Multiple sclerosis, the measurement of disability and access to clinical trial data

Background: Inferences about long-term effects of therapies in multiple sclerosis (MS) have been based on surrogate markers studied in short-term trials. Nevertheless, MS trials have been getting steadily shorter despite the lack of a consensus definition for the most important clinical outcome - unremitting progression of disability. Methods: We have examined widely used surrogate markers of disability progression in MS within a unique database of individual patient data from the placebo arms of 31 randomised clinical trials. Findings: Definitions of treatment failure used in secondary progressive MS trials include much change unrelated to the target of unremitting disability. In relapsing-remitting MS, disability progression by treatment failure definitions was no more likely than similarly defined improvement for these disability surrogates. Existing definitions of disease progression in relapsing-remitting trials encompass random variation, measurement error and remitting relapses and appear not to measure unremitting disability. Interpretation: Clinical surrogates of unremitting disability used in relapsing -remitting trials cannot be validated. Trials have been too short and/or degrees of disability change too small to evaluate unremitting disability outcomes. Important implications for trial design and reinterpretation of existing trial results have emerged long after regulatory approval and widespread use of therapies in MS, highlighting the necessity of having primary trial data in the public domain

Reducing the Probability of False Positive Research Findings by Pre-Publication Validation - Experience with a Large Multiple Sclerosis Database

*Objective*
We have assessed the utility of a pre-publication validation policy in reducing the probability of publishing false positive research findings. 
*Study design and setting*
The large database of the Sylvia Lawry Centre for Multiple Sclerosis Research was split in two parts: one for hypothesis generation and a validation part for confirmation of selected results. We present case studies from 5 finalized projects that have used the validation policy and results from a simulation study.
*Results*
In one project, the "relapse and disability" project as described in section II (example 3), findings could not be confirmed in the validation part of the database. The simulation study showed that the percentage of false positive findings can exceed 20% depending on variable selection. 
*Conclusion*
We conclude that the validation policy has prevented the publication of at least one research finding that could not be validated in an independent data set (and probably would have been a "true" false-positive finding) over the past three years, and has led to improved data analysis, statistical programming, and selection of hypotheses. The advantages outweigh the lost statistical power inherent in the process

Treating systematic errors in multiple sclerosis data

Multiple sclerosis (MS) is characterized by high variability between patients and, more importantly here, within an individual over time. This makes categorization and prognosis difficult. Moreover, it is unclear to what degree this intra-individual variation reflects the long-term course of irreversible disability and what is attributable to short-term processes such as relapses, to interrater variability and to measurement error. Any investigation and prediction of the medium or long term evolution of irreversible disability in individual patients is therefore confronted with the problem of systematic error in addition to random fluctuations. The approach described in this article aims to assist in detecting relapses in disease curves and in identifying the underlying disease course. To this end neurological knowledge was transformed into simple rules which were then implemented into computer algorithms for pre-editing disease curves. Based on simulations it is shown that pre-editing time series of disability measured with the Expanded Disability Status Scale (EDSS) can lead to more robust and less biased estimates for important disease characteristics, such as baseline EDSS and time to reach certain EDSS levels or sustained progression

Treating Systematic Errors in Multiple Sclerosis Data

Multiple sclerosis (MS) is characterized by high variability between patients and, more importantly here, within an individual over time. This makes categorization and prognosis difficult. Moreover, it is unclear to what degree this intra-individual variation reflects the long-term course of irreversible disability and what is attributable to short-term processes such as relapses, to interrater variability and to measurement error. Any investigation and prediction of the medium or long term evolution of irreversible disability in individual patients is therefore confronted with the problem of systematic error in addition to random fluctuations. The approach described in this article aims to assist in detecting relapses in disease curves and in identifying the underlying disease course. To this end neurological knowledge was transformed into simple rules which were then implemented into computer algorithms for pre-editing disease curves. Based on simulations it is shown that pre-editing time series of disability measured with the Expanded Disability Status Scale (EDSS) can lead to more robust and less biased estimates for important disease characteristics, such as baseline EDSS and time to reach certain EDSS levels or sustained progression

Liability For Artificial Intelligence And EU Consumer Law

The new Directives on Digital Contracts – the Digital Content and Services Directive (DCSD) 2019/770 and the Sale of Goods Directive (SGD) 2019/771 – are often seen as important steps in adapting European private law to the requirements of the digital economy. However, neither directive contains special rules for new technologies such as Artificial Intelligence (AI). In light of this issue, the following paper discusses whether existing EU consumer law is equipped to deal with situations in which AI systems are either used for internal purposes by companies or offered to consumers as the main subject matter of the contract. This analysis will reveal a number of gaps in current EU consumer law and briefly discuss upcoming legislation

An Extremes of outcome strategy provides evidence that multiple sclerosis severity is determined by alleles at the <i>HLA-DRB1</i> locus

