559866
research-article2015
MSJ0010.1177/1352458514559866Multiple Sclerosis JournalO Ciccarelli and J Chataway
O Ciccarelli and J Chataway
We can compare the relative efficacy of multiple sclerosis medications by examining the results of independent clinical trials: No
Multiple Sclerosis Journal 2015, Vol. 21(1) 37–38 DOI: 10.1177/ 1352458514559866 © The Author(s), 2015. Reprints and permissions: http://www.sagepub.co.uk/ journalsPermissions.nav
Olga Ciccarelli and Jeremy Chataway Date received: 22 October 2014; accepted: 22 October 2014
An increasing number of disease-modifying drugs (DMD) are now licensed to reduce disease activity in patients with relapsing–remitting (RRMS). Logical and frequent questions posed by patients to their clinician are firstly, how well do they work; and secondly, how they compare one to another? The neurologist will usually answer this question by comparing the reduction in annualised relapse rate (ARR) and the effect on new magnetic resonance imaging (MRI) lesions, as reported in the pivotal trials for each compound. We argue that this approach is likely to be approximate and inaccurate, by considering this under the key headings (detailed below) of: cohort characteristics, outcome definitions employed (relapse/progression) and MRI metrics. Cohort characteristics Fewer untreated patients with RRMS are now available for trials and a clear shift has occurred in disease baseline activity. When displayed graphically, a clear time-dependent curve exists, with patients in the 1990s having baseline ARRs of up to 2.0, which 20 years later, have fallen to below 0.5.1 The reasons for this shift may include patient selection, study design, current treatment options, and a possible change in the natural history of MS.2 The bias is clear in comparing activity over the 2-decade period. Epidemiological factors (known and unknown) will influence the activity of the entry cohort, making it dangerous to generalise too excessively to different populations not examined in the trial. There is clear geographic variation in the clinical course of MS (http://www.atlasofms.org), and more active disease is expected in countries at high latitude. There are genetic and environmental factors that are associated
with MS activity, but these may not have been considered as co-variates: Increased serum vitamin D levels, for example, may be associated with reduced disease activity and slower rate of progression in patients on a treatment of interferon.3 Other parameters, including birth month,4 age at onset, race, human leukocyte antigen (HLA) status,5 and clinically-isolated syndrome (CIS) multifocal/monofocal presentations may have a significant effect on the subsequent disease profile.6 These factors have generally not been examined when assessing the effect of a medication, although they may directly influence the primary trial endpoint.
Correspondence to: Olga Ciccarelli Queen Square MS Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK. [email protected] Olga Ciccarelli Queen Square MS Centre, UCL Institute of Neurology, London, UK Jeremy Chataway Queen Square MS Centre, UCL Institute of Neurology, London, UK/NIHR UCL/ UCLH Biomedical Research Centre (BRC), London, UK
Outcome measures Common primary outcome measures in clinical trials are comparisons of counts of the number of relapses and proportions of sustained disability progression; however, there are intrinsic ascertainment biases at play. The definition of a relapse may change between trials, with some trials reporting the need of detecting new objective neurological findings,7 whilst others describe exactly the increase in the Expanded Disability Status Scale (EDSS) score that is needed to define a relapse.8 Overall, the recentlyconducted trials have used more stringent definitions of relapses, compared with early trials.2 The number of relapses recorded in a clinical trial increases if there are frequent visits; and therefore, this measure is dependent on the study design.2 Sustained progression can be defined as a worsening of EDSS that persists for either 12 weeks9 or 24 weeks.10 Additionally, a worsening in EDSS does not reflect which functional system changes, as similar raw EDSS changes can be obtained with deteriorations (and improvements) in different functional systems.
