Medical Policy

Policy Num:      11.003.105
Policy Name:    Microarray-Based Gene Expression Profile Testing for Multiple Myeloma Risk Stratification
Policy ID:          [11.003.105]  [Ac  / B / M- / P-]  [2.04.97]

Last Review:  December 05, 2024
Next Review:  November 20, 2025
 

Related Policies:

08.001.033 - Hematopoietic Cell Transplantation for Plasma Cell Dyscrasias, Including Multiple Myeloma and POEMS Syndrome

Microarray-Based Gene Expression Profile Testing for Multiple Myeloma Risk Stratification

Summary

Summary

Description

Multiple myeloma is a genetically complex-and invariably fatal-disease. A host of well-characterized factors related to tumor biology, tumor burden, and patient-centered characteristics are used to stratify patients into high-, intermediate-, and standard-risk categories for prognostic purposes, as well as determining treatment intensity. However, clinical outcomes have varied among patients in the same risk category who received similar therapy. Thus, more specific methods have been sought to classify multiple myeloma; one such method being proposed is the utilization of a microarray-based gene expression profile (GEP) analysis, which serves to reveal the underlying activity of cellular biologic pathways. This method lends itself to a variety of benefits including the ability to risk-stratify patients with multiple myeloma, as well as guide treatment decisions.

Summary of Evidence

For individuals who have multiple myeloma who received risk stratification using a GEP test, the evidence includes retrospective series that correlate risk scores with survival. Relevant outcomes are progression-free survival, overall survival, disease-specific survival, test validity, and other test performance measures. The microarray-based GEP70 test (MyPRS/MyPRS Plus) has been reported to risk-stratify multiple myeloma patients. Some predictive models in the body of evidence combine risk status as determined by the GEP70 test with additional clinical or genetic variables. Patients with a high GEP70 risk score have a substantially increased risk of mortality compared with patients without a high score. However, there is no evidence (from available studies) that this test would add incremental value to existing risk stratification methods; nor have any studies demonstrated the need to prospectively allocate patients to risk-based therapies based on the GEP70 score. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome..

Additional Information

Not applicable.

OBJECTIVE

The objective of this evidence review is to determine whether risk stratification using a gene expression profile risk score improves the net health outcome in individuals with multiple myeloma.

POLICY statements

Microarray-based gene expression profile testing for multiple myeloma is considered investigational for all indications.

POLICY GUIDELINES

According to Mayo Clinic recommendations, a large number of prognostic factors have been validated and categorized into 3 main groups: tumor biology, tumor burden, and patient-related factors. These factors must be considered to individualize the choice of therapy in individuals with multiple myeloma (Table PG1).

Table PG1. Prognostic Factors in Multiple Myeloma

Coding

See the Codes table for details.

BENEFIT APPLICATION

BlueCard/National Account Issues

No applicable information.

Benefits are determined by the group contract, member benefit booklet, and/or individual subscriber certificate in effect at the time services were rendered.  Benefit products or negotiated coverages may have all or some of the services discussed in this medical policy excluded from their coverage.

BACKGROUND

Multiple Myeloma

Multiple myeloma is a genetically complex - and invariably fatal - neoplasm of plasma cells.^1,

Disease Description

Multiple myeloma is a malignant plasma cell dyscrasia characterized by clonal proliferation of plasma cells derived from B cells in the bone marrow.^2, It accounts for about 1 in every 100 cancers and 13% of hematologic cancers. The American Cancer Society has estimated 35,780 new cases of multiple myeloma will occur in the U.S. in 2024, and some 12,540 deaths will occur due to the disease.^3, The annual age-adjusted incidence is about 7 cases per 100,000 persons, with a median age-at-diagnosis of about 70 years. Before the advent of current treatment protocols, most patients with multiple myeloma succumbed to their disease within 5 to 10 years; in the prechemotherapy era, median survival was less than 1 year. Among patients who present at an age younger than 60 years, 10-year overall survival with current treatment protocols may now exceed 30%.^4, Black individuals have double the risk of multiple myeloma compared with White individuals and tend to be diagnosed with multiple myeloma at a younger age.^5, Furthermore, Hispanic individuals have a slightly higher incidence rate than White individuals (6.7 per 100,000 vs. 6.2 per 100,100). Recent US Surveillance, Epidemiology, and End Results Program data estimates that the 5-year age-adjusted mortality rate of Black individuals due to multiple myeloma is 6.2 per 100,000, compared with 3.1 per 100,000 White individuals. However, the 5-year relative survival appears to comparable at 53.9% and 51.3% for Black and White individuals in the US, respectively. When treatment is standardized, there is some evidence that Black individuals have superior survival after multiple myeloma diagnosis compared to White individuals, suggesting that Black individuals have a more indolent disease subtype. However, significant disparities in treatment use, access, and referral patterns persist that may impair clinical outcomes.

