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Medical Policy

Policy Num:       11.001.016
Policy Name:    
Serum Biomarker Tests for Multiple Sclerosis
Policy ID:          [11.001.016][Ac B M P ][2.04.118]


Last Review:      June 8, 2020
Next Review:     N/A
Issue:                   6:2020

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Serum Biomarker Tests for Multiple Sclerosis

Popultation Reference No. Populations Interventions Comparators Outcomes
1 Individuals:
  • Individuals: With signs and/or symptoms of multiple sclerosis
Interventions of interest are:
  •  Serum biomarker tests for multiple scleros
Comparators of interest are:
  • Standard clinical workup without serum biomarkers

Relevant outcomes include:

  • Test accuracy
  •  Test validity
  •  Other test performance measures
  •  Symptoms
  •  Functional outcomes
  •  Health status measures
  •  Quality of life

Summary

Serum antibodies to polysaccharide-containing molecules, called glycans, and other serum biomarkers are potential biomarker tests for the diagnosis and prognosis of multiple sclerosis (MS). MS is diagnosed according to criteria that incorporate clinical symptoms and magnetic resonance imaging and cerebrospinal fluid findings. Currently, there is no biomarker available to inform diagnosis or prognosis. A serum biomarker is particularly desirable because of ease of repeat measurements. For individuals who have signs and/or symptoms of MS who receive serum biomarker tests for MS, the evidence includes cross-sectional studies of diagnostic accuracy and cohort studies. Relevant outcomes are test accuracy and validity, other test performance measures, symptoms, functional outcomes, health status measures, and quality of life. Antibodies to glycan molecules are thought to impair immune function. They include antibodies to 1 (glucose[α1,4]glucose[α] [GAGA4]) or several (GAGA2, -3, -4, and - 6) glycan molecules. The gMS Dx and gMS Pro EDSS tests may aid in the diagnosis and prognosis in MS, respectively. Tests for serum levels of other potential MS biomarkers, including but not limited to apoptosis-related molecules, intercellular adhesion molecules, and myelin peptides, have also been described. Current evidence for these other biomarkers makes it difficult to assess their utility in diagnosis and prognosis. The evidence is insufficient to determine the effects of the technology on health outcomes.

Objective

Policy Statements

Serum biomarker tests for multiple sclerosis are considered investigational in all situations.

Policy Guidelines

There are no specific CPT codes for these tests. They would likely be reported with the unlisted chemistry procedure code 84999.

Benefit Application

BlueCard/National Account Issues

BlueCard/National Account Issues Some plans may have contract or benefit exclusions for genetic testing.

Background

Disease Description Estimated prevalence of multiple sclerosis (MS) in North America varies regionally and ranges from 240 of 100,000 in Canada to 191 of 100,000 in Minnesota and 40 of 100,000 in Texas.1 Women are affected twice as often as men, and median age of onset is 24 years. Most (85%) patients have relapsing-remitting MS (RRMS), and of these, 60% to 70% will progress to secondary progressive MS, usually 10 to 30 years after disease onset.2 Rarer forms are primary progressive MS and progressive relapsing MS.

MS is characterized by destruction of myelin in the central nervous system. Progressive focal demyelination eventually leads to axonal degeneration and cumulative physical and cognitive disabilities. Because any area of the brain, optic nerve, or spinal cord can be affected, symptoms are diverse and may include cognitive, speech, or vision deficits; numbness; pain; weakness or dyscoordination; and bowel or bladder dysfunction. Diagnosis is made by clinical symptoms, typical magnetic resonance imaging findings, and oligoclonal antibodies in the cerebrospinal fluid assessed using current McDonald criteria.3 Diagnosis requires 2 clinical episodes occurring at 2 discreet points in time, or 1 clinical episode (clinically isolated syndrome; defined next) with lesions detected by magnetic resonance imaging indicating development at 2 discreet points in time (ie, simultaneous appearance of old and new lesions). Disability progression is quantified in practice and in clinical trials using the Kurtzke Expanded Disability Status Scale.4 Patients with scores less than 5 are fully ambulatory; scores of 5 to 10 are defined by incrementally decreasing ability to walk.

