Aktuelle Neurologie 2013; 40(09): 486-493
DOI: 10.1055/s-0033-1349643
Originalarbeit
© Georg Thieme Verlag KG Stuttgart · New York

Multiple Sclerosis Decision Model (MSDM): Entwicklung eines Mehrfaktorenmodells zur Beurteilung des Therapie- und Krankheitsverlaufs bei schubförmiger Multipler Sklerose

Multiple Sclerosis Decision Model (MSDM): Development of a Multifactorial Model to Monitor Treatment Response and Disease Course in Relapsing Remitting Multiple Sclerosis
M. Stangel
1   Klinische Neuroimmunologie und Neurochemie, Neurologische Klinik, Medizinische Hochschule Hannover
,
I. K. Penner
2   Kognitive Psychologie und Methodologie, Universität Basel, Schweiz
,
B. A. Kallmann
3   Multiple-Sklerose-Zentrum Franken, Bamberg
,
C. Lukas
4   Institut für diagnostische und interventionelle Radiologie, St. Josef Hospital, Ruhr-Universität Bochum
,
B. C. Kieseier
5   Neurologische Klinik, Medizinische Fakultät, Heinrich-Heine-Universität Düsseldorf
,
R. Gold
6   Klinik für Neurologie, St. Josef Hospital, Ruhr-Universität Bochum
› Author Affiliations
Further Information

Publication History

Publication Date:
17 October 2013 (online)

Zusammenfassung

Die Einführung neuer und potenter Therapeutika für die Behandlung der schubförmigen Multiplen Sklerose (MS) hat die Ansprüche an den Therapieerfolg gesteigert. Eine alleinige Reduktion der Schubrate ist nicht mehr ausreichend, sondern das Ziel sollte eine „Freiheit von klinisch relevanter Krankheitsaktivität“ sein. Eine allgemein akzeptierte Definition liegt derzeit noch nicht vor. Ein deutsches Expertengremium formulierte hierzu die Forderung, dass ein solcher Parameter neben der Schubrate, Behinderungsprogression und MRT-Parametern auch neuropsychologische Kriterien und Lebensqualität eingeschlossen werden sollten. Wie dies unter Alltagsbedingungen gemessen werden kann, bedarf einer weiteren Präzisierung. Um die Untersuchungen standardisiert, zeitökonomisch und schematisiert durchzuführen, wird hier ein Mehrfaktorenmodell (Multiple Sclerosis Decision Model, MSDM) vorgeschlagen, welches die Domänen „Schub“, „Behinderungsprogression“, „MRT“ und „Neuropsychologie“ beinhaltet. Die vorgeschlagenen Tests bilden die Komplexität der Erkrankung auch in frühen Stadien ab, in denen eine Progression mit z. B. der EDSS (Expanded Disability Status Scale) nur schwer zu erfassen ist. Das MSDM soll eine Hilfe für Therapieentscheidungen darstellen und ein Therapieversagen frühzeitig anzeigen. Prospektive Untersuchungen sind erforderlich, um zu prüfen, ob mittels dieses Instruments zum Krankheitsmonitoring tatsächlich eine effektivere Behandlung und schnellere Krankheitsstabilisierung erreicht werden kann.

Abstract

The introduction of new and potent medications for the treatment of relapsing-remitting multiple sclerosis (MS) has increased the desire for therapeutic success. The mere reduction of the relapse rate is not sufficient anymore. Instead, the goal should be the “absence of clinically relevant disease activity”. However, there is no generally accepted definition so far. A panel of German experts has proposed that achievement of this therapeutic aim should include – beside relapse rate, disability progression and MRI parameters – neuropsychological tests and quality of life measures. A specification is required as to how this can be measured in everyday practice. In order to standardise the investigations in an economic and schematic way, a multifactorial model (Multiple Sclerosis Decision Model, MSDM) is proposed that includes the domains “relapse”, “disability progression”, “MRI”, and “neuropsychology”. The proposed tests reflect the complexity of the disease even in the early stages when scales like the EDSS (Expanded Disability Status Scale) are not able to discriminate low levels of progression. The MSDM is intended to support early treatment decisions and uncover treatment failures early on. Prospective investigations are required to prove that such a disease monitoring does indeed lead to an early and effective disease stabilisation.