Criteria for the diagnosis, staging, and response assessment of multiple myeloma developed by the International Myeloma Working Group are in widespread use.^6,7,8, The decision to treat is based on criteria set forth in the diagnosis of multiple myeloma, which includes calcium elevation; renal insufficiency; anemia; and bone disease (CRAB). Patients with monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma do not require therapy, irrespective of any associated risk factors-except on specifically targeted protocols.

Pathogenesis and Genetic Architecture of Multiple Myeloma

Multiple myeloma is a complex disease that presents itself in distinct clinical phases and risk levels. They include MGUS and smoldering multiple myeloma (also known as asymptomatic myeloma).^9, Monoclonal gammopathy of undetermined significance is a generally benign condition, with a transformation rate to symptomatic plasma cell disorders of about 1% to 2% annually.^10, Smoldering multiple myeloma represents a progression from MGUS to frank multiple myeloma; the risk of the disease transforming to multiple myeloma is about 10% for the first 5 years.^10, Although both of these conditions lack many clinical features of multiple myeloma, they may ultimately share characteristics that necessitate therapy. By contrast, symptomatic multiple myeloma is defined by specific clinical symptoms, accumulation of monoclonal immunoglobulin proteins in the blood or urine, and associated organ dysfunction (including nephropathy and neuropathy). The acronym CRAB reflects the hallmark features of multiple myeloma.^7, Premyeloma plasma cells initially require interaction with the bone marrow microenvironment; however, during disease progression, the cells develop the ability to proliferate outside the bone marrow, manifesting as extramedullary myeloma and plasma cell leukemia. These “bone marrow independent” cells represent the end stages in a multistep transformation process from normal to multiple myeloma.

As outlined below, complex genetic abnormalities, commonly identified in multiple myeloma plasma cells, are considered to play major roles in disease initiation, progression, and pathogenesis. Further, these abnormalities are used in conjunction with laboratory and radiographic studies to stratify patients for therapeutic decisions.^6,11,12,

Diagnosis

Cytogenetic and other laboratory tests identify markers to classify newly diagnosed multiple myeloma patients into high, intermediate, and standard clinical risk categories. The level of risk reflects the aggressiveness of the disease, and ultimately dictates the intensity of initial treatment.^6,13,14,15, Thus, a risk-adapted approach provides optimal therapy to patients, ensuring intense treatment for those with the aggressive disease. Further, this approach minimizes toxic effects, thereby delivering sufficient-but less-intense-therapy for those with a lower risk of disease. However, it should be noted that clinical outcomes can vary substantially, using even the most standard of methods, among patients with the same estimated risk who undergo a similar intensity of treatment.

Microarray-based gene expression profile (GEP) analysis can be used to estimate the underlying activity of cellular biological pathways, and these pathways control a host of mechanisms such as cell division, cell proliferation, apoptosis, metabolism, and other signaling pathways. Relative over- or underexpression of these pathways is considered to mirror disease aggressiveness, independent of cytogenetics and other laboratory measures. Gene expression profile analysis has been proposed as a means to more finely stratify multiple myeloma patients into risk categories for 2 purposes: (1) to personalize therapy selection according to tumor biology^14,15, and (2) to avoid over- or undertreating patients. Moreover, GEP analysis could be used as a supplement to existing stratification methods, or as a stand-alone test; however, further study is needed to confirm that the analysis has the capability to perform those roles.

The term gene expression refers to the process by which the coded information of genes (DNA) is transcribed into messenger RNA (mRNA) and translated into proteins. A GEP assay simultaneously examines the patterns of multiple genes in a single tissue sample; it does this to identify those that are actively producing mRNA or not, ultimately producing proteins or not. By concurrently measuring the cellular levels of mRNA of thousands of genes, a GEP test creates a picture of the rate at which those genes are expressed in a tissue sample.

Gene expression profile tests are not “genetic” tests. Genetic tests measure an individual DNA signature to identify genetic changes or variants that remain constant in the genome. Gene expression tests measure the activity of mRNA in a tissue or bodily fluid at a single point, reflecting an individual’s current disease state (or the likelihood of developing a disease). However, because mRNA levels are dynamic and change as a result of disease processes or environmental signals, dynamic changes in these processes can be studied over time. This information thus reflects the pathogenic process, and in theory, can be used to assess the effects of therapeutic interventions or select therapy based on specifically expressed gene targets.