The term clinically isolated syndrome (CIS) describes patients who have suffered a first episode suggestive of MS but do not meet diagnostic criteria for definite MS. Studies have indicated that early treatment with interferon beta-1b (IFN-β1b) may delay relapse (ie, a second episode), but not long-term disability outcomes.5,6

In addition to IFN-β1b, 8 other disease-modifying drugs are currently approved by the U.S. Food and Drug Administration for first- or second-line treatment of MS, with varying degrees of efficacy for reducing relapses and preventing neurologic deterioration. First-line treatments include self-injectable drugs (interferon, glatiramer acetate) and newer oral agents (eg, fingolimod, teriflunomide, dimethyl fumarate). Choice of first-line agent depends on severity of initial presentation, patient preference, and adverse effect profile. Patients with more active or refractory disease are more likely to tolerate greater risk for greater efficacy, eg, with second- or third-line agents (eg, natalizumab, alemtuzumab). 2,

Biomarkers Glycominds, based in Israel, markets the diagnostic test gMS Dx, for patients with a first episode or CIS, and the multimarker prognostic test gMS Pro EDSS, for predicting deterioration in patients diagnosed with MS. Both tests detect serum antibodies to glycans, which are polysaccharide- or carbohydrate-containing molecules on the surface of immune and other cells. The gMS Dx test detects immunoglobulin M (IgM) antibodies to the disaccharide glycan, glucose(α1,4)glucose(α) (GAGA4), and gMS Pro EDSS detects IgM antibodies to GAGA2, -3, -4, and -6. These anti-glycan antibodies are thought to interfere with normal function of the

Several other serum biomarkers for MS have been investigated, but no other commercially available tests were identified.

Regulatory Status

Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests (LDTs) must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments (CLIA). Glycominds (Lod, Israel) offered gMS® Dx and gMS® Pro EDSS as laboratory-developed (in-house) tests at its CLIA-certified laboratory in Simi Valley, California. The current status of the tests is unknown because links to the company’s website are inactive, and ordering information is not readily available through the parent company, Coronis Partners. Laboratories that offer LDTs must be licensed by 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 April 2014 and has been updated with a literature review of the MEDLINE database through April 29, 2016.

gMS Dx Test In 2006, Schwarz et al screened sera from 107 patients in Israel diagnosed with relapsing-remitting multiple sclerosis (RRMS) for antibodies to 76 glycan molecules.9 Sera were analyzed by immunofluorescence assay using the GlycoChip® (Glycominds) glycan array. Antibody levels in patients with RRMS were compared to levels in patients with primary progressive MS (PPMS; n=16); patients with other neurologic diseases, including inflammatory (eg, Guillain-Barré syndrome, myasthenia gravis) and noninflammatory (eg, Parkinson disease, Huntington disease,) neurologic diseases (n=50); and patients with other autoimmune diseases (eg, rheumatoid arthritis, Crohn disease; n=27). No differences between groups were observed for immunoglobulin G (IgG) and IgA antibodies. IgM binding to glycans containing free glucose residues (eg, disaccharide glycan, glucose[α1,4]glucose[α] [GAGA4]) best discriminated RRMS patients from other groups; anti-GAGA4 antibody levels were significantly higher in patients with RRMS than in patients with other neurologic disease (p<0.001) and patients with other autoimmune diseases (p=0.02). No differences between patients with RRMS and PPMS was observed. Coefficients of variation for repeated anti-GAGA4 IgM measurements were approximately 8% for quadruple intraplate measurements and 22% for interplate measurements. Area under the receiver operating characteristic (ROC) curve for discriminating patients with MS (RRMS or PPMS) from patients with other neurologic diseases was 0.765 (95% confidence interval [CI], 0.673 to 0.865). Using a cutoff value for anti-GAGA4 IgM positivity (normalized for total IgM) of 2.1103 relative fluorescence units (RFU)/(μg total IgM/mL serum)0.5 , sensitivity was 57%, and specificity was 85%.

