Project

Project details

  • TITLE

    Big Multiple Sclerosis Data (BMSD) network

  • SYNOPSIS AND RESULTS

  • Data start Data end
    2021-12-31
  • PARTICIPATING CENTERS

    ---

  • OUTCOME

    Introduction and aims
    In 2013, five MS registries (Italian MS registry - formerly known as iMEDweb network, SMSReg of Sweden, MSBase based in Australia, OFSEP of France and the Danish MS registry) started to evaluate the potential, usefulness and potential paths of collaboration and/or pooling of data for research on the diagnosis, epidemiology and treatment of MS – the Big MS Data Network (BMSD).
    A feasibility phase was carried out between 2014 and 2015. This feasibility evaluation comprised the following steps: registries descriptions; registries comparison in terms of governance structure, data collection tools and data storage systems, availability of key variables for MS research.
    The governance of the BMSD network has been established as follow: a steering committee composed by the principal investigator of each involved registry; a data management subcommittee composed by data analysts involved in the data management of each dataset; a statistical analysis committee composed by statisticians and project leaders of the research projects.
    At the end of the feasibility phase was decided to launch three demonstrator projects in order to test the capability to pool data which come from different sources, working also on the harmonization of the data structure, outcomes definitions and data analysis.
    The following were the title of the projects along with the leading registry: Very long-term effectiveness of DMTs in multiple sclerosis - Italian MS Registry; Discontinuation frequencies of DMTs - Swedish MS Registry; Efficacy of DMTs in progressive MS – MSBase.


    Results
    Here are reported the objectives and the main results obtained from these projects.
    1. Very long-term effectiveness of DMTs in multiple sclerosis - Italian MS Registry: The aim was to evaluate the impact of the time interval from disease onset to the first DMT on the treatment effect on long-term disability accumulation.
    Four study outcomes were evaluated: 3- and 12-month Confirmed Disability Worsening (CDW) and assignment of either irreversible EDSS 4.0 or EDSS 6.0.
    In the first step of our analysis, four Cox regression models were used to estimate the risk of reaching each of the 4 outcomes. The time from disease onset to the first DMT start was included as quintiles and the first quintile was included as reference class.
    In the second step of this analysis, propensity score (PS) matching was used to enable pairwise comparisons among patients grouped by the time from disease onset to the first DMT start.
    The final cohort, obtained by applying the inclusion criteria, was composed by 11,871 RRMS patients.
    A 3- and 12-month confirmed disability worsening event and irreversible EDSS 4.0 and 6.0 scores were reached by 7,062 (59.5%), 4,138 (34.9%), 3,209 (31.1%) and 1,909 (16.5%) patients, respectively.
    The risk of reaching all the disability outcomes was significantly lower (p<0.0004) for the 1st quintile patients’ group. These data represent the largest RRMS cohort with the longest follow-up ever analysed to determine the long-term effectiveness of the early initiation of DMTs. Our results indicate that the optimal time to start DMTs in MS to prevent long-term disability accumulation is within 12 months of disease onset.
    2. Discontinuation frequencies of DMTs - Swedish MS Registry: The objective of this study was to describe treatment interruption and discontinuation in the BMSD network. Information on 269,822 treatment episodes in 110,326 patients from 1997 to 2016 were retrieved. Treatment stop was defined as a clinician recorded DMT end for any reason and included treatment interruptions, switching to alternate DMTs and long-term or permanent discontinuations. The incidence of DMT stopping cross the full observation period was lowest in fingolimod (19.7 per 100 person-years (PY) of treatment; 95% CI 19.2–20.1), followed by natalizumab (22.6/100 PY; 95% CI 22.2–23.0), IFNb (23.3/100 PY; 95% CI 23.2–23.5). Of the 184,013 observed DMT stops, 159,309 (86.6%) switched to an alternate DMT within 6 months. DMT stopping reasons and rates were mostly stable over time with a slight increase in recent years, with the availability of more DMTs. The results suggest that discontinuation of MS DMTs is mostly due to DMT properties and to a lesser extent to risk management and a competitive market.
    3. Efficacy of DMTs in progressive MS – MSBase: The objective was to identify subgroups of SPMS patients with similar longitudinal trajectories of EDSS over time. Longitudinal EDSS scores were modelled by a latent class mixed model (LCMM), using a nonlinear function of time from the first EDSS visit with an EDSS value of 3 to 4.
    A total of 3613 SPMS (66.2% females; 39.1% from France, 24.4% from Italy, 19.6% MSBase, 16.9% Sweden). LCMM detected 3 different subgroups of patients with a mild, a moderate and a severe disability trajectory. Median time to EDSS 6 was 12.2, 5 and 1.7 years, for the 3 groups respectively. Patients with the “severe” disability time course were younger (p<0.001) and with a shorter disease duration at baseline (p<0.001). Heterogeneity among the four Registries was also observed (p<0.001) with a higher frequency of patients with milder MS in the French (39.2%) and Swedish (43.9%) registries. We observed a higher frequency of moderate MS in the Italian (59.6%) and MSBase (55.6%) registries. This results indicate that for the treatment of SPMS and in the design of
    future clinical trials, with time to confirmed EDSS progression as the primary endpoint, the existence of heterogeneous classes of patients could have important implications.

