The importance of collecting structured clinical information on multiple sclerosis
Background:
Randomized controlled trials (RCTs) are the ‘gold standard’ in the generation of drug efficacy and safety evidence. However, enrolment criteria, timelines and atypical comparators of RCTs limit their relevance to standard clinical practice.
Discussion:
Real-world data (RWD) provide longitudinal information on the comparative effectiveness and tolerability of drugs, as well as their impact on resource use, medical costs, and pharmacoeconomic and patient-reported outcomes. This is particularly important in multiple sclerosis (MS), where economic treatment benefits of long-term disability reduction are a cornerstone of payer drug approvals – these are typically not examined in the RCT itself but modelled using real-world datasets. Importantly, surrogate markers used in RCTs to predict the prevention of long-term disability progression can only truly be assessed through RWD methodologies.
Summary:
We discuss the differences between RCTs and RWD studies, describe how RWD complements the evidence base from RCTs in MS, summarize the different methods of RWD collection, and explain the importance of structuring data analysis to avoid bias. Guidance on performing and identifying high-quality real-world evidence studies is also provided.
Keywords:
Multiple sclerosis, Real-world evidence, Real-world data, Randomised controlled trials, Registries, Pharmacoeconomics
Autoři:
Tjalf Ziemssen 1*; Jan Hillert 2; Helmut Butzkueven 3
Působiště autorů:
Center of Clinical Neuroscience, Department of Neurology, MS Center Dresden, Center of Clinical Neuroscience, University Hospital Carl Gustav Carus, Dresden University of Technology, Fetscherstr. 74, 01 07 Dresden, Germany.
1; Department of Clinical Neuroscience and Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden.
2; Department of Neurology, Royal Melbourne Hospital, Victoria, Australia.
3
Vyšlo v časopise:
BMC Medicine 2016, 14:81
Kategorie:
Opinion
prolekare.web.journal.doi_sk:
https://doi.org/10.1186/s12916-016-0627-1
© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
The electronic version of this article is the complete one and can be found online at: https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-016-0627-1
Souhrn
Background:
Randomized controlled trials (RCTs) are the ‘gold standard’ in the generation of drug efficacy and safety evidence. However, enrolment criteria, timelines and atypical comparators of RCTs limit their relevance to standard clinical practice.
Discussion:
Real-world data (RWD) provide longitudinal information on the comparative effectiveness and tolerability of drugs, as well as their impact on resource use, medical costs, and pharmacoeconomic and patient-reported outcomes. This is particularly important in multiple sclerosis (MS), where economic treatment benefits of long-term disability reduction are a cornerstone of payer drug approvals – these are typically not examined in the RCT itself but modelled using real-world datasets. Importantly, surrogate markers used in RCTs to predict the prevention of long-term disability progression can only truly be assessed through RWD methodologies.
Summary:
We discuss the differences between RCTs and RWD studies, describe how RWD complements the evidence base from RCTs in MS, summarize the different methods of RWD collection, and explain the importance of structuring data analysis to avoid bias. Guidance on performing and identifying high-quality real-world evidence studies is also provided.
Keywords:
Multiple sclerosis, Real-world evidence, Real-world data, Randomised controlled trials, Registries, Pharmacoeconomics
Zdroje
1. Nallamothu BK, Hayward RA, Bates ER. Beyond the randomized clinical trial: the role of effectiveness studies in evaluating cardiovascular therapies. Circulation. 2008;118:1294–303.
2. Milnes F, Bergvall N, Olson M, Capkun-Niggli G, Bonzani I, Makin C. Use of real-world data to assess outcomes in patients with multiple sclerosis in a real-life clinical setting. 10th Annual Meeting of Health Technology Assessment international (HTAi). Seoul: Poster P1082; 2013.
3. Association of the British Pharmaceutical Industry. Demonstrating value with real world data: a practical guide. 2011. http://www.abpi.org.uk/our-work/library/guidelines/Pages/real-world-data.aspx. Accessed 25 February 2016.
4. Garrison Jr LP, Neumann PJ, Erickson P, Marshall D, Mullins CD. Using realworld data for coverage and payment decisions: the ISPOR Real-World Data Task Force report. Value Health. 2007;10:326–35.
5. Ziemssen T, Kempcke R, Eulitz M, Grossmann L, Suhrbier A, Thomas K, Schultheiss T. Multiple sclerosis documentation system (MSDS): moving from documentation to management of MS patients. J Neural Transm (Vienna). 2013;120 Suppl 1:S61–6.