Gene Expression Analysis of Cancer Using Microarray Technology

Gene expression profile analysis using microarray technology is based on the Watson-Crick pairing of complementary nucleic acid molecules.^16, A collection of DNA sequences, referred to as “probes,” are “arrayed” on miniaturized solid support (the “microarray”). They are used to determine the concentration of the corresponding complementary mRNA sequences, called “targets,” isolated from a tissue sample. Laboratory advancements in attaching nucleic acid sequences to solid supports, combined with robotic technology, have allowed investigators to miniaturize the scale of the reactions. As a result of these advances, it is possible to assess the expression of thousands of different genes in a single reaction.

A basic microarray GEP analysis uses mRNA targets that have been both harvested from a patient’s tissue sample and labeled with a fluorescent dye.^17, These samples are hybridized to the DNA probe sequences attached to the microarray medium, then incubated in the presence of mRNA from a different sample labeled with a different fluorescent dye. In a 2 color experimental design, samples can be directly compared with one another or with a common reference mRNA, and their relative expression levels can be quantified. After hybridization, grayscale images corresponding to fluorescent signals are obtained by scanning the microarray with dedicated instruments; the fluorescence intensity corresponding to each gene is then quantified by specific software. After normalization, the intensity of the hybridization signals can be compared to detect differential expression by using sophisticated computational and statistical techniques.

Technical variability is a major concern with microarray technologies for clinical management^17,; eg, the source of mRNA is a technical variable that can affect test results. A typical biopsy sample from a solid tumor contains a mixture of malignant and normal (stromal) cells that, in turn, will yield total RNA that reflects all the cells contained in the specimen. To address this, tissue samples may be macro- or microdissected (prior to RNA extraction) to ensure that the specimens contain a sufficiently representative percentage of cancer cells to reflect the disease. For analysis of hematologic cancers, including multiple myeloma, immunomagnetic cell separation technology is used to isolate and enrich cancerous cells from bone marrow aspirates that contain a mixture of cell types.^15,18,

The instability of mRNA relative to DNA complicates GEP analysis studies, especially when comparing the method with genomic analyses. Two factors that affect RNA quality include preanalysis storage time and the reagents used to prepare mRNA. Moreover, pH changes in the storage media can trigger mRNA degradation, as can ribonucleases present in cells, which can remain active in the RNA preparation if not stringently controlled.

As noted, Watson-Crick hybridization of complementary nucleic acid moieties in the sequences of mRNA and DNA is the basis of any microarray-based GEP test. This means that sequence selection and gene annotation are among the most important factors that can contribute to analytic variability, hence validity, in results.^19, Different technologic platforms, protocols, and reagents can affect the analytic variability of the results, and therefore affect reproducibility within and across laboratories. Gene expression measures are virtually never used as raw output but undergo sequential steps of mathematical transformation; thus, data preprocessing and analysis may increase variability in results. Moreover, different levels of gene expression can be further processed and combined, according to complex algorithms, to obtain composite summary measurements that are associated with the phenotype(s) under investigation. A statistical analytic technique known as “unsupervised clustering analysis” is applied to the data to produce a visual display, known as a “dendrogram,” that shows a hierarchy of similar genes, differentially expressed as mRNA.^20,

International standards have been developed to address the quality of microarray-based GEP analysis.^17, These standards focus on documentation of experimental design, details, and results. Additional topics of interest include interplatform and interlaboratory reproducibility. Quality control efforts emphasize the importance of minimizing the sources of variability in gene expression analysis, thus ensuring that the information derived from such analyses is specific and does not represent accidental associations.

Prognosis and Risk Stratification

Two validated clinical systems are in widespread use to assess prognosis in newly diagnosed multiple myeloma patients: the Durie-Salmon Staging System and the International Staging System.^7,8, The Durie-Salmon Staging System provides a method to measure multiple myeloma tumor burden, based on multiple myeloma cell numbers and clinical, laboratory and imaging studies; however, the system has significant shortcomings due to its use of observer-dependent studies (eg, radiographic evaluation of bone lesions), primarily focused on tumor mass-not behavior. The International Staging System, incorporating serum albumin and β₂-microglobulin measures, is considered valuable because it permits comparison of outcomes across clinical trials; and it is even more reproducible than the Durie-Salmon Staging System. However, the International Staging System is useful only if a diagnosis of multiple myeloma has already been made; it has no role in MGUS, smoldering multiple myeloma, or related plasma cell dyscrasias.^7, Further, the International Staging System does not provide a good estimate of tumor burden, nor is it generally useful for therapeutic risk stratification. In fact, it may not retain prognostic significance in the era of novel drug therapies.^6,

