How to monitor the effectiveness of treatment in multiple sclerosis Review article
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Published:
Dec 31, 2019
Keywords:
disease modifying therapy (DMT), magnetic resonance imaging, neurofilament light chain, personalized therapy
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Abstract
The decision on therapy in multiple sclerosis (MS) requires more and more attention due to the rapidly increasing number of drugs available. As in any chronic disease, attention is paid to the individualization of therapy and its adaptation to both the patient (his state of health, comorbidities, life plans and preferences) and to the activity of the disease, taking into account the safety profile, mechanism of action and effectiveness of the selected drug. Early treatment initiation and inhibition of the inflammatory process gives a chance for a better course of the disease and no occurrence, or a slower development of disability. Monitoring the effectiveness of treatment should carefully analyze clinical deterioration and magnetic resonance imaging, but also disability progression and cognitive impairment. The development of new biological markers, such as the level of light neurofilaments in serum, gives hope for better assessment of drug response.
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References
1. Brown JWL, Coles A, Horakova D et al. MSBase Study Group. Association of Initial Disease-Modifying Therapy With Later Conversion to Secondary Progressive Multiple Sclerosis. JAMA 2019; 321(2): 175-187.
2. Kingwell E, Leray E, Zhu F et al. Multiple sclerosis: effect of beta interferon treatment on survival. Brain 2019; 142(5): 1324-1333.
3. Goodin DS, Reder AT, Ebers GC et al. Survival in MS: a randomized cohort study 21 years after the start of the pivotal IFNβ-1b trial. Neurology 2012; 78(17): 1315-1322.
4. Palace J, Duddy M, Lawton M et al. Assessing the long-term effectiveness of interferon-beta and glatiramer acetate in multiple sclerosis: final 10-year results from the UK multiple sclerosis risk-sharing scheme. J Neurol Neurosurg Psychiatry 2019; 90(3): 251-260.
5. Harding K, Williams O, Willis M et al. Clinical Outcomes of Escalation vs Early Intensive Disease-Modifying Therapy in Patients With Multiple Sclerosis. JAMA Neurol 2019; 76(5): 536-541.
6. Avasarala J. Redefining Acute Relapses in Multiple Sclerosis: Implications for Phase 3 Clinical Trials and Treatment Algorithms. Innov Clin Neurosci 2017; 14(3-4): 38-40.
7. Montalban X, Gold R, Thompson AJ et al. ECTRIMS/EAN guideline on the pharmacological treatment of people with multiple sclerosis. Mult Scler J 2018; 24(2): 96-120.
8. Reuter F, Zaaraoui W, Crespy L et al. Frequency of cognitive impairment dramatically increases during the first 5 years of multiple sclerosis. J Neurol Neurosurg Psychiatry 2011; 82: 1157-1159.
9. Ochi H. Clinical trials for multiple sclerosis: Outcome measures and impact on cognitive function. Clin Experiment Neuroimmunol 2019; 10: 169-179.
10. Morrow SA, O’Connor PW, Polman CH et al. Evaluation of the symbol digit modalities test (SDMT) and MS neuropsychological screening questionnaire (MSNQ) in natalizumab-treated MS patients over 48 weeks. Mult Scler 2010; 16: 1385-1392.
11. Rocca MA, Battaglini M, Benedict RH et al. Brain MRI atrophy quantification in MS: From methods to clinical application. Neurology 2017; 88(4): 403-413.
12. Sormani MP and Bruzzi P. MRI lesions as a surrogate for relapses in multiple sclerosis: a meta-analysis of randomised trials. Lancet Neurol 2013; 12: 669-676.
13. Prosperini L, Gallo V, Petsas N et al. Oneyear MRI scan predicts clinical response to interferon beta in multiple sclerosis. Eur J Neurol 2009; 16: 1202-1209.
14. Bermel RA, You X, Foulds P et al. Predictors of long-term outcome in multiple sclerosis patients treated with interferon beta. Ann Neurol 2013; 73: 95-103.
15. Giovannoni G, Turner B, Gnanapavan S et al. Is it time to target no evident disease activity (NEDA) in multiple sclerosis? Mult Scler Relat Disord 2015; 4: 329-333.
16. Stangel M, Penner IK, Kallmann BA et al. Towards the implementation of ‘no evidence of disease activity’ in multiple sclerosis treatment: the multiple sclerosis decision model. Ther Adv Neurol Disord 2015; 8: 3-13.
17. Sąsiadek M, Walecki J, Majos A et al. Zalecenia Polskiego Lekarskiego Towarzystwa Radiologicznego do stosowanego rutynowo protokołu badania MR u pacjentów ze stwardnieniem rozsianym [Online].