 
  • Literatur

  • 1 Polman CH, O’Connor PW, Havrdova E et al. A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N Engl J Med 2006; 354: 899-910
  • 2 Kappos L, Radue EW, O’Connor P et al. A placebo-controlled trial of oral fingolimod in relapsing multiple sclerosis. N Engl J Med 2010; 362: 387-401
  • 3 Goodman AD, Rossman H, Bar-Or A et al. GLANCE: results of a phase 2, randomized, double-blind, placebo-controlled study. Neurology 2009; 72: 806-812
  • 4 Khatri B, Barkhof F, Comi G et al. Comparison of fingolimod with interferon beta-1a in relapsing-remitting multiple sclerosis: a randomised extension of the TRANSFORMS study. Lancet Neurol 2011; 10: 520-529
  • 5 Rudick RA, Stuart WH, Calabresi PA et al. Natalizumab plus interferon beta-1a for relapsing multiple sclerosis. N Engl J Med 2006; 354: 911-923
  • 6 Havrdova E, Galetta S, Hutchinson M et al. Effect of natalizumab on clinical and radiological disease activity in multiple sclerosis: a retrospective analysis of the Natalizumab Safety and Efficacy in Relapsing-Remitting Multiple Sclerosis (AFFIRM) study. Lancet Neurol 2009; 8: 254-260
  • 7 Gold R, Hartung HP, Stangel M et al. Therapeutic Goals of Baseline and Escalation Therapy for Relapsing-Remitting Multiple Sclerosis. Akt Neurol 2012; 39: 342-350
  • 8 Rudick RA, Polman CH. Current approaches to the identification and management of breakthrough disease in patients with multiple sclerosis. Lancet Neurol 2009; 8: 545-559
  • 9 Freedman MS, Selchen D, Arnold DL et al. Treatment Optimization in MS: Canadian MS Working Group Updated Recommendations. Can J Neurol Sci 2013; 40: 307-323
  • 10 Leray E, Yaouanq J, Le Page E et al. Evidence for a two-stage disability progression in multiple sclerosis. Brain 2010; 133: 1900-1913
  • 11 Weinshenker BG, Bass B, Rice GP et al. The natural history of multiple sclerosis: a geographically based study. 2. Predictive value of the early clinical course. Brain 1989; 112: 1419-1428
  • 12 Scalfari A, Neuhaus A, Degenhardt A et al. The natural history of multiple sclerosis: a geographically based study 10: relapses and long-term disability. Brain 2010; 133: 1914-1929
  • 13 Tremlett H, Yousefi M, Devonshire V et al. Impact of multiple sclerosis relapses on progression diminishes with time. Neurology 2009; 73: 1616-1623
  • 14 Hirst C, Ingram G, Pearson O et al. Contribution of relapses to disability in multiple sclerosis. J Neurol 2008; 255: 280-287
  • 15 Lublin FD, Baier M, Cutter G. Effect of relapses on development of residual deficit in multiple sclerosis. Neurology 2003; 61: 1528-1532
  • 16 Sormani MP, Li DK, Bruzzi P et al. Combined MRI lesions and relapses as a surrogate for disability in multiple sclerosis. Neurology 2011; 77: 1684-1690
  • 17 Confavreux C, Vukusic S, Moreau T et al. Relapses and progression of disability in multiple sclerosis. N Engl J Med 2000; 343: 1430-1438
  • 18 Goldman MD, Motl RW, Rudick RA. Possible clinical outcome measures for clinical trials in patients with multiple sclerosis. Ther Adv Neurol Disord 2010; 3: 229-239
  • 19 Ontaneda D, LaRocca N, Coetzee T et al. Revisiting the multiple sclerosis functional composite: proceedings from the National Multiple Sclerosis Society (NMSS) Task Force on Clinical Disability Measures. Mult Scler 2012; 18: 1074-1080
  • 20 Balcer LJ, Frohman EM. Evaluating loss of visual function in multiple sclerosis as measured by low-contrast letter acuity. Neurology 2010; 74 (Suppl. 03) S16-23
  • 21 Baier ML, Cutter GR, Rudick RA et al. Low-contrast letter acuity testing captures visual dysfunction in patients with multiple sclerosis. Neurology 2005; 64: 992-995
  • 22 Drake AS, Weinstock-Guttman B, Morrow SA et al. Psychometrics and normative data for the Multiple Sclerosis Functional Composite: replacing the PASAT with the Symbol Digit Modalities Test. Mult Scler 2010; 16: 228-237
  • 23 Rudick RA, Polman CH, Cohen JA et al. Assessing disability progression with the Multiple Sclerosis Functional Composite. Mult Scler 2009; 15: 984-997
