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Use of tofacitinib and baracitinib with MTX is safe and
effective intervention for treatment of RA patients with an inadequate response
to DMARDs or biologics.
The researchers of Korea University Anam Hospital and Hanyang University Hospital for Rheumatic Diseases discovered that Baricitinib 4 mg + methotrexate (MTX) and Tofacitinib 10 mg + MTX show a significant response among the RA patients who were unable to respond to biologics or DMARDs. For the patients who show no progression in health after the biologics or DMARDs treatment, JAK inhibitors are one the suitable approach. JAK inhibitors work by inhibiting the action of one or more of the Janus Kinase that begins immune and inflammatory responses seen during rheumatoid arthritis (RA).
This study assessed the relative safety and efficacy of JAK inhibitors; Baricitinib and Tofacitinib in managing RA. Bayesian network meta-analysis was performed to associate direct and indirect data from randomized controlled trials (RCTs).
A total of 12 RCTs with 5883 patients were selected.
Fifteen pairwise comparisons were found with 6 treatments and 10 direct comparisons.
The most efficient approaches for active RA with an ineffectual DMARD or
biologic response noticed was Baricitinib 4 mg + MTX and Tofacitinib
10 mg + MTX; which was following by Tofacitinib 5 mg + MTX, Adalimumab + MTX,
and Baricitinib 2 mg + MTX. As per the ranking probability (on the basis of
surface under the cumulative ranking curve (SUCRA)), the best strategy that
obtain the ACR20 response rate was Tofacitinib 10 mg + MTX followed by
Baricitinib 4 mg + MTX, Baricitinib 2 mg + MTX, Tofacitinib 5 mg + MTX,
Adalimumab + MTX, and placebo + MTX. No particular differences were noticed
among the groups regarding adverse events. The above findings explain the
combination of MTX with 10 mg Tofacitinib and 4 mg Baricitinib is the most
effective strategy to treat RA.
Zeitschrift für Rheumatologie
Comparison of the efficacy and safety of Tofacitinib and Baricitinib in patients with active rheumatoid arthritis: a Bayesian network meta-analysis of randomized controlled trials.
S.-C. Bae, Y. H. Lee
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