Although multiple myeloma cells may appear morphologically similar across risk levels the disease exhibits substantial genetic heterogeneity that may change with progression or at relapse.^11,12, Investigators have used conventional cytogenetic methods (karyotyping) and fluorescence in situ hybridization to prognostically stratify multiple myeloma patients according to a host of recurrent chromosomal changes (immunoglobulin heavy chain translocations, chromosome deletions, or amplification). This stratification forms the basis of the Mayo Stratification of Myeloma and Risk-Adapted Therapy, an evidence-based algorithm to facilitate treatment decisions for patients with newly diagnosed multiple myeloma (Table 1).^13,

Table 1. Mayo Clinic Stratification of Multiple Myeloma and Risk-Adapted Therapy

In addition to the cytogenetic characteristics noted in Table 1, other findings are typically considered in this model. Although GEP analysis is included in Table 1, the Mayo Clinic does not currently recommend or routinely perform GEP analysis in a nonresearch setting.^13,

The risk stratification model outlined in Table 1 is meant to prognosticate and to determine the treatment approach; it is not used to decide whether to initiate therapy (see Therapy Synopsis subsection).^6, Furthermore, therapeutic outcomes among individuals in these categories may vary significantly, to the extent that additional means of subdividing patients into response groups are under investigation. In particular, molecular profiling using microarray-based methods (see Rationale section).

Therapy Synopsis

Asymptomatic (smoldering) multiple myeloma and MGUS currently require only ongoing clinical observation (this is because early treatment with conventional chemotherapy has shown no benefit). However, for symptomatic patients diagnosed with multiple myeloma, prompt induction therapy is indicated. Induction therapy generally consists of an immunomodulatory drug (most often lenalidomide), a proteasome inhibitor (eg, bortezomib), and dexamethasone, and may include daratumumab.^21, Eligible patients will then undergo autologous hematopoietic cell transplantation; following transplantation, or induction in transplant-ineligible patients, treatment will typically continue with low-dose maintenance therapy (eg, with lenalidomide).

Gene Expression Profile Test

The MyPRS/MyPRS Plus GEP70 test analyzes the human genome to determine the level of aggressiveness of diagnosed multiple myeloma based on 70 of the most relevant genes involved in cellular signaling and proliferation.

Regulatory Status

Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). The MyPRS™/MyPRS Plus™ GEP70 test was acquired by Quest Diagnostics in December 2016. Laboratories that offer laboratory-developed tests must be licensed by the CLIA for high-complexity testing. To date, the U.S. Food and Drug Administration has chosen not to require any regulatory review of this test.

RATIONALE

This evidence review was created in July 2013 and has been updated regularly with searches of the PubMed database. The most recent literature update was performed through August 27, 2024.

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.

Promotion of greater diversity and inclusion in clinical research of historically marginalized groups (e.g., People of Color [African-American, Asian, Black, Latino and Native American]; LGBTQIA (Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, Asexual); Women; and People with Disabilities [Physical and Invisible]) allows policy populations to be more reflective of and findings more applicable to our diverse members. While we also strive to use inclusive language related to these groups in our policies, use of gender-specific nouns (e.g., women, men, sisters, etc.) will continue when reflective of language used in publications describing study populations.

MyPRS/MyPRSPlus

Multiple myeloma is a fatal disease.^1, A host of well-characterized factors related to tumor biology, tumor burden, and patient-centered characteristics are used to stratify individuals into high, intermediate, and standard clinical risk categories for prognostication purposes, as well as to determine treatment intensity. However, clinical outcomes have varied among individuals in the same risk category who received similar therapy. Thus, more specific methods have been sought to classify multiple myeloma; 1 such method being proposed is the utilization of a microarray-based gene expression profile (GEP) analysis, which serves to reveal the underlying activity of cellular biologic pathways.^6,13,14,15,

The MyPRS/MyPRS Plus test was developed primarily using the microarray-based technology described in the Background section.^14, Two key publications have reported the application of this method can do 2 things: (1) construct molecular profiles of multiple myeloma in newly diagnosed patients; and (2) retrospectively associate treatment outcomes with specific GEPs.^22,23,

Clinical Context and Test Purpose

The purpose of a microarray-based GEP test (eg, MyPRS/MyPRS Plus) in individuals who have multiple myeloma is to provide risk stratification information that can be used to guide treatment decisions.

