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#AANAM – Research Focuses on Measuring Therapeutic Lag

#AANAM – Research Focuses on Measuring Therapeutic Lag
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Editor’s note: The Multiple Sclerosis News Today team is providing in-depth coverage of the 2021 Virtual AAN Annual Meeting, held April 17–22. Go here to read the latest stories from the conference.

A novel method to calculate how long it takes therapies for multiple sclerosis (MS) to become fully effective was described in a presentation at the 2021 Virtual American Academy of Neurology Annual Meeting.

Findings from the analysis indicate that MS therapies take longer to be effective for people with greater disability or with a higher rate of relapses prior to starting treatment.

The data were presented by Izanne Roos, a PhD candidate at the University of Melbourne, in Australia, in the talk, “Delay from treatment start to full effect of immunotherapies for multiple sclerosis.”

In the past two decades, there have been substantial strides made in MS treatment. There currently are more than a dozen therapies approved to treat relapsing MS. While clinical trials have broadly demonstrated that long-term treatment with these medications can reduce relapse rates and ease disability, “much less emphasis is usually placed on the early period after treatments are commenced,” Roos said.

“It is important to know, however, how long a treatment will take to become effective,” Roos said, noting that this is important both for people starting treatment for the first time, and for those switching from one treatment to another.

The time between when a person starts taking a medication, and when full effects of that medication become apparent, is called “therapeutic lag.”

In their analysis, Roos and colleagues, “aimed to develop a method that allows identification of the time to full clinical manifestation of therapies on two clinical outcomes: relapses and progression of disability,” Roos said.

To do this, the scientists analyzed data from the two largest observational studies of MS: the international study MSBase, and the French database OFSEP.

“Together, this gives us access to [data on] more than 120,000 patients,” Roos said.

The researchers specifically identified patients who had been on an MS disease-modifying therapy for at least one year, and who had at least three years of available data prior to starting treatment and were reviewed annually.

In order to calculate therapeutic lag, the researchers drew graphs to compare rates of relapses or disability progression in the years immediately before and after starting therapy. This revealed some notable trends. For example, there generally was a peak in relapses or disability progression right before treatments were started.

“This makes sense, because this [the relapses or disability progression] is probably the reason why treatments were commenced in the first place,” Roos said.

Then, after treatments were started, the rates of relapses or disability progression decreased and stabilized as the treatments took effect.

“What we wanted to measure was this timepoint between treatment start and stabilization – i.e., the duration of therapeutic lag,” Roos said.

Roos and colleagues calculated this using differential calculus and statistical models for various different MS therapies. Results from analyses using data from MSBase or OFSEP generally provided comparable results, supporting the validity of this method.

Most of the therapies analyzed became effective on relapses about 12–20 weeks after starting treatment. The exception was Tecfidera (dimethyl fumarate), which took slightly longer (about 30 weeks).

Treatments generally became effective on disability progression after about 30–52 weeks. The exception was interferon beta-1a (sold as Avonex, among others) injected into muscle, which took about 70 weeks to affect disability progression.

In further analyses, the researchers looked for patient clinical and demographic factors that could affect therapeutic lag significantly.

These analyses revealed that, for an effect on disability progression, therapeutic lag was higher for individuals with greater disability or a higher rate of relapses prior to starting treatment. Therapeutic lag also was longer in males than in females.

Relapse rate, disability, and male sex also were associated with longer therapeutic lag for the effect of therapy on relapses. Secondary progressive MS was associated with a longer therapeutic lag for relapse rate.

Looking at combinations of individual characteristics allowed the researchers to make detailed predictions. For example, “if we look specifically at females with an annualized relapse rate of less than one, having a disability score [on the Expanded Disability Status Scale or EDSS] of more than 6, resulted in a 28-week longer time to treatment effect [on disability],” compared with females with a similar relapsed rate, but an EDSS of less than 6, Roos said.

“Baseline EDSS and annualized relapse rates are significant determinants of therapeutic lag, and when estimating clinical treatment response, as well as clinical trial and study design, one should keep these estimated durations of lag in mind,” Roos concluded.

Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
Total Posts: 81
Inês holds a PhD in Biomedical Sciences from the University of Lisbon, Portugal, where she specialized in blood vessel biology, blood stem cells, and cancer. Before that, she studied Cell and Molecular Biology at Universidade Nova de Lisboa and worked as a research fellow at Faculdade de Ciências e Tecnologias and Instituto Gulbenkian de Ciência. Inês currently works as a Managing Science Editor, striving to deliver the latest scientific advances to patient communities in a clear and accurate manner.
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Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
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