    Conclusions
    In conclusions, the results obtained by the BMSD network provide evidence that data sharing among MS registries and databases is feasible and can provide enough statistical power to detect the impact of treatment on disability outcomes over the long term and to select specific sub-population that may need a more tailored treatment approach.




    Pubblicazioni e Comunicazioni a Congressi/ Publications and Congress Presentations
    • Iaffaldano P, Lucisano G, Butzkueven H, Hillert J, Hyde R, Koch-Henriksen N, Magyari M, Pellegrini F, Spelman T, Sørensen PS, Vukusic S, Trojano M. Early treatment delays long-term disability accrual in RRMS: Results from the BMSD network. Mult Scler. 2021 Sep;27(10):1543-1555. doi: 10.1177/13524585211010128
    • Hillert J, Magyari M, Soelberg Sørensen P, Butzkueven H, Van Der Welt A, Vukusic S, Trojano M, Iaffaldano P, Pellegrini F, Hyde R, Stawiarz L, Manouchehrinia A, Spelman T. Treatment Switching and Discontinuation Over 20 Years in the Big Multiple Sclerosis Data Network. Front Neurol. 2021 Mar 17;12:647811 doi:10.3389/fneur.2021.647811
    • Signori A, Lorscheider J, Vukusic S, Trojano M, Iaffaldano P, Hillert J, Hyde R, Pellegrini F, Magyari M, Sorensen PS, Spelman T. Heterogeneity on long-term disability trajectories in secondary progressive MS patients-a latent class analysis from big MS data network. Presented to ECTRIMS congress 2021. Multiple Sclerosis Journal 2021 Oct 1, Vol. 27, No. 2_ Suppl, pp. 213-214

    Website: https://bigmsdata.org

  • PUBLICATIONS

    Iaffaldano P, Lucisano G, Butzkueven H, Hillert J, Hyde R, Koch-Henriksen N, Magyari M, Pellegrini F, Spelman T, Sørensen PS, Vukusic S, Trojano M. Early treatment delays long-term disability accrual in RRMS: Results from the BMSD network. Mult Scler. 2021 Sep;27(10):1543-1555. doi: 10.1177/13524585211010128.

    Hillert J, Magyari M, Soelberg Sørensen P, Butzkueven H, Van Der Welt A, Vukusic S, Trojano M, Iaffaldano P, Pellegrini F, Hyde R, Stawiarz L, Manouchehrinia A, Spelman T. Treatment Switching and Discontinuation Over 20 Years in the Big Multiple Sclerosis Data Network. Front Neurol. 2021 Mar 17;12:647811. doi: 10.3389/fneur.2021.647811.

    Signori A, et al. Big MS Data Network. Heterogeneity on long-term disability trajectories in patients with secondary progressive MS: a latent class analysis from Big MS Data network. J Neurol Neurosurg Psychiatry. 2022 Sep 28:jnnp-2022-329987. doi: 10.1136/jnnp-2022-329987.

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