Management of rheumatoid arthritis: consensus recommendations from the Hong Kong Society of Rheumatology

Given the recent availability of novel biologic agents for the treatment of rheumatoid arthritis (RA), the Hong Kong Society of Rheumatology has developed consensus recommendations on the management of RA, which aim at providing guidance to local physicians on appropriate, literature-based management of this condition, specifically on the indications and monitoring of the biologic disease-modifying anti-rheumatic drugs (DMARDs). The recommendations were developed using the European League Against Rheumatism (EULAR) recommendations for the management of early arthritis as a guide, along with local expert opinion. As significant joint damage occurs early in the course of RA, initiating therapy early is key to minimizing further damage and disability. Patients with serious disease or poor prognosis should receive early, aggressive therapy. Because of its good efficacy and safety profile, methotrexate is considered the standard first-line DMARD for most treatment-naïve RA patients. Patients with a suboptimal response to methotrexate monotherapy should receive step-up (combination) therapy with either the synthetic or biologic DMARDs. In recent years, combinations of methotrexate with tocilizumab, abatacept, or rituximab have emerged as effective therapies in patients who are unresponsive to traditional DMARDs or the anti-tumor necrosis factor (TNF)-α agents. As biologic agents can increase the risk of infections such as tuberculosis and reactivation of viral hepatitis, screening for the presence of latent tuberculosis and chronic viral hepatitis carrier state is recommended before initiating therapy

Tumor necrosis factor-α blockade treatment decreased CD154 (CD40-ligand) expression in rheumatoid arthritis

CD154 (commonly referred to as CD40-ligand) is a critical T cell factor that participates in the pathogenesis of autoimmune and is over-expressed in rheumatoid arthritis (RA). TNF-α blockade treatment had dramatic efficacy in RA.To investigate whether TNF-α blockade treatment can inhibit CD154 expression in RA.Blood samples were collected from 33 patients with rheumatoid arthritis before and 3 months after TNF-α blockade treatment. Clinical serological data determined by standard assays and T cell CD154 expression levels determined by flow cytometry were statistically analyzed for these two time points.The percentage of CD154 expression on gated CD4+ T cells of PBMCs from RA patients after 3 months TNF-α blockade treatment was significantly lower than before treatment (2.94 ± 3.21% vs. 7.21 ± 5.64%; p = 0.0001). The disease activity and anti-CCP antibody levels were also significantly reduced after TNF-α blockade treatment. The CD154 expression levels were positively correlated with disease activity index DAS28, and CRP. The post-stimulated CD154 expression percentage of purified CD4+ T cells between baseline and after TNF-α blockade treatment was not significantly different (p = 0.221). Baseline CD154 levels were positively correlated with treatment-induced changes in DAS28 (p = 0.014; r2 = 0.187).TNF-α blockade treatment significantly decreased the CD154 expression on CD4+ T cells, disease activity and anti-CCP antibody simultaneously in RA patients. However TNF-α blockade did not impair T cell capacity to express CD154 after stimulation. These results suggest that decreased CD154 expression after TNF-α blockade may be due to decreased RA disease activity but not direct inhibition of CD154 responsiveness of T cells

Evidence of effectiveness: How much can we extrapolate from existing studies?

Drug development can be a science of extrapolation if the use of a drug exposure-response relationship is embraced and implemented through mechanistically oriented pharmacokinetic (PK)-pharmacodynamic (PD) modeling analysis and clinical trial simulation. The traditional requirement of at least 2 adequate and well-controlled phase III studies by the US Food and Drug Administration for drug approval can be waived in certain situations, substantially reducing the resources and time. In this article, the authors introduce a real drug development case where the chance for this exemption was maximized by actively using PK-PD modeling followed by clinical trial simulation, resulting in faster and more economical introduction of a new dosage regimen to patients