Serum TNFα levels at 24 h after certolizumab pegol predict effectiveness at week 12 in patients with rheumatoid arthritis from TSUBAME study

Modulation of Interleukin-23 Signaling With Guselkumab in Biologic-Naive Patients Versus Tumor Necrosis Factor Inhibitor-Inadequate Responders With Active Psoriatic Arthritis

OBJECTIVE

We assessed and compared immunologic differences and associations with clinical response to guselkumab, a fully human interleukin (IL)-23p19 subunit inhibitor, in participants with active psoriatic arthritis (PsA) who were biologic-naive or had inadequate response to tumor necrosis factor inhibitors (TNFi-IR).

METHODS

Serum biomarker levels at baseline and after treatment with guselkumab 100 mg every 8 weeks were compared between biologic-naive (n = 251) and TNFi-IR (n = 93) subgroups identified in the pooled DISCOVER-1/DISCOVER-2/COSMOS data set. Baseline biomarker levels determined by achievement of week 24 clinical responses (≥75%/90% improvement in Psoriasis Area and Severity Index [PASI 75/90], Investigator's Global Assessment [IGA] of psoriasis score 0/1 and ≥2-point improvement], ≥20% improvement in American College of Rheumatology criteria [ACR20]) were compared between prior treatment subgroups.

RESULTS

Baseline IL-22, TNFα, and beta defensin-2 (BD-2) levels were significantly lower in biologic-naive than in TNFi-IR participants. With guselkumab, week 24 IL-17A, IL-17F, IL-22, serum amyloid A, C-reactive protein, IL-6, and BD-2 levels were significantly reduced from baseline in biologic-naive and TNFi-IR participants (≥1.4-fold difference, nominal P < 0.05). Clinical responders to guselkumab exhibited significantly higher baseline levels of several biomarkers than nonresponders (IL-17A, IL-17F, BD-2 in biologic-naive PASI 90 responders; IL-17A, BD-2 in TNFi-IR IGA 0/1 responders; IL-22, BD-2 in TNFi-IR PASI 90 responders [nominal P < 0.05]) and trended higher in TNFi-IR ACR20 responders.

CONCLUSION

Guselkumab modulates IL-23 signaling and provides consistent pharmacodynamic effects in both biologic-naive and TNFi-IR PsA patients. Significantly elevated baseline IL-22, TNFα, and BD-2 levels and associations between baseline IL-22, IL-17A, and BD-2 levels and skin responses to guselkumab suggest greater dysregulation of IL-23/Th17 signaling in patients with TNFi-IR.

Comparative analysis of low-field magnetic resonance imaging in patients with rheumatoid arthritis treated with certolizumab pegol or infliximab

OBJECTIVES

The aim is to clarify the differences in magnetic resonance imaging (MRI) findings between rheumatoid arthritis (RA) patients treated with certolizumab pegol (CZP) and infliximab (IFX).

METHODS

The study included RA patients who received CZP or IFX and were examined with low-field MRI (compacTscan; compact magnetic resonance imaging) at the beginning and again within 6 months of treatment initiation. Comparisons were made regarding background, clinical course, and differences in MRI findings following initiation of tumour necrosis factor inhibitors between the CZP and IFX treatment groups. MRI findings were evaluated by scoring erosion, bone marrow oedema (BME), and synovitis.

RESULTS

Ten cases in CZP and 18 cases in IFX group were compared. The biologic disease-modifying antirheumatic drug-naïve rate in the IFX group was significantly higher than that in the CZP group. After 6 months, disease activities were significantly decreased from baseline in both groups. Erosion score did not change significantly in both groups after 6 months. BME score was significantly decreased in the CZP group after 6 months, whereas in the IFX group, there was no significant change. Synovitis score was significantly decreased in both groups after 6 months.

CONCLUSIONS

The findings of our study suggest that, in patients with RA, CZP might improve BME more effectively than IFX.