http://msj.sagepub.com 37
Downloaded from msj.sagepub.com at The University of Iowa Libraries on June 17, 2015
Multiple Sclerosis Journal 21(1) MRI parameters Here again there is heterogeneity, because of differences in study design, frequency of the scans, observer rating experience and skills, the scanning protocol and the MRI outcome measures. In order to examine the effect on active lesions, trials have used a range of measures, from the cumulative number of unique active lesions (which include gadolinium-enhancing lesions, and new or enlarged lesions) to the number of patients with new or enlarging lesions.10 Although they all reflect roughly the effect of the drug upon MRI disease activity, which is useful to know to counsel patients, it is impossible to perform a headto-head comparison of exactly the same outcome measure. The situation becomes even more confusing when examining the results of brain volume changes, which are not comparable between trials, because of differences in MRI analysis acquisition and analysis techniques.11 In conclusion, as we are now in an era where placebo-controlled trials are associated with ethical issues and will become rarer, and trials with an activecomparator arm will become more popular, thereby impeding even further direct comparisons with the findings of the first and second generation-conducted trials. Although results of any given trial are individually important and valid in their own context, intertrial comparisons will remain rough and imprecise, and should be accompanied by the appropriate statistical health-warning.
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SAGE journals
References 1. Nicholas R, Straube S, Schmidli H, et al. Timepatterns of annualized relapse rates in randomized placebo-controlled clinical trials in relapsing– remitting multiple sclerosis: A systematic review and meta-analysis. Mult Scler 2012; 18: 1290–1296. 2. Uitdehaag BM, Barkhof F, Coyle PK, et al. The changing face of multiple sclerosis clinical trial populations. Curr Med Res Opin 2011; 27: 1529–1537. 3. Ascherio A, Munger KL, White R, et al. Vitamin D as an early predictor of multiple sclerosis activity and progression. JAMA Neurol 2014; 71: 306–314. 4. Dobson R, Giovannoni G and Ramagopalan S. The month of birth effect in multiple sclerosis: Systematic review, meta-analysis and effect of latitude. J Neurol Neurosurg Psychiatry 2013; 84: 427–432. 5. Kelly MA, Cavan DA, Penny MA, et al. The influence of HLA-DR and -DQ alleles on progression to multiple sclerosis following a clinically isolated syndrome. Hum Immunol 1993; 37: 185–191. 6. Miller DH, Chard DT and Ciccarelli O. Clinically isolated syndromes. Lancet Neurol 2012; 11: 157–169. 7. Calabresi PA, Kieseier BC, Arnold DL, et al. Pegylated interferon β-1a for relapsing–remitting multiple sclerosis (ADVANCE): A randomised, phase 3, double-blind study. Lancet Neurol 2014; 13: 657–665.
Conflict of interest Author O Ciccarelli is an Associate Editor of Neurology® and serves on the editorial board of Multiple Sclerosis Journal; she serves as consultant for Biogen, General Electric, and Novartis; and she receives research support from UK MS Society, UCL/UCLH NIHR BRC, and EPSRC. Author J Chataway has been the PI of trials sponsored by Novartis, GSK, Biogen and Apitope; he has received speaking honoraria from, and/or served in an advisory role for Novartis; and he receives research support from Novartis.
8. Kappos L, Radue EW, O’Connor P, et al. A placebocontrolled trial of oral fingolimod in relapsing multiple sclerosis. N Engl J Med 2010; 362: 387–401.
Funding This research received no specific grant from any funding agency in the public, commercial, or not-forprofit sectors.
11. Zivadinov R, Reder AT, Filippi M, et al. Mechanisms of action of disease-modifying agents and brain volume changes in multiple sclerosis. Neurology 2008; 71: 136–144.
9. O’Connor P, Wolinsky JS, Confavreux C, et al. Randomized trial of oral teriflunomide for relapsing multiple sclerosis. N Engl J Med 2011; 365: 1293–1303. 10. Cohen JA, Coles AJ, Arnold DL, et al. Alemtuzumab versus interferon beta 1a as first-line treatment for patients with relapsing–remitting multiple sclerosis: A randomised controlled phase 3 trial. Lancet 2012; 380: 1819–1828.
