Therapieziele und Therapiemanagement bei schubförmigremittierender Multipler Sklerose

R. Gold; A. Gass; M. Haupts; R. Linker; C. Lukas; M. Mäurer; M. Stangel; B. Tackenberg; T. Ziemssen; H. Wiendl; H.-P. Hartung; für die Teilnehmer eines Expertenmeetings

doi:10.1055/s-0038-1627648

Nervenheilkunde, Table of Contents

Nervenheilkunde 2015; 34(11): 915-923
DOI: 10.1055/s-0038-1627648

Übersichtsartikel

Schattauer GmbH

Therapieziele und Therapiemanagement bei schubförmigremittierender Multipler Sklerose

Therapy and management of relapsing-remitting multiple sclerosis

R. Gold

¹Neurologische Klinik der Ruhr-Universität, St. Josef Hospital, Bochum

,

A. Gass

²Neurologische Universitätsklinik der Universitätsmedizin, Mannheim

,

M. Haupts

³Augustahospital, Anholt

,

R. Linker

⁴Neurologische Klinik des Universitätsklinikums, Erlangen

,

C. Lukas

⁵Institut für Diagnostische und Interventionelle Radiologie und Nuklearmedizin, St. Josef und St. Elisabeth Hospital, Bochum

,

M. Mäurer

⁶Caritas Krankenhaus, Bad Mergentheim

,

M. Stangel

⁷Klinik für Neurologie, Medizinische Hochschule Hannover

,

B. Tackenberg

⁸Philipps-Universität und Universitätsklinikum Gießen und Marburg GmbH, Marburg

,

T. Ziemssen

⁹Zentrum für Klinische Neurowissenschaften / Multiple Sklerose Zentrum, Universitätsklinikum Carl Gustav Carus Dresden an der Technischen Universität, Dresden

,

H. Wiendl

¹⁰Neurologische Klinik des Universitätsklinikums, Münster

,

H.-P. Hartung

¹¹Neurologischen Klinik der Heinrich-Heine-Universität, Universitätsklinikum, Düsseldorf

,

für die Teilnehmer eines Expertenmeetings

› Author Affiliations

Abstract

Zusammenfassung

Unsere Expertengruppe hatte im Jahr 2012 Therapieziele der immunmodulatorischen Behandlung der schubförmig-remittierenden MS (RRMS) formuliert: Übergeordnetes Therapieziel ist die bestmögliche Krankheitskontrolle, messbar an der Freiheit von klinisch und kernspintomografisch nachweisbarer Krankheitsaktivität. Die Therapie sollte daher früh mit einem möglichst wirksamen Medikament begonnen und bei unzureichender Effektivität rechtzeitig optimiert werden. Dementsprechend sind individuell optimierte Therapieentscheidungen auf der Basis der sensitiven Detektion von Krankheitsaktivität essenziell. In einem zweiten Workshop 2014 erörterte die Expertengruppe Kriterien und Prozeduren für das Monitoring und Management von RRMSPatienten. Schubereignisse sind durch sorgfältige Anamnese bei regelmäßigen neurologischen Untersuchungen zu erfassen. Veränderungen des Behinderungsstatus sollten mit gut quantifizierbaren Parametern mindestens einmal jährlich, besser halbjährlich erhoben werden. Dabei sind relevante funktionelle Systeme, Kognition, Fatigue und Depression einzubeziehen. MRT-Befunde sind zunehmend als frühe Indikatoren für unzureichende Therapiewirkung relevant. Voraussetzung sind technisch konsistente, standardisierte MRT-Aufnahmen. Derzeit steht die Detektion neuer und vergrößerter Läsionen im Vordergrund. Die Hirnatrophie als zusätzlicher Parameter ist unter Routinebedingungen noch nicht verlässlich messbar. Patientenzentrierte Faktoren wie individuelle Lebensqualität, persönliche Ziele und spezifische Lebensführung sollten in Verlaufsbeobachtung und Therapieentscheidung maßgeblich einfließen. Standardisierte Patientenmanagementsysteme können die Konsistenz und Qualität der langfristigen Betreuung verbessern. Auch von intersektoral-interdisziplinären Netzwerken mit MS-Zentren als Schaltstellen ist eine Verbesserung der Versorgungsqualität zu erwarten.

