Telitacicept demonstrates high probability of efficacy in myasthenia gravis: a Bayesian real-world study

This real-world study evaluated the efficacy and safety of telitacicept, a dual BAFF/APRIL inhibitor, in patients with generalized myasthenia gravis (MG).

In this retrospective study, 17 myasthenia gravis patients on stable background therapy received weekly subcutaneous telitacicept (160-240 mg). Efficacy was evaluated at 12/24 weeks using a primary composite endpoint (≥2-point MG-ADL and ≥3-point QMG reduction). A pre-specified Bayesian analysis, updating a conservative prior with observed data, was employed to determine the posterior probability of treatment success and its 95% credible interval. Safety and steroid-sparing effects were also assessed.

Of the 15 patients evaluable for efficacy (≥12 weeks treatment), 12 (80.0%) met the composite efficacy endpoint. Significant improvements were observed: mean MG-ADL decreased from 8.0 ± 4.4 to 4.2 ± 3.1 (p < 0.01); mean QMG decreased from 13.8 ± 5.5 to 7.6 ± 4.3 (p < 0.01). A robust steroid-sparing effect was demonstrated: the mean daily prednisone dose decreased by 76.0% (10.41 ± 7.30 mg to 2.50 ± 3.21 mg, p < 0.05), with 3 patients achieving complete withdrawal. Five patients attained Minimal Symptom Expression. Bayesian analysis yielded a posterior mean efficacy rate of 66.67% (95% CrI: 49.99-81.43%), with a probability (P) of exceeding 50% efficacy at 97.49%. Treatment was well-tolerated: only mild, transient AEs occurred (one injection-site reaction, one gastrointestinal event leading to withdrawal), and no serious adverse events (SAEs) were reported.

This real-world study utilizing Bayesian analysis provides evidence supporting a high probability of efficacy for telitacicept in AChR-Ab-positive MG, demonstrating significant symptom improvement, substantial steroid-sparing effects, and favorable safety. These findings complement prior randomized controlled trial data and support the use of telitacicept in clinical practice. Study limitations include retrospective design and small sample size.