38 http://msj.sagepub.com
Downloaded from msj.sagepub.com at The University of Iowa Libraries on June 17, 2015
research-article2015
MSJ0010.1177/1352458514559866Multiple Sclerosis JournalO Ciccarelli and J Chataway
O Ciccarelli and J Chataway
We can compare the relative efficacy of multiple sclerosis medications by examining the results of independent clinical trials: No
Multiple Sclerosis Journal 2015, Vol. 21(1) 37–38 DOI: 10.1177/ 1352458514559866 © The Author(s), 2015. Reprints and permissions: http://www.sagepub.co.uk/ journalsPermissions.nav
Olga Ciccarelli and Jeremy Chataway Date received: 22 October 2014; accepted: 22 October 2014
An increasing number of disease-modifying drugs (DMD) are now licensed to reduce disease activity in patients with relapsing–remitting (RRMS). Logical and frequent questions posed by patients to their clinician are firstly, how well do they work; and secondly, how they compare one to another? The neurologist will usually answer this question by comparing the reduction in annualised relapse rate (ARR) and the effect on new magnetic resonance imaging (MRI) lesions, as reported in the pivotal trials for each compound. We argue that this approach is likely to be approximate and inaccurate, by considering this under the key headings (detailed below) of: cohort characteristics, outcome definitions employed (relapse/progression) and MRI metrics. Cohort characteristics Fewer untreated patients with RRMS are now available for trials and a clear shift has occurred in disease baseline activity. When displayed graphically, a clear time-dependent curve exists, with patients in the 1990s having baseline ARRs of up to 2.0, which 20 years later, have fallen to below 0.5.1 The reasons for this shift may include patient selection, study design, current treatment options, and a possible change in the natural history of MS.2 The bias is clear in comparing activity over the 2-decade period. Epidemiological factors (known and unknown) will influence the activity of the entry cohort, making it dangerous to generalise too excessively to different populations not examined in the trial. There is clear geographic variation in the clinical course of MS (http://www.atlasofms.org), and more active disease is expected in countries at high latitude. There are genetic and environmental factors that are associated
with MS activity, but these may not have been considered as co-variates: Increased serum vitamin D levels, for example, may be associated with reduced disease activity and slower rate of progression in patients on a treatment of interferon.3 Other parameters, including birth month,4 age at onset, race, human leukocyte antigen (HLA) status,5 and clinically-isolated syndrome (CIS) multifocal/monofocal presentations may have a significant effect on the subsequent disease profile.6 These factors have generally not been examined when assessing the effect of a medication, although they may directly influence the primary trial endpoint.
Correspondence to: Olga Ciccarelli Queen Square MS Centre, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK. [email protected] Olga Ciccarelli Queen Square MS Centre, UCL Institute of Neurology, London, UK Jeremy Chataway Queen Square MS Centre, UCL Institute of Neurology, London, UK/NIHR UCL/ UCLH Biomedical Research Centre (BRC), London, UK
Outcome measures Common primary outcome measures in clinical trials are comparisons of counts of the number of relapses and proportions of sustained disability progression; however, there are intrinsic ascertainment biases at play. The definition of a relapse may change between trials, with some trials reporting the need of detecting new objective neurological findings,7 whilst others describe exactly the increase in the Expanded Disability Status Scale (EDSS) score that is needed to define a relapse.8 Overall, the recentlyconducted trials have used more stringent definitions of relapses, compared with early trials.2 The number of relapses recorded in a clinical trial increases if there are frequent visits; and therefore, this measure is dependent on the study design.2 Sustained progression can be defined as a worsening of EDSS that persists for either 12 weeks9 or 24 weeks.10 Additionally, a worsening in EDSS does not reflect which functional system changes, as similar raw EDSS changes can be obtained with deteriorations (and improvements) in different functional systems.
