 68(1):7-30.
  43. Soong SJ, Ding S, Coit DG, et al. AJCC: Individualized melanoma patient outcome prediction tools. n.d.; www.melanomaprognosis.net/. Accessed March 21, 2018.
  44. Vergier B, Prochazkova-Carlotti M, de la Fouchardiere A, et al. Fluorescence in situ hybridization, a diagnostic aid in ambiguous melanocytic tumors: European study of 113 cases. Mod Pathol. May 2011; 24(5):613-623.
  45. Vestergaard ME, Macaskill P, Holt PE, et al. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol. Sep 2008; 159(3):669-676.
  46. Wachsman W, Morhenn V, Palmer T, et al. Noninvasive genomic detection of melanoma. Br J Dermatol. Apr 2011; 164(4):797-806.
  47. Weber J, Mandala M, Del Vecchio M, et al. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med. Nov 9 2017; 377(19):1824-1835.
  48. Wendt J, Rauscher S, Burgstaller-Muehlbacher S, et al. Human determinants and the role of melanocortin-1 receptor variants in melanoma risk independent of UV radiation exposure. JAMA Dermatol. Jul 1 2016; 152(7):776-782.
  49. Wiesner T, Obenauf AC, Murali R, et al. Germline mutations in BAP1 predispose to melanocytic tumors. Nat Genet. Aug 28 2011; 43(10):1018-1021.
  50. Wilson RL, Yentzer BA, Isom SP, et al. How good are US dermatologists at discriminating skin cancers? A number-needed-to-treat analysis. J Dermatolog Treat. Feb 2012; 23(1):65-69.
  51. Wong SL, Balch CM, Hurley P, et al. Sentinel lymph node biopsy for melanoma: American Society of Clinical Oncology and Society of Surgical Oncology joint clinical practice guideline. J Clin Oncol. Aug 10 2012; 30(23):2912-2918.
  52. Wrightson WR, Wong SL, Edwards MJ, et al. Complications associated with sentinel lymph node biopsy for melanoma. Ann Surg Oncol. Jul 2003; 10(6):676-680.
  53. Zager JS, Gastman BR, Leachman S, et al. Performance of a prognostic 31-gene expression profile in an independent cohort of 523 cutaneous melanoma patients. BMC Cancer. Feb 5 2018; 18(1):130.

POLICY HISTORY:

Medical Policy Panel, May 2018

Medical Policy Group, June 2018 (2): New policy created.

Medical Policy Administration Committee, July 2018

Available for comment June 29, 2018 through August 13, 2018.

Medical Policy Group, June 2018: Quarterly coding update, July 2018. Added new CPT codes 0058U and 0059U to Current Coding. Added new Key Words: Merkel SmT and Merkel Virus VP1.

Medical Policy Panel, December 2018

Medical Policy Group, January 2019 (9): Annual updates to Key Points and Description. No change to policy statement.

Medical Policy Panel, May 2019

Medical Policy Group, May 2019 (9): 2019 Updates to Key Points, Description, References. No change to policy statement.

Medical Policy Group, June 2019: July 2019 quarterly coding update.  Added new CPT codes 0089U and 0090U to Current Coding.  Created Previous Coding section for 81401.


This medical policy is not an authorization, certification, explanation of benefits, or a contract. Eligibility and benefits are determined on a case-by-case basis according to the terms of the member’s plan in effect as of the date services are rendered. All medical policies are based on (i) research of current medical literature and (ii) review of common medical practices in the treatment and diagnosis of disease as of the date hereof. Physicians and other providers are solely responsible for all aspects of medical care and treatment, including the type, quality, and levels of care and treatment.

This policy is intended to be used for adjudication of claims (including pre-admission certification, pre-determinations, and pre-procedure review) in Blue Cross and Blue Shield’s administration of plan contracts.

The plan does not approve or deny procedures, services, testing, or equipment for our members. Our decisions concern coverage only. The decision of whether or not to have a certain test, treatment or procedure is one made between the physician and his/her patient. The plan administers benefits based on the member’s contract and corporate medical policies. Physicians should always exercise their best medical judgment in providing the care they feel is most appropriate for their patients. Needed care should not be delayed or refused because of a coverage determination.

As a general rule, benefits are payable under health plans only in cases of medical necessity and only if services or supplies are not investigational, provided the customer group contracts have such coverage.

The following Association Technology Evaluation Criteria must be met for a service/supply to be considered for coverage:

1. The technology must have final approval from the appropriate government regulatory bodies;

2. The scientific evidence must permit conclusions concerning the effect of the technology on health outcomes;

3. The technology must improve the net health outcome;

4. The technology must be as beneficial as any established alternatives;

5. The improvement must be attainable outside the investigational setting.

Medical Necessity means that health care services (e.g., procedures, treatments, supplies, devices, equipment, facilities or drugs) that a physician, exercising prudent clinical judgment, would provide to a patient for the purpose of preventing, evaluating, diagnosing or treating an illness, injury or disease or its symptoms, and that are:

1. In accordance with generally accepted standards of medical practice; and

2. Clinically appropriate in terms of type, frequency, extent, site and duration and considered effective for the patient’s illness, injury or disease; and

3. Not primarily for the convenience of the patient, physician or other health care provider; and

4. Not more costly than an alternative service or sequence of services at least as likely to produce equivalent therapeutic or diagnostic results as to the diagnosis or treatment of that patient’s illness, injury or disease.