The following PICO was used to select literature to inform this review.

Populations

The relevant population of interest is individuals with multiple myeloma.

Interventions

The test being considered is a microarray-based GEP test (eg, MyPRS/MyPRS Plus), which provides risk stratification information. The level of risk reflects the aggressiveness of the disease, and ultimately dictates the intensity of initial treatment. The MyPRS/MyPRS Plus GEP70 test analyzes the human genome to determine the level of aggressiveness of diagnosed multiple myeloma based on 70 of the most relevant genes involved in cellular signaling and proliferation.

Comparators

Tests such as the following may be used to perform standard clinical risk evaluation for multiple myeloma. Some of these tests may also be part of the diagnostic evaluation.

• complete blood count and differential examination of peripheral blood smear

• chemistry screen plus serum calcium, albumin, lactate dehydrogenase, and β₂-microglobulin

• serum creatinine and glomerular filtration rate estimate

• serum free light chain assay

• serum protein electrophoresis, routine urinalysis, and 24-hour urine collection

• bone marrow aspiration and biopsy with immunophenotyping and fluorescence in situ hybridization

• cross-sectional imaging (eg, computed tomography, positron emission tomography with computed tomography, or magnetic resonance imaging).

Outcomes

Longer-term outcomes involve overall survival (OS) as well as disease-specific morbidity and mortality.

Measurement of long-term outcomes requires follow-up over years; multiple myeloma has a 5-year OS rate of 50%.

Study Selection Criteria

For the evaluation of clinical validity of the microarray-based GEP test (eg, MyPRS/MyPRS Plus) in individuals who have multiple myeloma, studies that meet the following eligibility criteria were considered:

• Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores)

• Included a suitable reference standard (describe the reference standard)

• Patient/sample clinical characteristics were described

• Patient/sample selection criteria were described.

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).

Review of Evidence

Randomized Controlled Trials

A phase 3 trial by Kumar et al (2011) examined the utility of the GEP70 risk stratification test among patients undergoing initial therapy with lenalidomide.^23, Patients with previously untreated multiple myeloma who enrolled in the E4A03 trial were randomized to lenalidomide plus either standard-dose dexamethasone (40 mg on days 1 to 4, 9 to 12, and 17 to 21) or low-dose dexamethasone (40 mg/wk). After the first 4 cycles of therapy, patients could discontinue therapy to pursue hematopoietic cell transplantation (HCT) or continue on protocol until progression. Overall, 445 patients were randomized: 222 to the low-dose arm and 223 to the high-dose arm. As in the GEP70 validation study, CD138-positive plasma cells were isolated using bone marrow aspirates of consenting patients. Total messenger RNA was isolated from those cells and analyzed by high-density oligonucleotide microarrays containing probes for 50,000 transcripts and variants including 14,500 known human genes (Affymetrix U133Plus2.0 array).

The GEP70 signature was determined as described by Shaughnessy et al (2007) and compared with OS data and other variables. Overall, 7 (15.6%) of 45 patients with adequate messenger RNA samples were considered high-risk by the GEP70 test, similar to the proportion described previously.^22, Among patients who had fluorescence in situ hybridization (FISH) cytogenetic data available, 10 (22.7%) of 44 were considered high-risk by the presence of the following translocations and deletions: t(4;14), t(14;16), t(14;20), and del(17p). Six of the FISH high-risk patients and 2 of the standard-risk patients were reclassified into the low- and high-risk categories by GEP70, respectively. Median OS was 19 months for the 7 GEP70 high-risk patients; OS did not reach the median for the standard-risk group. For 10 high-risk FISH patients, the median OS was 39 months; OS did not reach the median for the standard-risk group. The predictive ability of the GEP70 test, which was estimated using the C-statistic for the GEP70 score dichotomously, was 0.74 (95% confidence interval [CI], 0.61 to 0.88), a value conventionally considered to reflect a prediction model with good discriminatory ability. The C-statistic for FISH-based risk stratification was 0.70 (95% CI, 0.55 to 0.84), very similar to the GEP70 finding. These results would suggest the GEP70 high-risk results are inversely associated with OS among patients treated outside the context of HCT, in a cohort of patients treated primarily with novel agents. The small number of patients and the retrospective nature of the association between GEP70 scores and survival rates precluded conclusions on the clinical utility of the test in risk stratification and therapeutic decisions, as well as an assessment of the incremental value of GEP70 compared with FISH.