In 2009, Brettschneider et al retrospectively analyzed sera from 2 cohorts of patients: cohort 1 (n=778) comprised 648 U.S. patients with MS (77% RRMS), 30 patients in Germany who had other neurologic disease (suspected neuropsychiatric lupus), and 100 healthy controls from the United States; cohort 2 (n=126) comprised 91 U.S. patients with MS (91% RRMS) and 35 U.S. patients with other inflammatory (eg, Guillain-Barré syndrome) and noninflammatory (eg, amyotrophic lateral sclerosis) neurologic diseases.10 Anti-GAGA4 IgM levels were assessed in all patients by enzyme immunoassay and were higher in MS patients than in controls, although differences were only statistically significant in cohort 1. Area under the curve (AUC) for discriminating MS patients from patients with other neurologic diseases was 0.903 in cohort 1 and 0.812 in cohort 2. For discriminating MS patients from healthy controls (cohort 1), AUC was 0.651. Sensitivity and specificity were determined for the combined cohort of 739 patients with MS and 65 patients with other neurologic diseases using a cutoff determined by anti-GAGA4 IgM levels in the upper 15 percentile of healthy controls (50 enzyme immunoassay units [EU]/[mg total IgM/mL serum]0.5). Sensitivity was 34%; specificity was 99%; positive likelihood ratio was 21.9; and negative likelihood ratio was 0.67.

Freedman et al (2009) retrospectively assessed sera drawn at the time of presentation with a first episode suggestive of MS in 3 cohorts in Canada and Belgium.11 Cohort 1 (n=88) comprised 44 patients later diagnosed with RRMS and 44 age- and sex-matched patients who had other neurologic diseases; cohort 2 (n=252) comprised 167 patients later diagnosed with RRMS and 85 patients with other neurologic diseases; cohort 3 is discussed next. Enzyme-linked immunosorbent assay was used to measure antiGAGA4 IgM, and values were normalized to total IgM, although 2 different normalizing algorithms were used. In cohort 1, the cutoff value was determined by mean optical density (OD) plus 2 SD in the control group (0.53 OD/[total IgM RFU106 ] 0.5); in cohort 2, the cutoff value was determined by ROC analysis to achieve 90% specificity for RRMS (42 EU/[mg total IgM/mL serum]0.5). Coefficients of variation for intraand interplate measurements were 11% and 15%, respectively. In cohorts 1 and 2, respectively, sensitivity was 27% and 26%; specificity was 98% and 91%; positive predictive value (PPV) was 92% and 85%; and negative predictive value (NPV) was 52% and 39%. In cohort 1, 16 (80%) of 20 patients with antibody titers above the median had a second clinical attack within 2 years, compared with 10 (47%) of 21 patients with antibody titers at or below the median (odds ratio, 4.4; 95% CI, 1.1 to 17.7; p=0.05).

Section Summary: gMS Dx Test Three studies indicated that anti-GAGA4 IgM antibody levels may be higher in patients with RRMS compared with patients with a various other neurologic diseases and healthy controls. Although the test demonstrated high specificity (estimated range, 85%-99%), suggesting that it may be useful to confirm a diagnosis of MS, different assay methodologies were used (fluorescence immunoassay and enzyme immunoassay) and cutoffs were data-driven. Further, prospective studies demonstrating improved health outcomes in patients who may have MS (eg, presenting with a first episode [clinically isolated syndrome (CIS)]) and who are treated according to test results are lacking. The anti-GAGA4 IgM test (gMS Dx) therefore is considered in an early stage of development and investigational for all uses.