18. Hoepner R, Kolb EM, Dahlhaus S et al. Predictors of severity and functional outcome in natalizumab-associated progressive multifocal leukoencephalopathy. Mult Scler 2017; 23(6): 830-835.
19. McGuigan C, Craner M, Guadagno J et al. Stratification and monitoring of natalizumab-associated progressive multifocal leukoencephalopathy risk: recommendations from an expert group. J Neurol Neurosurg Psychiatry 2016; 87: 117-125.
20. Major EO, Yousry TA, Clifford DB. Pathogenesis of progressive multifocal leukoencephalopathy and risks associated with treatments for multiple sclerosis: a decade of lessons learned. Lancet Neurol 2018; 17(5): 467-480.
21. Kaunzner UW, Gauthier SA. MRI in the assessment and monitoring of multiple sclerosis: an update on best practice. Ther Adv Neurol Disord 2017; 10(6): 247-261.
22. Casserly C, Seyman EE, Alcaide-Leon P et al. Spinal Cord Atrophy in Multiple Sclerosis: A Systematic Review and Meta-Analysis. J Neuroimaging 2018; 28(6): 556-586.
23. Kuhle J, Kropshofer H, Haering DA et al. Blood neurofilament light chain as a biomarker of MS disease activity and treatment response. Neurology 2019; 92(10): e1007-e1015.
24. Varhaug KN, Barro C, Bjornevik K et al. Neurofilament light chain predicts disease activity in relapsingremitting MS. Neurol Neuroimmunol Neuroinflamm 2018; 5(1): e422.
25. Bhan A, Jacobsen C, Myhr KM et al. Neurofilaments and 10-year follow-up in multiple sclerosis. Mult Scler 2018; 24(10): 1301-1307.
26. Chitnis T, Gonzalez C, Healy BC et al. Neurofilament light chain serum levels correlate with 10-year MRI outcomes in multiple sclerosis. Ann Clin Transl Neurol 2018; (5): 1478-1491.
27. Varhaug KN, Torkildsen Ø, Myhr KM, Vedeler CA. Neurofilament Light Chain as a Biomarker in Multiple Sclerosis. Front Neurol 2019; 10: 338. doi: 10.3389/fneur.2019.00338. eCollection 2019.
28. Rissin DM, Kan CW, Campbell TG et al. Single-molecule enzyme-linked immunosorbent assay detects serum proteins at subfemtomolar concentrations. Nat Biotechnol 2010; 28: 595-599.
29. Disanto G, Barro C, Benkert P et al. Serum Neurofilament light: a biomarker of neuronal damage in multiple sclerosis. Ann Neurol 2017; 81: 857-870. doi: 10.1002/ana.24954.
30. Novakova L, Zetterberg H, Sundstrom P et al. Monitoring disease activity in multiple sclerosis using serum neurofilament light protein. Neurology 2017; 89: 2230-2237.
31. Axelsson M, Malmestrom C, Gunnarsson M et al. Immunosuppressive therapy reduces axonal damage in progressive multiple sclerosis. Mult Scler 2014; 20: 43-50.
32. de Flon P, Gunnarsson M, Laurell K et al. Reduced inflammation in relapsing-remitting multiple sclerosis after therapy switch to rituximab. Neurology 2016; 87: 141-147.
33. Cai L, Huang J. Neurofilament light chain as a biological marker for multiple sclerosis: a meta-analysis study. Neuropsychiatr Dis Treat 2018; 14: 2241-2254.
34. Bertolotto A, Granieri L, Marnetto F et al. Biological monitoring of IFNβ therapy in multiple sclerosis. Cytokine Growth Factor Rev 2015; 26: 241-248.
35. Bertolotto A, Capobianco M, Amato MP et al. Guidelines on the clinical use for the detection of neutralizing antibodies (NAbs) to IFN beta in multiple sclerosis therapy: report from the Italian Multiple Sclerosis Study Group. Neurol Sci 2014; 35: 307-316.
36. Foley JF, Goelz S, Hoyt T et al. Evaluation of natalizumab pharmacokinetics and pharmacodynamics with standard and extended interval dosing. Mult Scler Relat Disord 2019; 31: 65-71.
37. Derfuss T, Kovarik JM, Kappos L et al. α4-integrin receptor desaturation and disease activity return after natalizumab cessation. Neurol Neuroimmunol Neuroinflamm 2017; 4(5): e388.
38. Ryerson LZ, Foley J, Chang I et al. Risk of natalizumab-associated PML in patients with MS is reduced with extended interval dosing. Neurology 2019; 93(15): e1452-e1462.