Cohort Studies

Mohan et al (2019) analyzed the predictive ability of the combination of chromosome 1q21 gain/amplification and GEP70 status on outcomes in 81 patients with relapsed/refractory multiple myeloma who were treated with daratumumab.^24, Gain or amplification of chromosome 1q21 has shown negative effects on progression-free survival (PFS) and OS in newly diagnosed and relapsed/refractory multiple myeloma. The authors analyzed predictive ability when GEP70 status was determined both at time of diagnosis and upon daratumumab treatment, given previous observations that GEP70 scores increase from presentation to relapse. At time of diagnosis, median PFS was significantly shorter in patients with versus without gain (1q21) (0.5 vs. 2.1 years; p=.004), as was median OS (0.9 years vs. not reached; p=.002). Median PFS was not significantly different based on GEP70 risk status, but median OS was significantly shorter in patients with high-risk GEP70 status (0.9 vs. 2.1 years; p=.01). When determined at time of daratumumab treatment, median PFS was shorter in patients with high-risk GEP70 status (0.5 years vs. not reached; p not reported), and median OS was significantly shorter in patients with high-risk GEP70 status (0.9 years vs. not reached; p<.001).

Papanikolaou et al (2015) analyzed predictive factors for survival in patients with multiple myeloma.^25, Clinical and demographic factors were combined with cytoplasmic immunoglobulin and the GEP70 model. Of the patients included, 94% of patients were White. Cytoplasmic immunoglobulin is a new prognostic factor being tested in conjunction with other known predictors of survival. The outcome variables used were OS and PFS. Both cytoplasmic immunoglobulin and GEP70 score were independent predictors of survival. The multivariate predictive model derived included the GEP70 score, the cytoplasmic immunoglobulin index, and the albumin level.

In a widely cited validation paper by Shaughnessy et al (2007), GEP data were reported for 523 newly diagnosed patients (training group n=351, validation group n=181) who underwent similar treatments for multiple myeloma in National Institutes of Health-sponsored clinical trials (UARK 98-026 and UARK 03-033, respectively).^22, Both protocols used induction regimens followed by melphalan-based tandem autologous HCT, consolidation chemotherapy, and maintenance treatment. Plasma cells were purified from bone marrow aspirates using a fully automated ROBOSEP cell separation system that uses immunomagnetic technology to positively select for CD138-positive cells from which messenger RNA was isolated. These preparations were hybridized to total human genome DNA using Affymetrix U133Plus2.0 microarrays. They were then processed to identify 19 underexpressed and 51 overexpressed prognostic genes (GEP70 test) that mapped primarily to chromosome 1 and were linked to short survival among the multiple myeloma patients. A high-risk GEP score, defined by the mean expression levels of up-regulated to down-regulated genes, was observed in 13% of patients who had significantly shorter durations of OS at 5 years (28%) than those with a low-risk score (78%; p<.001; hazard ratio, 5.16). The absence of a high-risk score identified a favorable subset of patients with a 5-year continuous complete remission of 60%, as opposed to a 3-year rate of only 20% in those with a high-risk GEP70 score. Multivariate analyses suggested significant correlations between OS and event-free survival, the presence of a high-risk GEP70 score, and laboratory parameters associated with a poor prognosis, including lactate dehydrogenase, albumin, and β₂-microglobulin as used in the International Staging System (see Background section). This evidence would suggest a potential connection between a GEP70 test result indicative of high-risk multiple myeloma. Moreover, the evidence would suggest that survival is higher when patients are treated on the same intensity protocol. However, this validation study was performed retrospectively on multiple myeloma plasma cells obtained prior to therapy. Further, the study was associated with the clinical outcomes from a small number of patients treated at a single-center in the U.S., primarily in the context of autologous HCT.

Clinically Useful

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

In the 2022 literature search update of this evidence review, BCBSA did not identify any systematic reviews or meta-analyses that addressed clinical data on GEP70 for risk analysis of multiple myeloma. Several review articles on risk stratification of multiple myeloma reported on the use of GEP70; however, reviewers uniformly stated this technology has not yet been proven to have clinical utility for this purpose.^26,27,28,29,

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.

Because the clinical validity of this test for multiple myeloma has not been established, a chain of evidence cannot be constructed to support the test’s clinical utility.