6. Agashivala N, Wu N, Abouzaid S, Wu Y, Kim E, Boulanger L, Brandes DW. Compliance to fingolimod and other disease modifying treatments in multiple sclerosis patients, a retrospective cohort study. BMC Neurol. 2013;13:138.
7. Bergvall N, Lahoz R, Reynolds T, Korn JR. Healthcare resource use and relapses with fingolimod versus natalizumab for treating multiple sclerosis: a retrospective US claims database analysis. Curr Med Res Opin. 2014;30:1461–71.
8. Bergvall N, Petrilla AA, Karkare SU, Lahoz R, Agashivala N, Pradhan A, Capkun G, Makin C, McGuiness CB, Korn JR. Persistence with and adherence to fingolimod compared with other disease-modifying therapies for the treatment of multiple sclerosis: a retrospective US claims database analysis. J Med Econ. 2014;17:696–707.
9. Butzkueven H, Kappos L, Pellegrini F, Trojano M, Wiendl H, Patel RN, Zhang A, Hotermans C, Belachew S; TYSABRI Observational Program (TOP) Investigators. Efficacy and safety of natalizumab in multiple sclerosis: interim observational programme results. J Neurol Neurosurg Psychiatry. 2014;85:1190–7.
10. A dose-blind, multicenter, extension study to determine the long-term safety and efficacy of two doses of BG00012 monotherapy in subjects with relapsing-remitting multiple sclerosis. ClinicalTrials.gov Identifier: NCT00835770. 2015. https://clinicaltrials.gov/show/NCT00835770. Accessed 25 February 2016.
11. Confavreux C, Vukusic S, Moreau T, Adeleine P. Relapses and progression of disability in multiple sclerosis. N Engl J Med. 2000;343:1430–8.
12. Davis MF, Sriram S, Bush WS, Denny JC, Haines JL. Automated extraction of clinical traits of multiple sclerosis in electronic medical records. J Am Med Inform Assoc. 2013;20:e334–40.
13. Jokubaitis VG, Li V, Kalincik T, Izquierdo G, Hodgkinson S, Alroughani R, Lechner-Scott J, Lugaresi A, Duquette P, Girard M, et al. Fingolimod after natalizumab and the risk of short-term relapse. Neurology. 2014;82:1204–11.
14. Kalincik T, Horakova D, Spelman T, Jokubaitis V, Trojano M, Lugaresi A, Izquierdo G, Rozsa C, Grammond P, Alroughani R, et al. Switch to natalizumab versus fingolimod in active relapsing-remitting multiple sclerosis. Ann Neurol. 2015;77:425–35.
15. Kalincik T, Jokubaitis V, Izquierdo G, Duquette P, Girard M, Grammond P, Lugaresi A, Oreja-Guevara C, Bergamaschi R, Hupperts R, et al. Comparative effectiveness of glatiramer acetate and interferon beta formulations in relapsing-remitting multiple sclerosis. Mult Scler. 2015;21:1159–71.
16. Nordin N, Hillert J, Piehl F, Svenningsson A, Lycke J, Fagius J, Walentin F, Martin C, Nilsson P, Feltelius N, et al. The "Immunomodulation and Multiple Sclerosis Epidemiology" (IMSE II) study; A Swedish nationwide pharmacoepidemiological and genetic study focused on long-term safety and efficacy
of fingolimod (Gilenya®), 29th Congress of the European Committee for Research and Treatment in Multiple Sclerosis (ECTRIMS). Copenhagen: Poster; 2013. p. 975.
17. He A, Spelman T, Jokubaitis V, Havrdova E, Horakova D, Trojano M, Lugaresi A, Izquierdo G, Grammond P, Duquette P, et al. Comparison of switch to fingolimod or interferon beta/glatiramer acetate in active multiple sclerosis. JAMA Neurol. 2015;72:405–13.
18. North American Research Committee on Multiple Sclerosis.. Publications validating NARCOMS data and instruments. 2016. http://narcoms.org/publications. Accessed 26 February 2016.
19. Westerlind H, Ramanujam R, Uvehag D, Kuja-Halkola R, Boman M, Bottai M, Lichtenstein P, Hillert J. Modest familial risks for multiple sclerosis: a registrybased study of the population of Sweden. Brain. 2014;137:770–78.