39. Sehr T, Proschmann U, Thomas K et al. New insights into the pharmacokinetics and pharmacodynamics of natalizumab treatment for patients with multiple sclerosis, obtained from clinical and in vitro studies. J Neuroinflammation 2016; 13: 164.
40. Walter E, Deisenhammer F. Socio-economic aspects of the testing for antibodies in MS-patients under interferon therapy in Austria: a cost of illness study. Mult Scler Relat Disord 2014; 3: 670-677.
41. Lublin FD, Cofield SS, Cutter GR et al. Randomized study combining interferon and glatiramer acetate in multiple sclerosis. Ann Neurol 2013; 73(3): 327-340.
2. Kingwell E, Leray E, Zhu F et al. Multiple sclerosis: effect of beta interferon treatment on survival. Brain 2019; 142(5): 1324-1333.
3. Goodin DS, Reder AT, Ebers GC et al. Survival in MS: a randomized cohort study 21 years after the start of the pivotal IFNβ-1b trial. Neurology 2012; 78(17): 1315-1322.
4. Palace J, Duddy M, Lawton M et al. Assessing the long-term effectiveness of interferon-beta and glatiramer acetate in multiple sclerosis: final 10-year results from the UK multiple sclerosis risk-sharing scheme. J Neurol Neurosurg Psychiatry 2019; 90(3): 251-260.
5. Harding K, Williams O, Willis M et al. Clinical Outcomes of Escalation vs Early Intensive Disease-Modifying Therapy in Patients With Multiple Sclerosis. JAMA Neurol 2019; 76(5): 536-541.
6. Avasarala J. Redefining Acute Relapses in Multiple Sclerosis: Implications for Phase 3 Clinical Trials and Treatment Algorithms. Innov Clin Neurosci 2017; 14(3-4): 38-40.
7. Montalban X, Gold R, Thompson AJ et al. ECTRIMS/EAN guideline on the pharmacological treatment of people with multiple sclerosis. Mult Scler J 2018; 24(2): 96-120.
8. Reuter F, Zaaraoui W, Crespy L et al. Frequency of cognitive impairment dramatically increases during the first 5 years of multiple sclerosis. J Neurol Neurosurg Psychiatry 2011; 82: 1157-1159.
9. Ochi H. Clinical trials for multiple sclerosis: Outcome measures and impact on cognitive function. Clin Experiment Neuroimmunol 2019; 10: 169-179.
10. Morrow SA, O’Connor PW, Polman CH et al. Evaluation of the symbol digit modalities test (SDMT) and MS neuropsychological screening questionnaire (MSNQ) in natalizumab-treated MS patients over 48 weeks. Mult Scler 2010; 16: 1385-1392.
11. Rocca MA, Battaglini M, Benedict RH et al. Brain MRI atrophy quantification in MS: From methods to clinical application. Neurology 2017; 88(4): 403-413.
12. Sormani MP and Bruzzi P. MRI lesions as a surrogate for relapses in multiple sclerosis: a meta-analysis of randomised trials. Lancet Neurol 2013; 12: 669-676.
13. Prosperini L, Gallo V, Petsas N et al. Oneyear MRI scan predicts clinical response to interferon beta in multiple sclerosis. Eur J Neurol 2009; 16: 1202-1209.
14. Bermel RA, You X, Foulds P et al. Predictors of long-term outcome in multiple sclerosis patients treated with interferon beta. Ann Neurol 2013; 73: 95-103.
15. Giovannoni G, Turner B, Gnanapavan S et al. Is it time to target no evident disease activity (NEDA) in multiple sclerosis? Mult Scler Relat Disord 2015; 4: 329-333.
16. Stangel M, Penner IK, Kallmann BA et al. Towards the implementation of ‘no evidence of disease activity’ in multiple sclerosis treatment: the multiple sclerosis decision model. Ther Adv Neurol Disord 2015; 8: 3-13.
17. Sąsiadek M, Walecki J, Majos A et al. Zalecenia Polskiego Lekarskiego Towarzystwa Radiologicznego do stosowanego rutynowo protokołu badania MR u pacjentów ze stwardnieniem rozsianym [Online].
18. Hoepner R, Kolb EM, Dahlhaus S et al. Predictors of severity and functional outcome in natalizumab-associated progressive multifocal leukoencephalopathy. Mult Scler 2017; 23(6): 830-835.
19. McGuigan C, Craner M, Guadagno J et al. Stratification and monitoring of natalizumab-associated progressive multifocal leukoencephalopathy risk: recommendations from an expert group. J Neurol Neurosurg Psychiatry 2016; 87: 117-125.