Effects of RETN polymorphisms on treatment response in rheumatoid arthritis patients receiving TNF-α inhibitors and utilization of machine-learning algorithms

This study was designed to investigate the effects of polymorphisms in RETN on remission in RA patients receiving TNF-α inhibitors. In addition, machine learning algorithms were trained to predict remission. Ten single-nucleotide polymorphisms were investigated. Univariate and multivariable analyses were performed to evaluate associations between genetic polymorphisms and the efficacy of TNF-α inhibitors. A random forest-based classification approach was used to assess the importance of different variables associated with the efficacy of TNF-α inhibitors. Various machine learning methods were used for finding vital factors and prediction of remission. The eight most significant features included in the multivariable analysis were sex, age, hypertension, sulfasalazine, rs1862513, rs3219178, rs3219177, and rs3745369. T-allele carriers of rs3219177 and males showed approximately 6.0- and 3.6-fold higher remission rates compared to those with the CC genotype and females, respectively. The elastic net algorithm was the best machine-learning method for predicting remission of patients with RA treated with TNF-α inhibitors. On the basis of the results of this study, it may be possible to design individually tailored treatment regimens to predict the efficacy of TNF-α inhibitors.

Recent progress in treatments of rheumatoid arthritis: an overview of developments in biologics and small molecules, and remaining unmet needs

Through treatment with biological DMARDs (bDMARDs) or targeted synthetic (tsDMARDs) such as Janus kinase (JAK) inhibitors in addition to MTX, clinical remission has become a realistic therapeutic goal for the majority of patients with RA, and sustained remission facilitates prevention of joint damage and physical dysfunction. Long-term safety and sustained inhibition of structural changes and physical dysfunction by bDMARDs have been reported. The development of next-generation bDMARDs and expansion of their indications to various autoimmune diseases are expected. Five JAK inhibitors show comparable efficacy to bDMARDs, and the latest ones are effective for overcoming difficult-to-treat RA regardless of prior medications. Patients treated with JAK inhibitors should be adequately screened and monitored for infection, cardiovascular disorders, thrombosis, malignancies and so on. Advances in therapeutic strategies, including the differential use of therapeutic drugs and de-escalation of treatment after remission induction, are prioritized.

Recent Advances in Understanding the Pathogenesis of Rheumatoid Arthritis: New Treatment Strategies

Rheumatoid arthritis (RA) is considered a chronic systemic, multi-factorial, inflammatory, and progressive autoimmune disease affecting many people worldwide. While patients show very individual courses of disease, with RA focusing on the musculoskeletal system, joints are often severely affected, leading to local inflammation, cartilage destruction, and bone erosion. To prevent joint damage and physical disability as one of many symptoms of RA, early diagnosis is critical. Auto-antibodies play a pivotal clinical role in patients with systemic RA. As biomarkers, they could help to make a more efficient diagnosis, prognosis, and treatment decision. Besides auto-antibodies, several other factors are involved in the progression of RA, such as epigenetic alterations, post-translational modifications, glycosylation, autophagy, and T-cells. Understanding the interplay between these factors would contribute to a deeper insight into the causes, mechanisms, progression, and treatment of the disease. In this review, the latest RA research findings are discussed to better understand the pathogenesis, and finally, treatment strategies for RA therapy are presented, including both conventional approaches and new methods that have been developed in recent years or are currently under investigation.

Possibilities for personalised medicine in rheumatoid arthritis: hype or hope

Knowledge of pathophysiology of rheumatoid arthritis (RA) has improved over the past decades, which resulted in new treatment options and strategies that led to better clinical outcomes. At the same time, we have come to understand that RA is a heterogeneous disease on a clinical as well as a pathophysiological level. Despite this heterogeneity, current management recommendations still adopt a ‘one-size-fits-all’ treatment approach, where ideally individualised treatment, or personalised medicine, is preferred. The first step towards personalised medicine in RA would be to designate different treatment strategies to distinct clinical or molecular phenotypes of patients. This viewpoint discusses current evidence and elaborates on future possibilities for personalised medicine in RA.