Medical Policy


Subject: Gene Expression Profile Tests for Multiple Myeloma
Document #: GENE.00020 Publish Date:    12/12/2018
Status: Reviewed Last Review Date:    11/08/2018
 
Description Scope

This document addresses the proposed use of gene expression profile (GEP) tests to analyze an individual’s genomic information to assist in the risk stratification and clinical management of multiple myeloma.

Position Statement

Investigational and Not Medically Necessary:

Gene expression profile tests are considered investigational and not medically necessary for evaluation or management of multiple myeloma, including but not limited to:

  1. Use as a risk stratification tool to predict outcomes in individuals with newly diagnosed multiple myeloma; or
  2. Assist in determining the prognosis for survival in individuals with relapsed multiple myeloma.
Rationale

Microarray-based gene expression analysis has been explored as a method to evaluate and manage individuals with multiple myeloma. The My Prognostic Risk Signature® (MyPRS®/MyPRS Plus®, Miragen Therapeutics, Boulder, CO [formerly Signal Genetics™ LLC]) GEP test is proposed as a method to risk stratify individuals with newly diagnosed and relapsed multiple myeloma. Clinical trials have shown that a high risk signature is present in approximately 15% of new cases of multiple myeloma (Shaughnessy, 2007b). A high risk signature at the time of diagnosis was associated with shorter durations of complete remission, event-free survival, and overall survival. Another study suggests that the MyPRS may be an independent and prognostic factor for survival in an analysis of individuals with relapsed multiple myeloma (Nair, 2009). However, as yet, treatment decisions based on these risk scores in addition to standard approaches, when compared to standard approaches alone, have not been demonstrated to improve clinical outcomes.

Kyle and Rajkumar (2008) reviewed the available laboratory tests and imaging modalities for the diagnosis, prognosis and risk stratification of multiple myeloma. Their recommendations for laboratory testing include a complete blood count, peripheral blood smear, chemistry screen including calcium and creatinine determinations, β2-microglobulin (β2M), lactate dehydrogenase and routine urinalysis (essential). In addition, serum protein electrophoresis, immunofixation, nephelometric quantitation of immunoglobulins and measurement of free light chains (FLCs) are needed. A bone marrow aspiration and biopsy with immunophenotyping, conventional cytogenetics (karyotyping), and fluorescence in situ hybridization (FISH) are required in all individuals for diagnosis and risk stratification. The presence of specific markers obtained from conventional cytogenetics and FISH testing is used to assess risk in newly diagnosed individuals and stratify tumors into high and standard risk disease. Such stratification may help guide therapy. High risk myeloma encompasses the 25% of individuals with multiple myeloma who have a median survival of approximately 2 years or less despite standard treatment. Individuals without any high risk markers are treated as standard risk myeloma. If available, bone marrow plasma cell labeling index may be of additional value. A radiological skeletal bone survey, including spine, pelvis, skull, humeri and femurs is necessary. A magnetic resonance imaging (MRI) or computerized tomography (CT) scan may be needed to evaluate symptomatic bony sites, even if the skeletal survey is negative. In addition, either is essential if spinal cord compression is suspected.

For risk stratification, Kyle and Rajkumar (2008) suggest that:

Gene expression profiling has been utilized to aid in the differentiation between normal plasma cells and those in monoclonal gammopathy of undetermined significance (MGUS), multiple myeloma, amyloid-light chain amyloidosis, and extramedullary plasmacytomas. It has also been used to identify high risk patients with multiple myeloma, and to further classify risk in poor prognosis multiple myeloma patients such as those with t(4;14). The Durie–Salmon Staging System and the International Staging System (ISS) are important for prognosis, but are not useful for therapeutic risk stratification. Independent prognostic markers provide a better estimate of differences in underlying myeloma biology. Either FISH or conventional cytogenetics, or preferably both, should be done at diagnosis in all individuals. However, modifying therapy based on underlying risk factors remains controversial and needs further study. Gene expression profiling is also useful in risk stratification, but is limited by the lack of a uniform platform across many centers in the world and widespread availability.