Multiple sclerosis (MS) is a common inflammatory disease of the central nervous system unsurpassed for variability in disease outcome. A cohort of sporadic MS cases (n=63), taken from opposite extremes of the distribution of long-term outcome, was used to determine the role of the HLA-DRB1 locus on MS disease severity. Genotyping sets of benign and malignant MS patients showed that HLA-DRB1*01 was significantly underrepresented in malignant compared with benign cases. This allele appears to attenuate the progressive disability that characterizes MS in the long term. The observation was doubly replicated in (i) Sardinian benign and malignant patients and (ii) a cohort of affected sibling pairs discordant for HLA-DRB1*01. Among the latter, mean disability progression indices were significantly lower in those carrying the HLA-DRB1*01 allele compared with their disease-concordant siblings who did not. The findings were additionally supported by similar transmission distortion of HLA-DRB1*04 subtypes closely related to HLA-DRB1*01. The protective effect of HLA-DRB1*01 in sibling pairs may result from a specific epistatic interaction with the susceptibility allele HLA-DRB1*1501. A high-density (&gt;700) SNP examination of the MHC region in the benign and malignant patients could not identify variants differing significantly between the two groups, suggesting that HLA-DRB1 may itself be the disease-modifying locus. We conclude that HLA-DRB1*01, previously implicated in disease resistance, acts as an independent modifier of disease progression. These results closely link susceptibility to long-term outcome in MS, suggesting that shared quantitative MHC-based mechanisms are common to both, emphasizing the central role of this region in pathogenesis

Reducing the probability of false positive research findings by pre-publication validation – Experience with a large multiple sclerosis database

<p>Abstract</p> <p>Background</p> <p>Published false positive research findings are a major problem in the process of scientific discovery. There is a high rate of lack of replication of results in clinical research in general, multiple sclerosis research being no exception. Our aim was to develop and implement a policy that reduces the probability of publishing false positive research findings.</p> <p>We have assessed the utility to work with a pre-publication validation policy after several years of research in the context of a large multiple sclerosis database.</p> <p>Methods</p> <p>The large database of the Sylvia Lawry Centre for Multiple Sclerosis Research was split in two parts: one for hypothesis generation and a validation part for confirmation of selected results. We present case studies from 5 finalized projects that have used the validation policy and results from a simulation study.</p> <p>Results</p> <p>In one project, the "relapse and disability" project as described in section II (example 3), findings could not be confirmed in the validation part of the database. The simulation study showed that the percentage of false positive findings can exceed 20% depending on variable selection.</p> <p>Conclusion</p> <p>We conclude that the validation policy has prevented the publication of at least one research finding that could not be validated in an independent data set (and probably would have been a "true" false-positive finding) over the past three years, and has led to improved data analysis, statistical programming, and selection of hypotheses. The advantages outweigh the lost statistical power inherent in the process.</p

The natural history of multiple sclerosis: a geographically based study 10: relapses and long-term disability.

The relationship of relapses to long-term disability in multiple sclerosis is uncertain. Relapse reduction is a common therapeutic target but clinical trials have shown dissociation between relapse suppression and disability accumulation. We investigated relationships between relapses and disability progression for outcomes of requiring assistance to walk, being bedridden and dying from multiple sclerosis [Disability Status Scale 6, 8, 10] by analysing 28 000 patient-years of evolution in 806-bout onset patients from the London Ontario natural history cohort. Having previously shown no effect of relapse frequency among progressive multiple sclerosis subtypes, here we examined these measures in the pre-progressive or relapsing-remitting phase. Survival was compared among groups stratified by (i) early relapses--number of attacks during the first 2 years of multiple sclerosis; (ii) length of first inter-attack interval; (iii) interval between onset and Disability Status Scale 3 (moderate disability); (iv) number of attacks from the third year of disease up to onset of progression; and (v) during the entire relapsing-remitting phase. Early clinical features can predict hard disability outcomes. Frequent relapses in the first 2 years and shorter first inter-attack intervals predicted shorter times to reach hard disability endpoints. Attack frequencies, in the first 2 years, of 1 versus >or=3, gave differences of 7.6, 12.8 and 20.3 years in times from disease onset to Disability Status Scale 6, 8 and 10, respectively. Time to Disability Status Scale 3 highly and independently predicted time to Disability Status Scale 6, 8 and 10. In contrast, neither total number of relapsing-remitting phase attacks nor of relapses experienced during the relapsing-remitting phase after the second year up to onset of progression showed a deleterious effect on times from disease onset, from progression onset and from Disability Status Scale 3 to these hard endpoints. The failure of a regulatory mechanism tied to neurodegeneration is suggested. Relapse frequency beyond Year 2 does not appear to predict the key outcome of secondary progression or times to Disability Status Scale 6, 8 or 10, highlighting two distinct disease phases related to late outcome. These appear to be separated by a watershed within the relapsing-remitting phase, just a few years after clinical onset. Higher early relapse frequencies and shorter first inter-attack intervals herald more rapid deterioration via interaction with the neurodegeneration characterizing secondary progression. They increase the probability of its occurrence, its latency and influence--to a lesser degree--its slope. The prevention or delay of the progressive phase of the disease is implicated as a key therapeutic target in relapsing-remitting patients