20. Ziemssen T, Kern R, Cornelissen C. The PANGAEA study design – a prospective, multicenter, non-interventional, long-term study on fingolimod for the treatment of multiple sclerosis in daily practice. BMC Neurol. 2015;15:93.
21. Willke RJ, Mullins CD. Ten commandments" for conducting comparative effectiveness research using "real-world data. J Managed Care Pharm. 2011;17:S10–5.
22. Normand SL, Sykora K, Li P, Mamdani M, Rochon PA, Anderson GM. Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding. BMJ. 2005;330:1021–3.
23. Austin PC. An Introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46:399–424.
24. Cepeda MS, Boston R, Farrar JT, Strom BL. Comparison of logistic regression versus propensity score when the number of events is low and there are multiple confounders. Am J Epidemiol. 2003;158:280–7.
25. Möller HJ. Effectiveness studies: advantages and disadvantages. Dialogues Clin Neurosci. 2011;13:199–207.
26. CONSORT. The CONSORT Statement. 2010. http://www.consort-statement.org/. Accessed 12 April 2016.
27. STROBE. Checklist for cohort studies. 2007. href="http://www.strobe-statement.org/index.php?id=available-checklists">http://www.strobe-statement.org/index.php?id=available-checklists. Accessed 12 April 2016.
28. Dreyer NA, Velentgas P, Westrich K, Dubois R. The GRACE checklist for rating the quality of observational studies of comparative effectiveness: a tale of hope and caution. J Manag Care Spec Pharm. 2014;20:301–8.
29. Hurwitz BJ. Analysis of current multiple sclerosis registries. Neurology. 2011;76:S7–13.
30. Hurwitz BJ. Registry studies of long-term multiple sclerosis outcomes: description of key registries. Neurology. 2011;76:S3–6.
31. Kremenchutzky M, Rice GP, Baskerville J, Wingerchuk DM, Ebers GC. The natural history of multiple sclerosis: a geographically based study 9: observations on the progressive phase of the disease. Brain. 2006;129:584–94.
32. Weinstock-Guttman B, Jacobs LD, Brownscheidle CM, Baier M, Rea DF, Apatoff BR, Blitz KM, Coyle PK, Frontera AT, Goodman AD, et al. Multiple sclerosis characteristics in African American patients in the New York State Multiple Sclerosis Consortium. Mult Scler. 2003;9:293–8.
33. Butzkueven H, Chapman J, Cristiano E, Grand'Maison F, Hoffmann M, Izquierdo G, Jolley D, Kappos L, Leist T, Pohlau D, et al. MSBase: an international, online registry and platform for collaborative outcomes research in multiple sclerosis. Mult Scler. 2006;12:769–74.
34. Jokubaitis VG, Spelman T, Kalincik T, Izquierdo G, Grand'Maison F, Duquette P, Girard M, Lugaresi A, Grammond P, Hupperts R, et al. Predictors of disability worsening in clinically isolated syndrome. Ann Clin Transl Neurol. 2015;2:479–91.
35. Spelman T, Kalincik T, Zhang A, Pellegrini F, Wiendl H, Kappos L, Tsvetkova L, Belachew S, Hyde R, Verheul F, et al. Comparative efficacy of switching to natalizumab in active multiple sclerosis. Ann Clin Transl Neurol. 2015;2:373–87.
36. Kappos L, Radue EW, Comi G, Montalban X, Butzkueven H, Wiendl H, Giovannoni G, Hartung HP, Derfuss T, Naegelin Y, et al. Switching from natalizumab to fingolimod: a randomized, placebo-controlled study in RRMS. Neurology. 2015;85:29–39.
37. Frisell T, Forsberg L, Nordin N, Kiesel C, Alfredsson L, Askling J, Hillert J, Olsson T, Piehl F. Comparative analysis of first-year fingolimod and natalizumab drug discontinuation among Swedish patients with multiple sclerosis. Mult Scler. 2016;22:85–93.
38. Hupperts R, Ghazi-Visser L, Martins Silva A, Arvanitis M, Kuusisto H, Marhardt K, Vlaikidis N, Group SS. The STAR Study: a real-world, international, observational study of the safety and tolerability of, and adherence to, serum-free subcutaneous interferon beta-1a in patients with relapsing multiple sclerosis. Clin Ther. 2014;36:1946–57.