Summary

In 2012, our expert group formulated treatment goals for the immunomodulatory therapy of relapsing-remitting MS (RRMS): the primary aim is the best achievable control of disease activity, as measured by the absence of clinical and MRI-detectable disease activity. Treatment of RRMS should therefore be initiated early with an effective medication. Prompt adaptation is required in the case of insufficient disease suppression. Accordingly, the sensitive clinical and MRI-based detection of disease activity is essential for individually optimized treatment decisions. In a second workshop in 2014, the expert group discussed criteria and procedures for the monitoring and management of RRMS patients. Relapse episodes should be detected by carefully taking patient history at regular neurologic visits. Changes in the disability status should be monitored clinically and supplemented by sensitive quantitative tools at least annually, or better in 6 months intervals. Monitoring should cover relevant functional systems, neurocognition, fatigue, and depression. MRI becomes increasingly important in providing early evidence of disease activity. It remains currently focused on the detection of new or enlarging lesions. Global brain atrophy cannot be reliably quantified in routine care to date. Patient- reported outcomes such as quality of life, personal goals and factors affecting life-style requirements should be represented in monitoring and treatment decisions. Standardized patient management systems can improve the consistency and benefit of long-term care. Cooperation in multi-sector and interdisciplinary networks with MS centers working as the hubs will also likely contribute to the quality of care.

Schlüsselwörter

Schubförmig-remittierende Multiple Sklerose - immunmodulatorische Therapie - Krankheitsaktivität - Therapieziele

Keywords

Relapsing remitting multiple sclerosis - immunomodulatory therapy - disease activity - treatment goals