For individuals who have multiple myeloma who received risk stratification using a gene expression profile (GEP) test, the evidence includes retrospective series that correlate risk scores with survival. Relevant outcomes are progression-free survival, overall survival, disease-specific survival, test validity, and other test performance measures. The microarray-based GEP70 test (MyPRS/MyPRS Plus) has been reported to risk-stratify multiple myeloma patients. Some predictive models in the body of evidence combine risk status as determined by the GEP70 test with additional clinical or genetic variables. Patients with a high GEP70 risk score have a substantially increased risk of mortality compared with patients without a high score. However, there is no evidence (from available studies) that this test would add incremental value to existing risk stratification methods; nor have any studies demonstrated the need to prospectively allocate patients to risk-based therapies based on the GEP70 score. The evidence is insufficient to determine that the technology results in an improvement in the net health outcome.

Supplemental Information

The purpose of the following information is to provide reference material. Inclusion does not imply endorsement or alignment with the evidence review conclusions.

Practice Guidelines and Position Statements

Guidelines or position statements will be considered for inclusion in ‘Supplemental Information' if they were issued by, or jointly by, a US professional society, an international society with US representation, or National Institute for Health and Care Excellence (NICE). Priority will be given to guidelines that are informed by a systematic review, include strength of evidence ratings, and include a description of management of conflict of interest.

Mayo Clinic Stratification of Multiple Myeloma and Risk-Adapted Therapy

Guidelines from the Mayo Clinic (2017) have stated that “if indicated, gene expression profiling may be performed to further understand the behavior of the disease and guide therapy.”^30,

National Comprehensive Cancer Network

The National Comprehensive Cancer Network practice guidelines (v4.2024) on multiple myeloma do not provide evidence-based recommendations regarding use of gene expression profiling.^31,

U.S. Preventive Services Task Force Recommendations

Not applicable.

Medicare National Coverage

There is no national coverage determination. In the absence of a national coverage determination, coverage decisions are left to the discretion of local Medicare carriers.

Ongoing and Unpublished Clinical Trials

Some currently ongoing and unpublished trials that might influence this review are listed in Table 2.