20. Major EO, Yousry TA, Clifford DB. Pathogenesis of progressive multifocal leukoencephalopathy and risks associated with treatments for multiple sclerosis: a decade of lessons learned. Lancet Neurol 2018; 17(5): 467-480.
21. Kaunzner UW, Gauthier SA. MRI in the assessment and monitoring of multiple sclerosis: an update on best practice. Ther Adv Neurol Disord 2017; 10(6): 247-261.
22. Casserly C, Seyman EE, Alcaide-Leon P et al. Spinal Cord Atrophy in Multiple Sclerosis: A Systematic Review and Meta-Analysis. J Neuroimaging 2018; 28(6): 556-586.
23. Kuhle J, Kropshofer H, Haering DA et al. Blood neurofilament light chain as a biomarker of MS disease activity and treatment response. Neurology 2019; 92(10): e1007-e1015.
24. Varhaug KN, Barro C, Bjornevik K et al. Neurofilament light chain predicts disease activity in relapsingremitting MS. Neurol Neuroimmunol Neuroinflamm 2018; 5(1): e422.
25. Bhan A, Jacobsen C, Myhr KM et al. Neurofilaments and 10-year follow-up in multiple sclerosis. Mult Scler 2018; 24(10): 1301-1307.
26. Chitnis T, Gonzalez C, Healy BC et al. Neurofilament light chain serum levels correlate with 10-year MRI outcomes in multiple sclerosis. Ann Clin Transl Neurol 2018; (5): 1478-1491.
27. Varhaug KN, Torkildsen Ø, Myhr KM, Vedeler CA. Neurofilament Light Chain as a Biomarker in Multiple Sclerosis. Front Neurol 2019; 10: 338. doi: 10.3389/fneur.2019.00338. eCollection 2019.
28. Rissin DM, Kan CW, Campbell TG et al. Single-molecule enzyme-linked immunosorbent assay detects serum proteins at subfemtomolar concentrations. Nat Biotechnol 2010; 28: 595-599.
29. Disanto G, Barro C, Benkert P et al. Serum Neurofilament light: a biomarker of neuronal damage in multiple sclerosis. Ann Neurol 2017; 81: 857-870. doi: 10.1002/ana.24954.
30. Novakova L, Zetterberg H, Sundstrom P et al. Monitoring disease activity in multiple sclerosis using serum neurofilament light protein. Neurology 2017; 89: 2230-2237.
31. Axelsson M, Malmestrom C, Gunnarsson M et al. Immunosuppressive therapy reduces axonal damage in progressive multiple sclerosis. Mult Scler 2014; 20: 43-50.
32. de Flon P, Gunnarsson M, Laurell K et al. Reduced inflammation in relapsing-remitting multiple sclerosis after therapy switch to rituximab. Neurology 2016; 87: 141-147.
33. Cai L, Huang J. Neurofilament light chain as a biological marker for multiple sclerosis: a meta-analysis study. Neuropsychiatr Dis Treat 2018; 14: 2241-2254.
34. Bertolotto A, Granieri L, Marnetto F et al. Biological monitoring of IFNβ therapy in multiple sclerosis. Cytokine Growth Factor Rev 2015; 26: 241-248.
35. Bertolotto A, Capobianco M, Amato MP et al. Guidelines on the clinical use for the detection of neutralizing antibodies (NAbs) to IFN beta in multiple sclerosis therapy: report from the Italian Multiple Sclerosis Study Group. Neurol Sci 2014; 35: 307-316.
36. Foley JF, Goelz S, Hoyt T et al. Evaluation of natalizumab pharmacokinetics and pharmacodynamics with standard and extended interval dosing. Mult Scler Relat Disord 2019; 31: 65-71.
37. Derfuss T, Kovarik JM, Kappos L et al. α4-integrin receptor desaturation and disease activity return after natalizumab cessation. Neurol Neuroimmunol Neuroinflamm 2017; 4(5): e388.
38. Ryerson LZ, Foley J, Chang I et al. Risk of natalizumab-associated PML in patients with MS is reduced with extended interval dosing. Neurology 2019; 93(15): e1452-e1462.
39. Sehr T, Proschmann U, Thomas K et al. New insights into the pharmacokinetics and pharmacodynamics of natalizumab treatment for patients with multiple sclerosis, obtained from clinical and in vitro studies. J Neuroinflammation 2016; 13: 164.
40. Walter E, Deisenhammer F. Socio-economic aspects of the testing for antibodies in MS-patients under interferon therapy in Austria: a cost of illness study. Mult Scler Relat Disord 2014; 3: 670-677.
41. Lublin FD, Cofield SS, Cutter GR et al. Randomized study combining interferon and glatiramer acetate in multiple sclerosis. Ann Neurol 2013; 73(3): 327-340.