Full Text

References

Literatur
1 Ellwardt E, Zipp F. Molecular mechanisms linking neuroinflammation and neurodegeneration in MS. Exp Neurol 2014; 262: 8-17.
2 Durrenberger PF, Fernando FS, Kashefi SN, Bonnert TP, Seilhean D, Nait-Oumesmar B, Schmitt A, Gebicke-Haerter PJ, Falkai P, Grünblatt E, Palkovits M, Arzberger T, Kretzschmar H, Dexter DT, Reynolds R. Common mechanisms in neurodegeneration and neuroinflammation: a BrainNet Europe gene expression microarray study. J Neural Transm. 2014 Aug 13. Epub ahead of print.
3 Scalfari A, Neuhaus A, Degenhardt A, Rice GP, Muraro PA, Daumer M, Ebers GC. The natural history of multiple sclerosis: a geographically based study 10: relapses and long-term disability. Brain 2010; 133: 1914-1929.
4 Fisniku LK, Brex PA, Altmann DR, Miszkiel KA, Benton CE, Lanyon R, Thompson AJ, Miller DH. Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis. Brain 2008; 131: 808-817.
5 Gold R, Hartung H-P, Stangel M, Wiendl H, Zipp F. Therapieziele von Basisund Eskalationstherapien zur Behandlung der schubförmigremittierenden Multiplen Sklerose. Akt Neurol 2012; 39: 342-350.
6 Giovannoni G, Rhoades RW. Individualizing treatment goals and interventions for people with MS. Curr Opin Neurol 2012; 25 Suppl: S20-S27.
7 Fox EJ, Rhoades RW. New treatments and treatment goals for patients with relapsing-remitting multiple sclerosis. Curr Opin Neurol 2012; 25 Suppl: S11-S19.
8 Bevan CJ, Cree BA. Disease activity free status: a new end point for a new era in multiple sclerosis clinical research?. JAMA Neurol 2014; 71: 269-270.
9 Havrdova E, Galetta S, Stefoski D, Comi G. Freedom from disease activity in multiple sclerosis. Neurology 2010; 74: S3-S7.
10 Stangel M, Penner IK, Kallmann BA, Lukas C, Kieseier BC. Towards the implementation of ‘no evidence of disease activity’ in multiple sclerosis treatment: the multiple sclerosis decision model. Ther Adv Neurol Disord 2015; 08: 3-13.
11 Kappos L, Radue EW, Freedman MS. et al. Inclusion of brain volume loss in a revised measure of multiple sclerosis disease-activity freedom: the effect of fingolimod. ECTRIMS/ACTRIMS 2014; Abstract FC1.5.
12 Ytterberg C, Johansson S, Andersson M, Widén LHolmqvist, von Koch L. Variations in functioning and disability in multiple sclerosis. A two-year prospective study. J Neurol 2008; 255: 967-973.
13 Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, Fujihara K, Havrdova E, Hutchinson M, Kappos L, Lublin FD, Montalban X, O’Connor P, Sandberg-Wollheim M, Thompson AJ, Waubant E, Weinshenker B, Wolinsky JS. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 2011; 69: 292-302.
14 Lavery AM, Verhey LH, Waldman AT. Outcome measures in relapsing-remitting multiple sclerosis: capturing disability and disease progression in clinical trials. Mult Scler Int 2014; 2014: 262350.
15 Cohen JA, Reingold SC, Polman CH, Wolinsky JS. International Advisory Committee on Clinical Trials in multiple Sclerosis. Disability outcome measures in multiple sclerosis clinical trials: current status and future prospects. Lancet Neurol 2012; 11: 467-476.
16 Langdon DW, Amato MP, Boringa J, Brochet B, Foley F, Fredrikson S, Hämäläinen P, Hartung HP, Krupp L, Penner IK, Reder AT, Benedict RH. Recommendations for a Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). Mult Scler 2012; 18: 891-898.
17 Heesen C, Schulz KH, Fiehler J, Von der Mark U, Otte C, Jung R, Poettgen J, Krieger T, Gold SM. Correlates of cognitive dysfunction in multiple sclerosis. Brain Behav Immun 2010; 24: 1148-1155.
18 Gunzler DD, Perzynski A, Morris N, Bermel R, Lewis S, Miller D. Disentangling multiple sclerosis and depression: an adjusted depression screening score forpatient-centered care. J Behav Med 2015; 38: 237-50.
19 Sundgren M, Maurex L, Wahlin Å, Piehl F, Brismar T. Cognitive impairment has a strong relation to nonsomatic symptoms of depression in relapsing-remitting multiple sclerosis. Arch Clin Neuropsychol 2013; 28: 144-155.
20 Stangel M, Penner IK, Kallmann BA, Lukas C, Kieseier BC, Gold R. Multiple Sclerosis Decision Model (MSDM): Entwicklung eines Mehrfaktorenmodells zur Beurteilung des Therapie-und Krankheitsverlaufs bei schubförmiger Multipler Sklerose. Akt Neurol 2013; 40: 486-493.
21 Gajofatto A, Calabrese M, Benedetti MD, Monaco S. Clinical, MRI, and CSF markers of disability progression in multiple sclerosis. Dis Markers 2013; 35: 687-699.
22 Prosperini L, Gallo V, Petsas N, Borriello G, Pozzilli C. One-year MRI scan predicts clinical response to interferon beta in multiple sclerosis. Eur J Neurol 2009; 16: 1202-1209.
23 Stevenson VL, Ingle GT, Miller DH, Thompson AJ. Magnetic resonance imaging predictors of disability in primary progressive multiple sclerosis: a 5-year study. Mult Scler 2004; 10: 398-401.
24 Sormani MP, Rio J, Tintorè M, Signori A, Li D, Cornelisse P, Stubinski B, Stromillo Ml, Montalban X, De Stefano N. Scoring treatment response in patients with relapsing multiple sclerosis. Mult Scler 2013; 19: 605-612.
25 Wattjes MP, Barkhof F. Diagnosis of natalizumabassociated progressive multifocal leukoencephalopathy using MRI. Curr Opin Neurol 2014; 27: 260-270.