The second study (2012)12 prospectively assessed sera from patients presenting with a first episode suggestive of MS who were enrolled in an international trial (BENEFIT) assessing early versus delayed initiation of interferon beta-1b (IFN-β1b). 5 IgM antibodies to GAGA2, -3, -4, and -6 were measured by enzyme immunoassay in 286 patients (61% of enrolled patients) who had at least 2 mL of serum available. A total of 177 (62%) patients were randomized to IFN-β1b for 2 years and 109 (38%) patients were randomized to placebo; 255 (89%) of 286 patients enrolled in a follow-up phase with open-label IFN-β1b and were followed for up to 5 years. The primary outcome was the ability of the test to predict early (<24 months) relapse. Cutoffs for each antigen were calculated as mean values plus 1.4 SD, 1.8 SD, 0.8 SD, and 1.7 SD, for anti-GAGA2, -3, -4, and -6, respectively (148.8 EU, 164.6 EU, 133.6 EU, and 168.1 EU for anti-GAGA2, -3, -4, and -6, respectively). Samples were considered positive if at least 1 result exceeded the cutoff for 1 of the 4 antibodies. Sensitivity was 21%, specificity was 83%, PPV was 38%, and NPV was 68%. For secondary outcomes, the risk of confirmed disability progression, defined as a 1-point increase on the Expanded Disability Status Scale (EDSS) score confirmed over 6 months or more, was significantly greater for patients classified as positive than for patients classified as negative (hazard ratio, 2.05; 95% CI, 1.2 to 3.5; p=0.009). However, the results were not statistically significant when testing controlled for baseline EDSS score or examined only in the group who received IFN-β1b from the start of the trial. The assay panel also had no significant predictive value for conversion to MS satisfying McDonald criteria, 2005 version,13 for annualized relapse rates, or for magnetic resonance imaging (MRI) findings. The authors concluded that baseline EDSS score, presence of oligoclonal bands, and MRI findings remain the best predictors of disease progression and stated: “All current first-line, disease-modifying medications reduce the risk for subsequent attacks and lower MRI activity, and have shown benefit in patients at CIS [clinically isolated syndrome], so it is unlikely that CIS patients would not be treated with one of these agents, obviating the need for a baseline biomarker predicting early relapse.”

Investigational Serum Biomarkers Several other serum biomarkers for MS have been investigated. These have been reviewed recently elsewhere14,15 and include the factors listed in Table 1. Serum levels of several factors have been shown to change (increase or decrease) during relapses. None have been shown conclusively to alter disease

   Ongoing and Unpublished Clinical Trials A search of ClinicalTrials.gov in June 2016 did not identify any ongoing or unpublished trials that would likely influence this review

                                             Summary of Evidence

For individuals who have signs and/or symptoms of multiple sclerosis (MS) who receive serum biomarker tests for MS, the evidence includes cross-sectional studies of diagnostic accuracy and cohort studies. Relevant outcomes are test accuracy and validity, other test performance measures, symptoms, functional outcomes, health status measures, and quality of life. Antibodies to glycan molecules are thought to impair immune function. They include antibodies to 1 (glucose[α1,4]glucose[α] [GAGA4]) or several (GAGA2, -3, -4, and -6) glycan molecules. The gMS Dx and gMS Pro EDSS tests may aid in the diagnosis and prognosis in MS, respectively. Tests for serum levels of other potential MS biomarkers, including but not limited to apoptosis-related molecules, intercellular adhesion molecules, and myelin peptides, have also been described. Current evidence for these other biomarkers makes it difficult to assess their utility in diagnosis and prognosis. The evidence is insufficient to determine the effects of the technology on health outcomes.

 

Population Reference No. 1 Policy Statement

gMS Dx Test Three studies indicated that anti-GAGA4 IgM antibody levels may be higher in patients with RRMS compared with patients with a various other neurologic diseases and healthy controls. Although the test demonstrated high specificity (estimated range, 85%-99%), suggesting that it may be useful to confirm a diagnosis of MS, different assay methodologies were used (fluorescence immunoassay and enzyme immunoassay) and cutoffs were data-driven. Further, prospective studies demonstrating improved health outcomes in patients who may have MS (eg, presenting with a first episode [clinically isolated syndrome (CIS)]) and who are treated according to test results are lacking. The anti-GAGA4 IgM test (gMS Dx) therefore is considered in an early stage of development and investigational for all uses.

