Jak monitorować skuteczność leczenia w stwardnieniu rozsianym Artykuł przeglądowy
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Opublikowane:
gru 31, 2019
Słowa kluczowe:
terapie modyfikujące przebieg choroby, neurofilamenty lekkie, rezonans magnetyczny, terapia personalizowana
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Abstrakt
Decyzja o wyborze terapii w stwardnieniu rozsianym wymaga coraz więcej uwagi ze względu na powiększającą się w szybkim tempie liczbę leków, którymi dysponujemy. Jak w każdej przewlekłej chorobie zwraca sie uwagę na indywidualizację terapii i dopasowanie jej zarówno do pacjenta (jego stanu zdrowia, dodatkowych chorób, planów życiowych i preferencji), jak i do aktywności choroby, uwzględniając profil bezpieczeństwa, mechanizm działania i skuteczność wybranego leku. Wczesne rozpoczęcie leczenia i zahamowanie aktywności procesu zapalnego daje szansę na lepszy przebieg choroby i niewystąpienie lub wolniejszy rozwój niepełnosprawności. Monitorowanie skuteczności leczenia powinno obejmować dokładną analizę pogorszeń klinicznych i obrazowania metodą rezonansu magnetycznego, ale również postęp niepełnosprawności i zaburzenia funkcji poznawczych. Rozwój nowych markerów biologicznych, jak np. stężenie neurofilamentów lekkich w surowicy, pozwala mieć nadzieję na lepszą ocenę odpowiedzi na leki.
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Artykuły
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Bibliografia
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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.