26 Eisele P, Szabo K, Griebe M, Rossmanith C, Förster A, Hennerici M, Gass A. Reduced diffusion in a subset of acute MS lesions: a serial multiparametric MRI study. AJNR Am J Neuroradiol 2012; 33: 1369-1373.
27 Rovira A, Auger C, Alonso J. Magnetic resonance monitoring of lesion evolution in multiple sclerosis. Ther Adv Neurol Disord 2013; 06: 298-310.
28 Filippi M, Preziosa P, Rocca MA. Magnetic resonance outcome measures in multiple sclerosis trials: time to rethink?. Curr Opin Neurol 2014; 27: 290-299.
29 De Stefano N, Airas L, Grigoriadis N, Mattle HP, O’Riordan J, Oreja-Guevara C, Sellebjerg F, Stankoff B, Walczak A, Wiendl H, Kieseier BC. Clinical relevance of brain volume measures in multiple sclerosis. CNS Drugs 2014; 28 (02) 147-156.
30 Calabrese M, Gajofatto A, Benedetti MD. Therapeutic strategies for relapsing-remitting multiple sclerosis: a special focus on reduction of grey matter damage as measured by brain atrophy. Expert Rev Neurother 2014; 14 (12) 1417-1428.
31 Amato MP, Razzolini L, Goretti B, Stromillo ML, Rossi F, Giorgio A, Hakiki B, Giannini M, Pastò L, Portaccio E, De Stefano N. Cognitive reserve and cortical atrophy in multiple sclerosis: a longitudinal study. Neurology 2013; 80: 1728-1733.
32 Lukas C, Knol DL, Sombekke MH, Bellenberg B, Hahn HK, Popescu V, Weier K, Radue EW, Gass A, Kappos L, Naegelin Y, Uitdehaag BM, Geurts JJ, Barkhof F, Vrenken H. Cervical spinal cord volume loss is related to clinical disability progression in multiple sclerosis. J Neurol Neurosurg Psychiatry 2015; 86: 410-418.
33 Jacobsen C, Hagemeier J, Myhr KM, Nyland H, Lode K, Bergsland N, Ramasamy DP, Dalaker TO, Larsen JP, Farbu E, Zivadinov R. Brain atrophy and disability progression in multiple sclerosis patients: a 10-year follow-up study. J Neurol Neurosurg Psychiatry 2014; 85: 1109-1115.
34 Duning T, Kloska S, Steinsträter O, Kugel H, Heindel W, Knecht S. Dehydration confounds the assessment of brain atrophy. Neurology 2005; 64: 548-550.
35 Pöllmann W, Busch C, Voltz R. [Quality of life in multiple sclerosis. Measures, relevance, problems, and perspectives]. Nervenarzt 2005; 76: 154-169.
36 Fegg MJ, Kramer M, L’hoste S, Borasio GD. The Schedule for Meaning in Life Evaluation (SMiLE): validation of a new instrument for meaning-in-life research. J Pain Symptom Manage 2008; 35: 356-364.
37 KKNMS Patientenaufklärungsbögen. www.kompetenznetz-multiplesklerose.de
38 Tan H, Cai Q, Agarwal S, Stephenson JJ, Kamat S. Impact of adherence to disease-modifying therapies on clinical and economic outcomes among patients with multiple sclerosis. Adv Ther 2011; 28: 51-61.
39 Treadaway K, Cutter G, Salter A. et al. Factors that influence adherence with disease-modifying therapy in MS. J Neurol 2009; 256: 568-576.
40 Meletiche D, Dickson KozmaM. et al. Association between adherence with multiple sclerosis disease modifying therapy and severe relapses using three measures of medication adherence. J Neurol 2008; 255 (Suppl. 02) 717.
41 Al-Sabbagh A, Bennet R, Kozma C, Dickson M, Meletiche D. Medication gaps in disease modifying therapy for multiple sclerosis are associated with an increased risk of relapse: findings from a national managed care database. J Neurol 2008; 255 (Suppl. 02) S79.
42 Uitdehaag B, Constantinescu C, Cornelisse P. et al. Impact of exposure to interferon beta-1a on outcomes in patients with relapsing-remitting multiple sclerosis: exploratory analyses from the PRISMS long-term follow-up study. Ther Adv Neurol Disord 2011; 04: 3-14.
43 Devonshire V, Pfohl D, Perrin ARoss, Poplear L. Adherence to Disease Modifying Therapy: Recognizing the Barriers and Offering Solutions. Ridgewood, NJ: Delaware Media Group; 2007
44 Martinelli V, Ghezzi A, Montanari E, Radaelli M, Comi G, Bossa R. Disclosing the diagnosis of multiple sclerosis: the Profile Project. J Neurol 2012; 259: 2605-2610.
45 Lugaresi A, Ziemssen T, Oreja-Guevara C, Thomas D, Verdun E. Improving patient-physician dialog: commentary on the results of the MS Choices survey. Patient Prefer Adherence 2012; 06: 143-152.
46 Wilson L, Loucks A, Bui C, Gipson G, Zhong L, Schwartzburg A, Crabtree E, Goodin D, Waubant E, McCulloch C. Patient centered decision making: use of conjoint analysis to determine risk-benefit trade-offs for preference sensitive treatment choices. J Neurol Sci 2014; 344: 80-7.
47 Crawford A, Jewell S, Mara H, McCatty L, Pelfrey R. Managing treatment fatigue in patients with multiple sclerosis on long-term therapy: the role of multiple sclerosis nurses. Patient Prefer Adherence 2014; 08: 1093-1099.
48 Ziemssen T, Kempcke R, Eulitz M, Großmann L, Suhrbier A, Thomas K, Schultheiss T. Multiple sclerosis documentation system (MSDS): moving from documentation tomanagement of MS patients. J Neural Transm 2013; 120 Suppl (Suppl. 01) S61-S66.
49 Schultheiss T, Kempcke R, Kratzsch F, Eulitz M, Pette M, Reichmann H, Ziemssen T. [Multiple sclerosis management system 3D. Moving from documentation towards management of patients]. Nervenarzt 2012; 83: 450-457.
50 https://neurotransdata.com
51 www.kompetenznetz-multiplesklerose.de/de/ak tuelle-studien/regims
52 Sozialgesetzbuch V. § 116b.