For individuals who have signs and/or symptoms of multiple sclerosis (MS) who receive serum biomarker tests for MS, the evidence includes cross-sectional studies of diagnostic accuracy and cohort studies. Relevant outcomes are test accuracy and validity, other test performance measures, symptoms, functional outcomes, health status measures, and quality of life. Antibodies to glycan molecules are thought to impair immune function. They include antibodies to 1 (glucose[α1,4]glucose[α] [GAGA4]) or several (GAGA2, -3, -4, and -6) glycan molecules. The gMS Dx and gMS Pro EDSS tests may aid in the diagnosis and prognosis in MS, respectively. Tests for serum levels of other potential MS biomarkers, including but not limited to apoptosis-related molecules, intercellular adhesion molecules, and myelin peptides, have also been described. Current evidence for these other biomarkers makes it difficult to assess their utility in diagnosis and prognosis. The evidence is insufficient to determine the effects of the technology on health outcomes.

Population Reference No. 1 Policy Statement [ ] MedicallyNecessary [x ] Investigational [ ] Not Medically Necessary


Supplemental Information

Practice Guidelines and Position Statements

Multiple Sclerosis Think Tank In 2013, the Multiple Sclerosis Think Tank, a group of approximately 40 hospital neurologists in France, published consensus recommendations for serum tests useful to diagnose MS.15 Recommendations were developed by systematic review of the literature and a Delphi consensus process. Panelists concurred that “there is currently no useful biological blood test for the positive diagnosis of MS.”

International Advisory Committee on Clinical Trials in Multiple Sclerosis In 2014, the International Advisory Committee on Clinical Trials in Multiple Sclerosis, jointly sponsored by the U.S. National Multiple Sclerosis Society, the European Committee for Treatment and Research in Multiple Sclerosis, and the MS Phenotype Group, published results of its deliberations on the MS clinical course descriptions in light of current evidence for improved descriptive terminology (eg, incorporating evidence for serum and other biomarkers).49 The Committee concluded: “To date, there are no clear clinical, imaging, immunologic, or pathologic criteria to determine the transition point when RRMS [relapse-remitting MS] converts to SPMS [secondary progressive MS]; the transition is usually gradual. This has limited our ability to study the imaging and biomarker characteristics that may distinguish this course.”

U.S. Preventive Services Task Force Recommendations

Not applicable.

Practice Guidelines and Position Statements

Practice Guidelines and Position Statements

Multiple Sclerosis Think Tank In 2013, the Multiple Sclerosis Think Tank, a group of approximately 40 hospital neurologists in France, published consensus recommendations for serum tests useful to diagnose MS.15 Recommendations were developed by systematic review of the literature and a Delphi consensus process. Panelists concurred that “there is currently no useful biological blood test for the positive diagnosis of MS.”

International Advisory Committee on Clinical Trials in Multiple Sclerosis In 2014, the International Advisory Committee on Clinical Trials in Multiple Sclerosis, jointly sponsored by the U.S. National Multiple Sclerosis Society, the European Committee for Treatment and Research in Multiple Sclerosis, and the MS Phenotype Group, published results of its deliberations on the MS clinical course descriptions in light of current evidence for improved descriptive terminology (eg, incorporating evidence for serum and other biomarkers).49 The Committee concluded: “To date, there are no clear clinical, imaging, immunologic, or pathologic criteria to determine the transition point when RRMS [relapse-remitting MS] converts to SPMS [secondary progressive MS]; the transition is usually gradual. This has limited our ability to study the imaging and biomarker characteristics that may distinguish this course.”

U.S. Preventive Services Task Force Recommendations

Not applicable.

Medicare National Coverage

Medicare National Coverage There is no national coverage determination (NCD). In the absence of an NCD, coverage decisions are left to the discretion of local Medicare carriers.