Kumar and colleagues (2011) reported on the first study examining the utility of two GEP-based risk stratification systems in a cohort of individuals undergoing initial therapy in the context of a phase III trial of lenalidomide in the treatment of multiple myeloma. Among 45 individuals studied at baseline, 7 (16%) and 10 (22%) were high-risk using the GEP70 and GEP15 signatures, respectively. The median overall survival (OS) for the GEP70 high-risk group was 19 months versus not reached for the standard-risk group (hazard ratio [HR] = 14.1). While the medians were not reached, the GEP15 also predicted a poor outcome among the high-risk individuals. The estimated C-statistic (the test used to assess the predictive ability of the gene score) for GEP70 score was 0.74 (95% confidence interval [CI], 0.61, 0.88), a value conventionally considered as reflecting a prediction model with good discriminatory ability. In comparison, the C-statistic for FISH based risk stratification was 0.70 (95% CI, 0.55, 0.84). The median OS for the 10 participants considered to be high-risk by FISH was 39 months and did not reach median for the standard risk group (HR 5.8; 95% CI, 1.62, 20.5; p=0.007). The median time to progression (TTP) for the participants with GEP70 high-risk was 9 months compared to the standard-risk group (23 months; p=0.3). In comparison the median TTP for the FISH high-risk group was 16 months versus the standard-risk group (23 months; p=0.4). The authors concluded these results strengthen the rationale for a GEP based risk stratification approach. The objective of the study was not to determine whether one system was better than the other, due to the limited number of study participants; however, the results are:

...valuable confirmation supporting the use of GEP based risk stratification approaches and its routine incorporation into clinical trials designed to test different treatment strategies for high-risk and standard-risk myeloma…The results presented here confirms the value of the GEP scoring and highlights its value in the setting of initial therapy with lenalidomide and dexamethasone, one of the most commonly used treatments for myeloma, as well as its value in older patients. The small number of patients in this study, however, prevents a comparison of the GEP and FISH-based risk stratification, and an assessment of the incremental value of GEP over FISH-based risk stratification (Kumar, 2011).

While the information provided in this small population-based study is encouraging, additional studies with larger populations are required to confirm the potential of the GEP70 (MyPRS) to improve health outcomes for individuals with multiple myeloma.

Mikhael and colleagues (2013) proposed a risk-adapted approach to the management of individuals with newly diagnosed symptomatic multiple myeloma. The Mayo Stratification of Myeloma and Risk-Adapted Therapy (mSMART) is an evidence-based algorithm using conventional cytogenetic methods (karyotyping) and FISH to prognostically stratify individuals with multiple myeloma according to multiple recurrent chromosomal changes. In addition to cytogenetic methods, a large number of prognostic factors have been validated and categorized into three main groups: tumor biology, tumor burden, and patient-related factors. The guideline suggests these factors must be considered to individualize the choice of therapy for persons with multiple myeloma. Although GEP analysis is included in the algorithms for prognostic factors and risk stratification, the consensus guideline does not currently recommend performing GEP analysis in a non-research setting. The investigators suggest that GEP analysis will likely play a greater role in the management of multiple myeloma as evidence develops.

Amin and colleagues (2014) retrospectively analyzed the ability of GEP to predict complete response (CR) to therapy in individuals with multiple myeloma. Data sets from four studies (n=647) were evaluated to determine the variability in predictive power of GEPs due to the microarray platform or treatment types. Among all methods employed for GEP-based CR predictive capability, the investigators reported an accuracy rate of 56% to 78% in test data sets and no significant difference with regard to GEP platforms, treatment regimens or in newly diagnosed or relapsed individuals. The authors concluded the ability to predict CR in individuals with multiple myeloma is “very limited.”

The National Comprehensive Cancer Network® (NCCN®) Clinical Practice Guidelines in Oncology® for multiple myeloma (V1.2019) state:

In addition to cytogenetic markers of prognosis, gene expression signatures may be capable of discerning prognosis and helping rational therapeutic decisions. Further understanding of the molecular subtypes of MM is emerging from the application of high-throughput genomic tools such as gene expression profiling (GEP)… GEP is a powerful and fast tool with the potential to provide additional prognostic information to further refine risk-stratification, help therapeutic decisions, and inform novel drug design and development...The NCCN Panel unanimously agreed that although GEP is not currently routinely used in clinical practice during diagnostic workup, GEP is a useful tool and may be helpful in selected patients to estimate the aggressiveness of the disease and individualize treatment.