39. Ziemssen T, Moser S, Schwartz HJ, Fuchs A, van Lockven T, Cornelissen C. Comparison of efficacy and treatment satisfaction of patients on baseline therapy and fingolimod: results of the interim analysis of two German registry studies PANGAEA and PEARL. American Academy of Neurology (AAN) Annual Meeting, April 26–May 3, 2014, Philadelphia PA; Poster P7.232.
40. Bonafede MM, Johnson BH, Watson C. Health care-resource utilization before and after natalizumab initiation in multiple sclerosis patients in the US. Clinicoecon Outcomes Res. 2013;6:11–20.
41. Fox E, Edwards K, Burch G, Wynn DR, LaGanke C, Crayton H, Hunter SF, Huffman C, Kim E, Pestreich L, et al. Outcomes of switching directly to oral fingolimod from injectable therapies: Results of the randomized, open-label, multicenter, Evaluate Patient OutComes (EPOC) study in relapsing multiple sclerosis. Mult Scler Relat Disord. 2014;3:607–19.
42. Vormfelde SV, Ortler S, Ziemssen T. Multiple Sclerosis Therapy With Disease-Modifying Treatments in Germany: The PEARL (ProspEctive phArmacoeconomic cohoRt evaluation) Noninterventional Study Protocol. JMIR Res Protocol. 2015;5(1), e23.
43. Stephenson JJ, Kern DM, Agarwal SS, Zeidman R, Rajagopalan K, Kamat SA, Foley J. Impact of natalizumab on patient-reported outcomes in multiple sclerosis: a longitudinal study. Health Qual Life Outcomes. 2012;10:155.
44. Flachenecker P, Buckow K, Pugliatti M, Kes VB, Battaglia MA, Boyko A, Confavreux C, Ellenberger D, Eskic D, Ford D, et al. Multiple sclerosis registries in Europe - results of a systematic survey. Mult Scler. 2014;20:1523–32.
45. A collaborative initiative to improve MS research and policy across Europe. Better outcomes with better data. 2014. http://www.emsp.org/wp-content/uploads/2015/06/140930-EUReMS-Report.pdf. Accessed 26 February 2016.
46. Barkhof F, Scheltens P, Frequin ST, Nauta JJ, Tas MW, Valk J, Hommes OR. Relapsing-remitting multiple sclerosis: sequential enhanced MR imaging vs clinical findings in determining disease activity. AJR Am J Roentgenol. 1992;159:1041–7.
47. Giorgio A, Stromillo ML, Bartolozzi ML, Rossi F, Battaglini M, De Leucio A, Guidi L, Maritato P, Portaccio E, Sormani MP, et al. Relevance of hypointense brain MRI lesions for long-term worsening of clinical disability in relapsing multiple sclerosis. Mult Scler. 2014;20:214–9.
48. Sormani MP, Rio J, Tintore M, Signori A, Li D, Cornelisse P, Stubinski B, Stromillo M, Montalban X, De Stefano N. Scoring treatment response in patients with relapsing multiple sclerosis. Mult Scler. 2013;19:605–12.
49. Barkhof F, Calabresi PA, Miller DH, Reingold SC. Imaging outcomes for neuroprotection and repair in multiple sclerosis trials. Nat Rev Neurol. 2009;5:256–66.
50. Simon JH. Brain atrophy in multiple sclerosis: what we know and would like to know. Mult Scler. 2006;12:679–87.
51. Calabrese M, Agosta F, Rinaldi F, Mattisi I, Grossi P, Favaretto A, Atzori M, Bernardi V, Barachino L, Rinaldi L, et al. Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. Arch Neurol. 2009;66:1144–50.
52. Sormani MP, Arnold DL, De Stefano N. Treatment effect on brain atrophy correlates with treatment effect on disability in multiple sclerosis. Ann Neurol. 2014;75:43–9.
53. Prinster A, Quarantelli M, Lanzillo R, Orefice G, Vacca G, Carotenuto B, Alfano B, Brunetti A, Morra VB, Salvatore M. A voxel-based morphometry study of disease severity correlates in relapsing– remitting multiple sclerosis. Mult Scler. 2010;16:45–54.
54. Zivadinov R, Bakshi R. Central nervous system atrophy and clinical status in multiple sclerosis. J Neuroimaging. 2004;14:27S–35S.
55. Kern R, Haase R, Eisele JC, Thomas K, Ziemssen T. Designing an Electronic Patient Management System for Multiple Sclerosis: Building a Next Generation Multiple Sclerosis Documentation System. Interact J Med Res. 2016;5(1), e2.
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