References

1. Evans C, Beland SG, Kulaga S, et al. Incidence and prevalence of multiple sclerosis in the Americas: a systematic review. Neuroepidemiology. 2013;40(3):195-210. PMID 23363936

2. Wingerchuk DM, Carter JL. Multiple sclerosis: current and emerging disease-modifying therapies and treatment strategies. Mayo Clin Proc. Feb 2014;89(2):225-240. PMID 24485135

3. Polman CH, Reingold SC, Banwell B, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. Feb 2011;69(2):292-302. PMID 21387374

4. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. Nov 1983;33(11):1444-1452. PMID 6685237

5. Kappos L, Freedman MS, Polman CH, et al. Effect of early versus delayed interferon beta-1b treatment on disability after a first clinical event suggestive of multiple sclerosis: a 3-year follow-up analysis of the BENEFIT study. Lancet. Aug 4 2007;370(9585):389-397. PMID 17679016

6. Kappos L, Freedman MS, Polman CH, et al. Long-term effect of early treatment with interferon beta-1b after a first clinical event suggestive of multiple sclerosis: 5-year active treatment extension of the phase 3 BENEFIT trial. Lancet Neurol. Nov 2009;8(11):987-997. PMID 19748319

7. Keegan BM. Therapeutic decision making in a new drug era in multiple sclerosis. Semin Neurol. Feb 2013;33(1):5-12. PMID 23709208

8. Hadjigeorgiou GM, Doxani C, Miligkos M, et al. A network meta-analysis of randomized controlled trials for comparing the effectiveness and safety profile of treatments with marketing authorization for relapsing multiple sclerosis. J Clin Pharm Ther. Dec 2013;38(6):433-439. PMID 23957759

9. Schwarz M, Spector L, Gortler M, et al. Serum anti-Glc(alpha1,4)Glc(alpha) antibodies as a biomarker for relapsing-remitting multiple sclerosis. J Neurol Sci. May 15 2006;244(1-2):59-68. PMID 16480743

10. Brettschneider J, Jaskowski TD, Tumani H, et al. Serum anti-GAGA4 IgM antibodies differentiate relapsing remitting and secondary progressive multiple sclerosis from primary progressive multiple sclerosis and other neurological diseases. J Neuroimmunol. Dec 10 2009;217(1-2):95-101. PMID 19879655

11. Freedman MS, Laks J, Dotan N, et al. Anti-alpha-glucose-based glycan IgM antibodies predict relapse activity in multiple sclerosis after the first neurological event. Mult Scler. Apr 2009;15(4):422-430. PMID 19324980

12. Freedman MS, Metzig C, Kappos L, et al. Predictive nature of IgM anti-alpha-glucose serum biomarker for relapse activity and EDSS progression in CIS patients: a BENEFIT study analysis. Mult Scler. Jul 2012;18(7):966-973. PMID 22183938

13. Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald Criteria". Ann Neurol. Dec 2005;58(6):840-846. PMID 16283615

14. Comabella M, Montalban X. Body fluid biomarkers in multiple sclerosis. Lancet Neurol. Jan 2014;13(1):113-126. PMID 24331797

15. Ouallet JC, Bodiguel E, Bensa C, et al. Recommendations for useful serum testing with suspected multiple sclerosis. Rev Neurol (Paris). Jan 2013;169(1):37-46. PMID 22325711

16. Brill L, Goldberg L, Karni A, et al. Increased anti-KIR4.1 antibodies in multiple sclerosis: Could it be a marker of disease relapse? Mult Scler. Apr 2015;21(5):572-579. PMID 25392324

17. Findling O, Durot I, Weck A, et al. Antimyelin antibodies as predictors of disability after clinically isolated syndrome. Int J Neurosci. Aug 2014;124(8):567-572. PMID 24274327 18. Koudriavtseva T, D'Agosto G, Mandoj C, et al. High frequency of antiphospholipid antibodies in relapse of multiple sclerosis: a possible indicator of inflammatory-thrombotic processes. Neurol Sci. Nov 2014;35(11):1737- 1741. PMID 24847961

