AAN2020. Therapeutic slag…Prof G was right


I mean Lag:-)..but the disclosures were 129 lines long:-)

If you remember about two years ago we wrote a very turgid and difficult to read paper, on why we have messed up in not finding treatments for progressive MS. In this paper we had two concepts (a) Length dependent axonopathy and (b) therapeutic lag.

https://www.ncbi.nlm.nih.gov/pubmed/28283111 Mult Scler Relat Disord. 2017 Feb;12:70-78. doi: 10.1016/j.msard.2017.01.007. Is multiple sclerosis a length-dependent central axonopathy? The case for therapeutic lag and the asynchronous progressive MS hypotheses.

The first one was that the longer the nerve tract the more likely that it would get damged by MS and so the neurological reserve to tolerate damage would be exhausted quicker. So doing trials based on leg function are harder to shown an effect, than doing trial on hand function. This has been supported by Oratorio trials with ocrelizumab and the ascend trial with natalizumab. Therapeuitic lag means that it takes time to see an effect as todays damge is going to grumble on for some time, therefore you have to re-baselinse studies and do longer studies,

Roos et al. Identification of Therapeutic Lag in Multiple Sclerosis S29.003  

Objective:To develop a method that allows identification of the time to full clinically manifest effect of multiple sclerosis (MS) treatments (‘therapeutic lag’) on clinical disease activity.

Background:In MS, treatment start or switch is prompted by evidence of disease activity, often presenting as relapses or disability progression.  Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear.  

Design/Methods:Data from MSBase, a multinational MS registry, and OFSEP, the French national registry, were used.  Patients diagnosed with MS, minimum 1-year exposure to MS treatment, minimum 3-year pre-treatment follow up and yearly review were included in the analysis.  For analysis of disability progression, all events in the subsequent 5-year period were included in the analysis.  Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy.  Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start. This point represents the point of stabilisation of treatment effect, after the maximum treatment effect was observed.  The method was developed using MSBase, and externally validated in OFSEP.  A merged MSBase-OFSEP cohort was used for all subsequent analyses.

Results:11,180 eligible treatment epochs were identified for analysis of relapses and 4088 treatment epochs for disability progression.  There were no significant differences between the results of discovery and validation analyses.  The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12-30 weeks.  The duration of therapeutic lag for disability progression was calculated for 7 therapies and ranged between 30-70 weeks.

Conclusions:We have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies. This method will be applied in studies that will evaluate the effect of patient and disease characteristics on therapeutic lag.

So to show an effect with some of the agents we may have to do a trial that lasts an extra year. Hopefully we can get Prof Kalincik to do a post to tell us which ones took 12 weeks.

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