The NCCN guideline does not provide specific patient selection criteria for GEP testing for individuals with multiple myeloma.

At this time, there is limited evidence in the peer-reviewed medical literature in the form of prospective studies that analyze the clinical validity of the MyPRS test in the management of individuals with newly diagnosed or relapsed multiple myeloma. The ability of such GEP testing to improve or potentially improve health outcomes by providing direction in determining or changing therapy based on the results of such testing in individuals with multiple myeloma requires further study.

Background/Overview

Multiple myeloma is a systemic malignancy of plasma cells that accumulate in the bone marrow, leading to destruction of bone and failure of the bone marrow. The American Cancer Society (ACS, 2018) has estimated 30, 770 new cases of multiple myeloma in the United States in 2018, with an estimated 12,770 deaths. The disease is staged by estimating the myeloma tumor cell mass on the basis of the amount of monoclonal (or myeloma) protein (M-protein) in the serum and/or urine along with various clinical parameters, such as the hemoglobin and serum calcium concentrations, the number of lytic bone lesions, and the presence or absence of renal failure. The stage of the disease at presentation is a strong predictor of survival, but has little influence on the choice of therapy since almost all individuals (except for those with solitary bone tumors or extramedullary plasmacytomas) have generalized disease. The age and general health of the individual, prior therapy and the presence of complications of the disease influence treatment selection. The median survival in the prechemotherapy era was about 7 months. Multiple myeloma has demonstrated chemosensitivity to initial treatment or treatment for relapsed disease. Standard treatment options include the use of alkylating agents such as melphalan, cyclophosphamide and corticosteroids. After the introduction of chemotherapy, prognosis improved significantly with a median survival of 24 to 30 months and a 10-year survival of 3%. Further improvements in the prognosis of individuals with multiple myeloma have occurred in recent years, with median survivals now exceeding 45 to 60 months, with the introduction of newer drugs such as pulse corticosteroids, bortezomib, thalidomide and lenalidomide in combination with doxorubicin, followed by autologous and allogeneic hematopoietic stem cell transplantation (ACS, 2018; Kumar, 2008; Ludwig, 2008; NCCN, 2018; NCI, 2018). Genetic variations among myeloma cells appear to underlie much of the heterogeneity in clinical outcomes (Badros, 2010; Rajkumar, 2007). Clinical response is transitory in all cases despite achievement of complete remission and apparent eradication of disease, and multiple myeloma is considered incurable with current approaches.

The MyPRS test analyzes genes in a person’s genome to determine the GEP associated with multiple myeloma. By looking at the entire genome of the person, it is proposed that the MyPRS test provides a predictive view of the individual’s long-term clinical outcome/prognosis, giving a basis for personalized treatment options. In the case of multiple myeloma, the GEP is made up of the 70 most relevant genes (GEP70) which aid in identifying a high risk gene signature at the time of diagnosis that are associated with shorter durations of complete remission, event-free survival, and overall survival. The test is intended to supplement the diagnostic aspects of multiple myeloma in a more complete method by assisting in the prediction of the individual’s disease outcome. In order to perform the test, plasma cells are retrieved by a bone marrow aspirate used in determining the diagnosis of multiple myeloma. These plasma cells from the bone marrow sample are enriched in order to provide the clearest assessment of these cells. Genetic material is then extracted from these plasma cells and analyzed. The results from this analysis are then compared to proprietary databases that have been developed and validated over the course of 10 years of study involving thousands of plasma cell samples. This analysis results in a MyPRS risk score that reflects the probability of early recurrence of the myeloma (high risk) or a maintenance of remission (low risk). In July 2013, Signal Genetics, LLC updated the MyPRS test to include an analysis of an additional set of 813 genes within the person’s genome, used to create an individualized “Virtual Karyotype” view of their disease. This new algorithm is offered in conjunction with the GEP70 risk stratification signature and 7-class molecular subtyping algorithm and is used to predict cytogenetic abnormalities in individuals with multiple myeloma using GEP. The accuracy of the method against a range of conventional cytogenetic techniques was validated in a proof of concept study, with the model showing an accuracy rate of up to 89% (Zhou, 2012).