Table 2. Summary of Key Trials

References

1. Fonseca R, Barlogie B, Bataille R, et al. Genetics and cytogenetics of multiple myeloma: a workshop report. Cancer Res. Feb 15 2004; 64(4): 1546-58. PMID 14989251
2. Palumbo A, Anderson K. Multiple myeloma. N Engl J Med. Mar 17 2011; 364(11): 1046-60. PMID 21410373
3. American Cancer Society. Key Statistics About Multiple Myeloma. 2024; https://www.cancer.org/cancer/types/multiple-myeloma/about/key-statistics.html. Accessed August 27, 2024.
4. Brenner H, Gondos A, Pulte D. Recent major improvement in long-term survival of younger patients with multiple myeloma. Blood. Mar 01 2008; 111(5): 2521-6. PMID 17901246
5. Marinac CR, Ghobrial IM, Birmann BM, et al. Dissecting racial disparities in multiple myeloma. Blood Cancer J. Feb 17 2020; 10(2): 19. PMID 32066732
6. Munshi NC, Anderson KC, Bergsagel PL, et al. Consensus recommendations for risk stratification in multiple myeloma: report of the International Myeloma Workshop Consensus Panel 2. Blood. May 05 2011; 117(18): 4696-700. PMID 21292777
7. Kyle RA, Rajkumar SV. Criteria for diagnosis, staging, risk stratification and response assessment of multiple myeloma. Leukemia. Jan 2009; 23(1): 3-9. PMID 18971951
8. Bladé J, Dimopoulos M, Rosiñol L, et al. Smoldering (asymptomatic) multiple myeloma: current diagnostic criteria, new predictors of outcome, and follow-up recommendations. J Clin Oncol. Feb 01 2010; 28(4): 690-7. PMID 20026810
9. Morgan GJ, Walker BA, Davies FE. The genetic architecture of multiple myeloma. Nat Rev Cancer. Apr 12 2012; 12(5): 335-48. PMID 22495321
10. Kyle RA, Durie BG, Rajkumar SV, et al. Monoclonal gammopathy of undetermined significance (MGUS) and smoldering (asymptomatic) multiple myeloma: IMWG consensus perspectives risk factors for progression and guidelines for monitoring and management. Leukemia. Jun 2010; 24(6): 1121-7. PMID 20410922
11. Fonseca R, Bergsagel PL, Drach J, et al. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia. Dec 2009; 23(12): 2210-21. PMID 19798094
12. Munshi NC, Avet-Loiseau H. Genomics in multiple myeloma. Clin Cancer Res. Mar 15 2011; 17(6): 1234-42. PMID 21411439
13. Mikhael JR, Dingli D, Roy V, et al. Management of newly diagnosed symptomatic multiple myeloma: updated Mayo Stratification of Myeloma and Risk-Adapted Therapy (mSMART) consensus guidelines 2013. Mayo Clin Proc. Apr 2013; 88(4): 360-76. PMID 23541011
14. Johnson SK, Heuck CJ, Albino AP, et al. The use of molecular-based risk stratification and pharmacogenomics for outcome prediction and personalized therapeutic management of multiple myeloma. Int J Hematol. Oct 2011; 94(4): 321-333. PMID 22002477
15. Zhou Y, Barlogie B, Shaughnessy JD. The molecular characterization and clinical management of multiple myeloma in the post-genome era. Leukemia. Nov 2009; 23(11): 1941-56. PMID 19657360
16. Shaughnessy J. Primer on medical genomics. Part IX: scientific and clinical applications of DNA microarrays--multiple myeloma as a disease model. Mayo Clin Proc. Sep 2003; 78(9): 1098-109. PMID 12962165
17. Hubank M. Gene expression profiling and its application in studies of haematological malignancy. Br J Haematol. Mar 2004; 124(5): 577-94. PMID 14871244
18. Zhou Y, Zhang Q, Stephens O, et al. Prediction of cytogenetic abnormalities with gene expression profiles. Blood. May 24 2012; 119(21): e148-50. PMID 22496154
19. Matsui S, Simon R, Qu P, et al. Developing and validating continuous genomic signatures in randomized clinical trials for predictive medicine. Clin Cancer Res. Nov 01 2012; 18(21): 6065-73. PMID 22927484
20. Meissner T, Seckinger A, Rème T, et al. Gene expression profiling in multiple myeloma--reporting of entities, risk, and targets in clinical routine. Clin Cancer Res. Dec 01 2011; 17(23): 7240-7. PMID 21986844
21. Cowan AJ, Green DJ, Kwok M, et al. Diagnosis and Management of Multiple Myeloma: A Review. JAMA. Feb 01 2022; 327(5): 464-477. PMID 35103762
22. Shaughnessy JD, Zhan F, Burington BE, et al. A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1. Blood. Mar 15 2007; 109(6): 2276-84. PMID 17105813
23. Kumar SK, Uno H, Jacobus SJ, et al. Impact of gene expression profiling-based risk stratification in patients with myeloma receiving initial therapy with lenalidomide and dexamethasone. Blood. Oct 20 2011; 118(16): 4359-62. PMID 21860025
24. Mohan M, Weinhold N, Schinke C, et al. Daratumumab in high-risk relapsed/refractory multiple myeloma patients: adverse effect of chromosome 1q21 gain/amplification and GEP70 status on outcome. Br J Haematol. Apr 2020; 189(1): 67-71. PMID 31820442
25. Papanikolaou X, Alapat D, Rosenthal A, et al. The flow cytometry-defined light chain cytoplasmic immunoglobulin index and an associated 12-gene expression signature are independent prognostic factors in multiple myeloma. Leukemia. Aug 2015; 29(8): 1713-20. PMID 25753926
26. Agnelli L, Tassone P, Neri A. Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing. Expert Opin Biol Ther. Jun 2013; 13 Suppl 1: S55-68. PMID 23614397
27. Amin SB, Yip WK, Minvielle S, et al. Gene expression profile alone is inadequate in predicting complete response in multiple myeloma. Leukemia. Nov 2014; 28(11): 2229-34. PMID 24732597
28. Chng WJ, Dispenzieri A, Chim CS, et al. IMWG consensus on risk stratification in multiple myeloma. Leukemia. Feb 2014; 28(2): 269-77. PMID 23974982
29. Fonseca R, Monge J, Dimopoulos MA. Staging and prognostication of multiple myeloma. Expert Rev Hematol. Feb 2014; 7(1): 21-31. PMID 24483346
30. Dingli D, Ailawadhi S, Bergsagel PL, et al. Therapy for Relapsed Multiple Myeloma: Guidelines From the Mayo Stratification for Myeloma and Risk-Adapted Therapy. Mayo Clin Proc. Apr 2017; 92(4): 578-598. PMID 28291589
31. National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology: Multiple Myeloma. Version 4.2024. http://www.nccn.org/professionals/physician_gls/pdf/myeloma.pdf. Accessed August 27, 2024.

CODES

Policy History