Multiple sclerosis is a chronic disease of the central nervous system, most often with relapsing-remitting (RRMS) course.
Cladribine tablets was tested against placebo in randomized controlled trials (RCT) in RRMS.
As there is lack of head-to-head trials directly comparing CT to other highly active DMTs, an indirect comparison via network meta-analysis (NMA) was performed with placebo as a common comparator.
To compare probabilities of sustained disability improvement (SDI) on the EDSS, in patients with relapsing-remitting multiple sclerosis (RRMS), treated with cladribine tablets (CT) or fingolimod (FIN), natalizumab (NAT), alemtuzumab (ALE) and ocrelizumab (OCR).
In compliance with the Polish HTA guidelines, a systematic review was conducted in Pubmed, Embase and Cochrane to identify clinical trials (RCT or non-RCT) evaluating 6-month SDI. An indirect comparison via network meta-analysis (NMA) was performed. Bayesian inference with Markov chains Monte Carlo methods were applied, using the WinBUGS© software.
Finally, 6 trials presenting SDI results and applicable for NMA were included: 5 non-RCTs, with control groups selected by propensity score matching (Kalincik 2018, Kalincik 2015, Kalincik 2017, Barnocini 2016, Guger 2018) and 1 RCT (CARE MS II), allowing for comparison of CT vs FIN, NAT, ALE. Due to the lack of proper data, comparison with OCR was not possible. Additionally, there were only 37 patients treated with CT with SDI data available (Kalincik 2018). NMA results revealed that Hazard Ratios (95% CrI) for achieving 6-month SDI with CT was statistically significantly higher in comparison with all other high efficacy disease modifying treatments studied in this analysis: CT vs FIN – 5,17 (1,81; 15,01), CT vs NAT – 3,06 (1,06; 8,62), CT vs ALE – 9,45 (2,79; 31,94).
Cladribine tablets treatment was associated with higher probability of sustained recovery from disability compared to fingolimod, natalizumab and alemtuzumab in RRMS patients with highly active disease. The conclusion is based on limited quality of identified clinical data.