  • 24 Morrow SA, Drake A, Zivadinov R et al. Predicting loss of employment over three years in multiple sclerosis: clinically meaningful cognitive decline. Clin Neuropsychol 2010; 24: 1131-1145
  • 25 Weiner HL, Guttmann CR, Khoury SJ et al. Serial magnetic resonance imaging in multiple sclerosis: correlation with attacks, disability, and disease stage. J Neuroimmunol 2000; 104: 164-173
  • 26 Brex PA, Ciccarelli O, O’Riordan JI et al. A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med 2002; 346: 158-164
  • 27 Prosperini L, Gallo V, Petsas N et al. One-year MRI scan predicts clinical response to interferon beta in multiple sclerosis. Eur J Neurol 2009; 16: 1202-1209
  • 28 Rudick RA, Lee JC, Simon J et al. Defining interferon beta response status in multiple sclerosis patients. Ann Neurol 2004; 56: 548-555
  • 29 Rio J, Rovira A, Tintore M et al. Relationship between MRI lesion activity and response to IFN-beta in relapsing-remitting multiple sclerosis patients. Mult Scler 2008; 14: 479-484
  • 30 Pozzilli C, Prosperini L, Sbardella E et al. Post-marketing survey on clinical response to interferon beta in relapsing multiple sclerosis: the Roman experience. Neurol Sci 2005; 26 (Suppl. 04) S174-178
  • 31 Fisniku LK, Brex PA, Altmann DR et al. Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis. Brain 2008; 131: 808-817
  • 32 Rio J, Castillo J, Rovira A et al. Measures in the first year of therapy predict the response to interferon beta in MS. Mult Scler 2009; 15: 848-853
  • 33 Lovblad KO, Anzalone N, Dorfler A et al. MR imaging in multiple sclerosis: review and recommendations for current practice. AJNR Am J Neuroradiol 2010; 31: 983-989
  • 34 Sailer M, Fazekas F, Gass A et al. Zerebrale und spinale MRT-Untersuchung bei Patienten mit klinisch isoliertem Syndrom oder gesicherter Multipler Sklerose. Rofo 2008; 180: 994-1001
  • 35 Simon JH, Li D, Traboulsee A et al. Standardized MR imaging protocol for multiple sclerosis: Consortium of MS Centers consensus guidelines. AJNR Am J Neuroradiol 2006; 27: 455-461
  • 36 Yong VW. Differential mechanisms of action of interferon-beta and glatiramer aetate in MS. Neurology 2002; 59: 802-808
  • 37 Molyneux PD, Miller DH, Filippi M et al. Visual analysis of serial T2-weighted MRI in multiple sclerosis: intra- and interobserver reproducibility. Neuroradiology 1999; 41: 882-888
  • 38 Debouverie M, Pittion-Vouyovitch S, Brissart H et al. Physical dimension of fatigue correlated with disability change over time in patients with multiple sclerosis. J Neurol 2008; 255: 633-636
  • 39 Penner IK, Raselli C, Stocklin M et al. The Fatigue Scale for Motor and Cognitive Functions (FSMC): validation of a new instrument to assess multiple sclerosis-related fatigue. Mult Scler 2009; 15: 1509-1517
  • 40 Elbers RG, Rietberg MB, van Wegen EE et al. Self-report fatigue questionnaires in multiple sclerosis, Parkinson’s disease and stroke: a systematic review of measurement properties. Qual Life Res 2012; 21: 925-944
  • 41 Herrmann-Lingen C, Buss U, Snaith RP. HADS-D – Hospital Anxiety and Depression Scale – Deutsche Version: Ein Fragebogen zur Erfassung von Angst und Depressivität in der somatischen Medizin. Bern: Huber; 1995
  • 42 Hobart J, Lamping D, Fitzpatrick R et al. The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. Brain 2001; 124: 962-973
  • 43 McGuigan C, Hutchinson M. The multiple sclerosis impact scale (MSIS-29) is a reliable and sensitive measure. J Neurol Neurosurg Psychiatry 2004; 75: 266-269
  • 44 Costelloe L, O’Rourke K, Kearney H et al. The patient knows best: significant change in the physical component of the Multiple Sclerosis Impact Scale (MSIS-29 physical). J Neurol Neurosurg Psychiatry 2007; 78: 841-844
  • 45 Kruger K, Wollenhaupt J, Albrecht K et al. [German 2012 guidelines for the sequential medical treatment of rheumatoid arthritis. Adapted EULAR recommendations and updated treatment algorithm]. Z Rheumatol 2012; 71: 592-603