http://msj.sagepub.com 37
Downloaded from msj.sagepub.com at The University of Iowa Libraries on June 17, 2015
Multiple Sclerosis Journal 21(1) MRI parameters Here again there is heterogeneity, because of differences in study design, frequency of the scans, observer rating experience and skills, the scanning protocol and the MRI outcome measures. In order to examine the effect on active lesions, trials have used a range of measures, from the cumulative number of unique active lesions (which include gadolinium-enhancing lesions, and new or enlarged lesions) to the number of patients with new or enlarging lesions.10 Although they all reflect roughly the effect of the drug upon MRI disease activity, which is useful to know to counsel patients, it is impossible to perform a headto-head comparison of exactly the same outcome measure. The situation becomes even more confusing when examining the results of brain volume changes, which are not comparable between trials, because of differences in MRI analysis acquisition and analysis techniques.11 In conclusion, as we are now in an era where placebo-controlled trials are associated with ethical issues and will become rarer, and trials with an activecomparator arm will become more popular, thereby impeding even further direct comparisons with the findings of the first and second generation-conducted trials. Although results of any given trial are individually important and valid in their own context, intertrial comparisons will remain rough and imprecise, and should be accompanied by the appropriate statistical health-warning.
Visit SAGE journals online http://msj.sagepub.com
SAGE journals
References 1. Nicholas R, Straube S, Schmidli H, et al. Timepatterns of annualized relapse rates in randomized placebo-controlled clinical trials in relapsing– remitting multiple sclerosis: A systematic review and meta-analysis. Mult Scler 2012; 18: 1290–1296. 2. Uitdehaag BM, Barkhof F, Coyle PK, et al. The changing face of multiple sclerosis clinical trial populations. Curr Med Res Opin 2011; 27: 1529–1537. 3. Ascherio A, Munger KL, White R, et al. Vitamin D as an early predictor of multiple sclerosis activity and progression. JAMA Neurol 2014; 71: 306–314. 4. Dobson R, Giovannoni G and Ramagopalan S. The month of birth effect in multiple sclerosis: Systematic review, meta-analysis and effect of latitude. J Neurol Neurosurg Psychiatry 2013; 84: 427–432. 5. Kelly MA, Cavan DA, Penny MA, et al. The influence of HLA-DR and -DQ alleles on progression to multiple sclerosis following a clinically isolated syndrome. Hum Immunol 1993; 37: 185–191. 6. Miller DH, Chard DT and Ciccarelli O. Clinically isolated syndromes. Lancet Neurol 2012; 11: 157–169. 7. Calabresi PA, Kieseier BC, Arnold DL, et al. Pegylated interferon β-1a for relapsing–remitting multiple sclerosis (ADVANCE): A randomised, phase 3, double-blind study. Lancet Neurol 2014; 13: 657–665.
Conflict of interest Author O Ciccarelli is an Associate Editor of Neurology® and serves on the editorial board of Multiple Sclerosis Journal; she serves as consultant for Biogen, General Electric, and Novartis; and she receives research support from UK MS Society, UCL/UCLH NIHR BRC, and EPSRC. Author J Chataway has been the PI of trials sponsored by Novartis, GSK, Biogen and Apitope; he has received speaking honoraria from, and/or served in an advisory role for Novartis; and he receives research support from Novartis.
8. Kappos L, Radue EW, O’Connor P, et al. A placebocontrolled trial of oral fingolimod in relapsing multiple sclerosis. N Engl J Med 2010; 362: 387–401.
Funding This research received no specific grant from any funding agency in the public, commercial, or not-forprofit sectors.
11. Zivadinov R, Reder AT, Filippi M, et al. Mechanisms of action of disease-modifying agents and brain volume changes in multiple sclerosis. Neurology 2008; 71: 136–144.
9. O’Connor P, Wolinsky JS, Confavreux C, et al. Randomized trial of oral teriflunomide for relapsing multiple sclerosis. N Engl J Med 2011; 365: 1293–1303. 10. Cohen JA, Coles AJ, Arnold DL, et al. Alemtuzumab versus interferon beta 1a as first-line treatment for patients with relapsing–remitting multiple sclerosis: A randomised controlled phase 3 trial. Lancet 2012; 380: 1819–1828.
38 http://msj.sagepub.com
Downloaded from msj.sagepub.com at The University of Iowa Libraries on June 17, 2015