19. Colomba P, Fontana S, Salemi G, et al. Identification of biomarkers in cerebrospinal fluid and serum of multiple sclerosis patients by immunoproteomics approach. Int J Mol Sci. 2014;15(12):23269-23282. PMID 25517032

20. Moreno C, Prieto P, Macias A, et al. Modulation of voltage-dependent and inward rectifier potassium channels by 15-epi-lipoxin-A4 in activated murine macrophages: implications in innate immunity. J Immunol. Dec 15 2013;191(12):6136-6146. PMID 24249731

21. Holmoy T, Loken-Amsrud KI, Bakke SJ, et al. Inflammation markers in multiple sclerosis: CXCL16 reflects and may also predict disease activity. PLoS One. 2013;8(9):e75021. PMID 24069377

22. Ingram G, Hakobyan S, Hirst CL, et al. Complement regulator factor H as a serum biomarker of multiple sclerosis disease state. Brain. Jun 2010;133(Pt 6):1602-1611. PMID 20421219

23. Kvistad S, Myhr KM, Holmoy T, et al. Antibodies to Epstein-Barr virus and MRI disease activity in multiple sclerosis. Mult Scler. Dec 2014;20(14):1833-1840. PMID 24842958

24. Sternberg Z, Sternberg D, Drake A, et al. Disease modifying drugs modulate endogenous secretory receptor for advanced glycation end-products, a new biomarker of clinical relapse in multiple sclerosis. J Neuroimmunol. Sep 15 2014;274(1-2):197-201. PMID 25064498

25. Gironi M, Solaro C, Meazza C, et al. Growth hormone and disease severity in early stage of multiple sclerosis. Mult Scler Int. 2013;2013:836486. PMID 24260717

26. Ortega-Madueño I, Garcia-Montojo M, Dominguez-Mozo MI, et al. Anti-human herpesvirus 6A/B IgG correlates with relapses and progression in multiple sclerosis. PLoS One. 2014;9(8):e104836. PMID 25110949

27. Dimisianos N, Rodi M, Kalavrizioti D, et al. Cytokines as biomarkers of treatment response to IFN beta in relapsing-remitting multiple sclerosis. Mult Scler Int. 2014;2014:436764. PMID 25152817

28. Fissolo N, Canto E, Vidal-Jordana A, et al. Levels of soluble TNF-RII are increased in serum of patients with primary progressive multiple sclerosis. J Neuroimmunol. Jun 15 2014;271(1-2):56-59. PMID 24794503

29. Polachini CR, Spanevello RM, Casali EA, et al. Alterations in the cholinesterase and adenosine deaminase activities and inflammation biomarker levels in patients with multiple sclerosis. Neuroscience. Apr 25 2014;266:266-274. PMID 24508813

30. Uysal S, Meric Yilmaz F, Bogdaycioglu N, et al. Increased serum levels of some inflammatory markers in patients with multiple sclerosis. Minerva Med. Jun 2014;105(3):229-235. PMID 24988088

31. Trenova AG, Slavov GS, Manova MG, et al. Cytokines and disability in interferon-beta-1b treated and untreated women with multiple sclerosis. Arch Med Res. Aug 2014;45(6):495-500. PMID 25130430

32. Hartung HP, Reiners K, Archelos JJ, et al. Circulating adhesion molecules and tumor necrosis factor receptor in multiple sclerosis: correlation with magnetic resonance imaging. Ann Neurol. Aug 1995;38(2):186-193. PMID 7544573

33. Trojano M, Avolio C, Simone IL, et al. Soluble intercellular adhesion molecule-1 in serum and cerebrospinal fluid of clinically active relapsing-remitting multiple sclerosis: correlation with Gd-DTPA magnetic resonance imagingenhancement and cerebrospinal fluid findings. Neurology. Dec 1996;47(6):1535-1541. PMID 8960741

34. Aydin O, Ellidag HY, Eren E, et al. Ischemia modified albumin is an indicator of oxidative stress in multiple sclerosis. Biochem Med (Zagreb). 2014;24(3):383-389. PMID 25351357