The MyPRS test, like many genetic tests, has not been cleared or approved by the U.S. Food and Drug Administration (FDA). The laboratory performing this test is accredited by the Centers for Medicare and Medicaid (CMS) under the Clinical Laboratory Improvement Amendments of 1988 (CLIA).

Definitions

Gene expression profile/profiling (GEP): The individual pattern of expression of a panel of genes that is regarded as a “signature” for that tissue; a major determinant of the biology of both normal and malignant cells.

Microarray-based gene expression profile: The ability to measure and analyze thousands of genes simultaneously in a single RNA sample; also referred to as gene expression microarray (GEM).

Coding

The following codes for treatments and procedures applicable to this document are included below for informational purposes. Inclusion or exclusion of a procedure, diagnosis or device code(s) does not constitute or imply member coverage or provider reimbursement policy. Please refer to the member's contract benefits in effect at the time of service to determine coverage or non-coverage of these services as it applies to an individual member.

When services are Investigational and Not Medically Necessary:
When the code describes a procedure indicated in the Position Statement section as investigational and not medically necessary.

CPT

 

81479

Unlisted molecular pathology procedure [when specified as My Prognostic Risk Signature (MyPRS/MyPRS Plus) micro-array test]

81599

Unlisted multianalyte assay with algorithmic analysis [when specified as My Prognostic Risk Signature (MyPRS/MyPRS Plus) micro-array test]

 

 

ICD-10 Diagnosis

 

C90.00-C90.32

Multiple myeloma and malignant plasma cell neoplasms

References

Peer Reviewed Publications:

  1. Amin SB, Yip WK, Minvielle S, et al. Gene expression profile alone is inadequate in predicting complete response in multiple myeloma. Leukemia. 2014; 28(11):2229-2234.
  2. Anguiano A, Tuchman SA, Acharya C, et al. Gene expression profiles of tumor biology provide a novel approach to prognosis and may guide the selection of therapeutic targets in multiple myeloma. J Clin Oncol. 2009; 27(25):4197-4203.
  3. Badros AZ. In the age of novel therapies, what defines high-risk multiple myeloma? J Natl Compr Canc Netw. 2010; 8(Suppl 1):S28-S34.
  4. Broyl A, Hose D, Lokhorst H, et al. Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients. Blood. 2010; 116(14):2543-2553.
  5. Dickens NJ, Walker BA, Leone PE, et al. Homozygous deletion mapping in myeloma samples identifies genes and an expression signature relevant to pathogenesis and outcome. Clin Cancer Res. 2010; 16(6):1856-1864.
  6. Girnius S, Seldin DC, Skinner M, et al. Short and long-term outcome of treatment with high-dose melphalan and stem cell transplantation for multiple myeloma-associated AL amyloidosis. Ann Hematol. 2010; 89(6):579-584.
  7. Kumar SK, Rajkumar SV, Dispenzieri A, et al. Improved survival in multiple myeloma and the impact of novel therapies. Blood. 2008; 111(5):2516-2520.
  8. 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. 2011; 118(16):4359-4362.
  9. Kyle RA, Rajkumar SV. Criteria for diagnosis, staging, risk stratification and response assessment of multiple myeloma. Leukemia. 2009; 23(1):3-9.
  10. Nair B, Shaughnessy JD Jr, Zhou Y, et al. Gene expression profiling of plasma cells at myeloma relapse from tandem transplantation trial Total Therapy 2 predicts subsequent survival. Blood. 2009; 113(26):6572-6575.
  11. Shaughnessy JD Jr, Haessler J, van Rhee F, et al. Testing standard and genetic parameters in 220 patients with multiple myeloma with complete data sets: superiority of molecular genetics. Br J Haematol. 2007a; 137(6):530-536.
  12. Shaughnessy JD Jr, 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. 2007b; 109(6):2276-2284.
  13. Shi L, Campbell G, Jones WD, et al. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models. Nat Biotechnol. 2010; 28(8):827-838.
  14. Stewart AK, Bergsagel PL, Greipp PR, et al. A practical guide to defining high-risk myeloma for clinical trials, patient counseling and choice of therapy. Leukemia. 2007; 21(3):529-534.
  15. Zhan F, Huang Y, Colla S, et al. The molecular classification of multiple myeloma. Blood. 2006; 108(6):2020-2028.
  16. Zhou Y, Zhang Q, Stephens O, et al. Prediction of cytogenetic abnormalities with gene expression profiles. Blood. 2012; 119(21):e148-e150.

