ClinicSpeak & StatsSpeak: switching sideways or upwards

How actively do you want your MS to be managed? #ClinicSpeak #StatsSpeak #MSBlog #MSResearch

"Just as video killed the radio-star; orals DMTs are killing the injectable DMTs. The study below is essentially a trial of NEDA-2 (no clinically evident disease disease activity) and is being referred amongst UK neurologists as current best practice, i.e. you change therapy when someone breaks through clinically with a relapse. What this study is showing that a horizontal switch from IFN-beta to GA or GA to IFNbeta results in a worse outcome compared to escalation to fingolimod. This study uses real-life data collected as part of routine clinical practice and controls for bias by using a statistical method called propensity matching. The latter is about as good as it gets with real-life data. Ideally you would like this to be a clinical trial and randomise the subjects to two arms; i.e. anyone failing a 1st-line injectable clinically gets randomised horizontally to another class of injectable or vertically to the higher efficacy fingolimod. We already know that fingolimod is on average more effective than the injectables based on phase 3 trial data and its impact on end-organ damage (brain atrophy on MRI)."

"In the UK, the MS Society's early effective task force is currently designing a trial to test NEDA-2 vs. NEDA-3; i.e routine clinical practice using significant relapses to escalate treatment compared to vs. using active monitoring with frequent MRI to detect subclinical relapses to escalate vs. flipping the pyramid to start on a highly-effective treatment first. When I have presented the concept of our trial design to neurologists outside of the UK they have responded that the trial is unethical and would not be possible in their country because this is how they manage MS already."

"Please note that in the UK escalating on breakthrough relapses is controversial; many neurologists only offer a switch if they relapse is disabling. In addition, many relapses are not reported by MSers and therefore not taken into account when making a decision about switching therapies. This is why you have to monitor your relapses and why self-monitoring apps and tools are becoming increasingly important. I personally don't think there is any biological difference between mild, moderate and severe MS relapses; what they are all telling you is that your disease is active and that if you are on a DMT is not doing its job. What determines if a MS lesion causes a relapse is its location and size; a small lesion in an ineloquent site of the brain will be asymptomatic, however the same size lesion in the brainstem could cause a devastating relapse that is life threatening. We need to get away from the idea that any disease activity is acceptable; this is why we have a zero tolerance strategy or ZeTo."

"The following are a few slides to illustrate our shifting practice and how we have stolen ideas from our colleagues in other specialities; the example I give is how the gastroenterologists manage inflammatory bowel disease."


StatsSpeak: In the statistical analysis of observational data, propensity score matching (PSM) is a statistical matching technique that attempts to estimate the effect of a treatment, policy, or other intervention by accounting for the covariates that predict receiving the treatment. 

Epub: He et al. Comparison of Switch to Fingolimod or Interferon Beta/Glatiramer Acetate in Active Multiple Sclerosis. JAMA Neurol. 2015 Feb :1-10. 

IMPORTANCE: After MS relapse while an MSer is receiving an injectable disease-modifying drug, many physicians advocate therapy switch, but the relative effectiveness of different switch decisions is often uncertain.

OBJECTIVE: To compare the effect of the oral immunomodulator fingolimod with that of all injectable immunomodulators (interferons or glatiramer acetate) on relapse rate, disability, and treatment persistence in MSers with active MS.

DESIGN, SETTING, AND PARTICIPANTS: Matched retrospective analysis of data collected prospectively from MSBase, an international, observational cohort study. The MSBase cohort represents a population of MSers monitored at large MS centers. The analyzed data were collected between July 1996 and April 2014. Participants included RRMSers who were switching therapy to fingolimod or injectable immunomodulators up to 12 months after on-treatment clinical disease activity (relapse or progression of disability), matched on demographic and clinical variables. Median follow-up duration was 13.1 months (range, 3-80). Indication and attrition bias were controlled with propensity score matching and pairwise censoring, respectively. Head-to-head analyses of relapse and disability outcomes used paired, weighted, negative binomial models or frailty proportional hazards models adjusted for magnetic resonance imaging variables. Sensitivity analyses were conducted.

EXPOSURES: MSers had received fingolimod, interferon beta, or glatiramer acetate for a minimum of 3 months following a switch of immunomodulatory therapy.

MAIN OUTCOMES AND MEASURES:  Annualized relapse rate and proportion of relapse-free MSers, as well as the proportion of MSers without sustained disability progression.

RESULTS: Overall, 379 MSers in the injectable group were matched to 148 MSers in the fingolimod group. The fingolimod group had a lower mean annualized relapse rate (0.31 vs 0.42; 95% CI, 0.02-0.19; P = .009), lower hazard of first on-treatment relapse (hazard ratio [HR], 0.74; 95% CI, 0.56-0.98; P = .04), lower hazard of disability progression (HR, 0.53; 95% CI, 0.31-0.91; P = .02), higher rate of disability regression (HR, 2.0; 95% CI, 1.2-3.3; P = .005), and lower hazard of treatment discontinuation (HR, 0.55; P = .04) compared with the injectable group.

CONCLUSIONS AND RELEVANCE: Switching from injectable immunomodulators to fingolimod is associated with fewer relapses, more favorable disability outcomes, and greater treatment persistence compared with switching to another injectable preparation following on-treatment activity of MS.

CoI: multiple

Labels: , , , , ,