35. Amorini AM, Nociti V, Petzold A, et al. Serum lactate as a novel potential biomarker in multiple sclerosis. Biochim Biophys Acta. Jul 2014;1842(7):1137-1143. PMID 24726946

36. Jafarzadeh A, Ebrahimi HA, Bagherzadeh S, et al. Lower serum levels of Th2-related chemokine CCL22 in women patients with multiple sclerosis: a comparison between patients and healthy women. Inflammation. Apr 2014;37(2):604-610. PMID 24254331

37. Stilund M, Reuschlein AK, Christensen T, et al. Soluble CD163 as a marker of macrophage activity in newly diagnosed patients with multiple sclerosis. PLoS One. 2014;9(6):e98588. PMID 24886843

38. Dickens AM, Larkin JR, Griffin JL, et al. A type 2 biomarker separates relapsing-remitting from secondary progressive multiple sclerosis. Neurology. Oct 21 2014;83(17):1492-1499. PMID 25253748

39. Waubant E, Goodkin DE, Gee L, et al. Serum MMP-9 and TIMP-1 levels are related to MRI activity in relapsing multiple sclerosis. Neurology. Oct 22 1999;53(7):1397-1401. PMID 10534241

40. Trentini A, Manfrinato MC, Castellazzi M, et al. TIMP-1 resistant matrix metalloproteinase-9 is the predominant serum active isoform associated with MRI activity in patients with multiple sclerosis. Mult Scler. Aug 2015;21(9):1121-1130. PMID 25662349

41. Kacperska MJ, Jastrzebski K, Tomasik B, et al. Selected extracellular microRNA as potential biomarkers of multiple sclerosis activity--preliminary study. J Mol Neurosci. May 2015;56(1):154-163. PMID 25487315

42. Berger T, Rubner P, Schautzer F, et al. Antimyelin antibodies as a predictor of clinically definite multiple sclerosis after a first demyelinating event. N Engl J Med. Jul 10 2003;349(2):139-145. PMID 12853586

43. Kuhle J, Pohl C, Mehling M, et al. Lack of association between antimyelin antibodies and progression to multiple sclerosis. N Engl J Med. Jan 25 2007;356(4):371-378. PMID 17251533

44. Koch MW, George S, Wall W, et al. Serum NSE level and disability progression in multiple sclerosis. J Neurol Sci. Mar 15 2015;350(1-2):46-50. PMID 25686504

45. Kivisakk P, Healy BC, Francois K, et al. Evaluation of circulating osteopontin levels in an unselected cohort of patients with multiple sclerosis: relevance for biomarker development. Mult Scler. Sep 4 2013. PMID 24005026

46. Shimizu Y, Ota K, Ikeguchi R, et al. Plasma osteopontin levels are associated with disease activity in the patients with multiple sclerosis and neuromyelitis optica. J Neuroimmunol. Oct 15 2013;263(1-2):148-151. PMID 23910387

47. Siroos B, Balood M, Zahednasab H, et al. Secretory phospholipase A2 activity in serum and cerebrospinal fluid of patients with relapsing-remitting multiple sclerosis. J Neuroimmunol. Sep 15 2013;262(1-2):125-127. PMID 23859159

48. Moccia M, Lanzillo R, Palladino R, et al. Uric acid: a potential biomarker of multiple sclerosis and of its disability. Clin Chem Lab Med. Apr 2015;53(5):753-759. PMID 25241733

49. Lublin FD, Reingold SC, Cohen JA, et al. Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology. Jul 15 2014;83(3):278-286. PMID 24871874

Codes

Codes Number Description
CPT   No specific code (see Policy Guidelines)
ICD-10-CM   Investigational for all relevant diagnoses
  G35  
ICD-10-PCS   Not applicable. ICD-10-PCS codes are only used for inpatient services. There are no ICD procedure codes for laboratory tests.
Type of Service    
Place of Service    
     
     
     

Appplicable Modifiers

Some modifiers

Policy History

Date Action Description
Jun 8, 2020 New Policy Adopted from BCBS