Government Agency, Medical Society, and Other Authoritative Publications:

  1. Decaux O, Lode L, Magrangeas F, et al. Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myélome. J Clin Oncol. 2008; 26(29):4798-4805.
  2. Fonseca R, Bergsagel PL, Drach J, et al. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia. 2009; 23(12):2210-2221.
  3. 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. 2013; 360-376.
  4. NCCN Clinical Practice Guidelines in Oncology®. ©2018 National Comprehensive Cancer Network, Inc. Multiple myeloma (V1.2019). Revised July 20, 2018. For additional information visit the NCCN website: http://www.nccn.org/index.asp. Accessed on October 9, 2018.
Websites for Additional Information
  1. American Cancer Society (ACS). Cancer facts and figures 2018. Myeloma. Available at: https://www.cancer.org/cancer/multiple-myeloma/about/key-statistics.html. Accessed on October 9, 2018.
  2. National Cancer Institute (NCI). Plasma cell neoplasm (including multiple myeloma) treatment (PDQ®). Last updated March 16, 2018. Available at: https://www.cancer.gov/types/myeloma/hp/myeloma-treatment-pdq. Accessed on October 9, 2018.
Index

My Prognostic Risk Signature
MyPRS Plus
MyPRS Test

The use of specific product names is illustrative only. It is not intended to be a recommendation of one product over another, and is not intended to represent a complete listing of all products available.

Document History

Status

Date

Action

Reviewed

11/08/2018

Medical Policy & Technology Assessment Committee (MPTAC) review.

Reviewed

10/31/2018

Hematology/Oncology Subcommittee review. Updated Rationale, Background and References sections.

Reviewed

11/02/2017

MPTAC review.

Reviewed

11/01/2017

Hematology/Oncology Subcommittee review. The document header wording updated from “Current Effective Date” to “Publish Date.” Updated Description, Rationale, Background, References, and Websites for Additional Information sections.

Reviewed

11/03/2016

MPTAC review.

Reviewed

11/02/2016

Hematology/Oncology Subcommittee review. Updated formatting in Position Statement section. Updated Description, Rationale, Background, References, and Websites for Additional Information.

Reviewed

11/05/2015

MPTAC review.

Reviewed

11/04/2015

Hematology/Oncology Subcommittee review. Updated Rationale, Background, and Websites for Additional Information sections. Removed ICD-9 codes from Coding section.

Reviewed

11/13/2014

MPTAC review.

Reviewed

11/12/2014

Hematology/Oncology Subcommittee review. Updated Description, Rationale, Background, References, and Websites for Additional Information sections. Other format changes throughout document.

Revised

11/14/2013

MPTAC review.

Revised

11/13/2013

Hematology/Oncology Subcommittee review. Revised Subject (title). Updated Description and clarified the investigational and not medically necessary statement with no change to the criteria. Updated Rationale, Background, References, and Websites for Additional Information, and Index sections. Updated Coding section to remove CPT 81406 which is not applicable.

Reviewed

11/08/2012

MPTAC review.

Reviewed

11/07/2012

Hematology/Oncology Subcommittee review. Revised Description, Rationale and Index. Updated Background, References, and Websites for Additional Information. Updated Coding section with 01/01/2013 CPT changes; removed codes 88384, 88385, 88386 deleted 12/31/2012.

Reviewed

11/17/2011

MPTAC review.

Reviewed

11/16/2011

Hematology/Oncology Subcommittee review. Updated Description, Rationale, Background, and References. Updated Coding section with 01/01/2012 CPT changes.

New

05/19/2011

MPTAC review.

New

05/18/2011

Hematology/Oncology Subcommittee review. Initial document development.