The 4-H of Biomarkers in Arthritis: A Lot of Help, Occasional Harm, Some Hype, Increasing Hope

Treatment journey in rheumatoid arthritis with biosimilars: from better access to good disease control through cost savings and prevention of nocebo effects

Early diagnosis and treatment of rheumatoid arthritis (RA) are of critical importance to halt the progression of the disease. Optimal use of advanced imaging techniques or biomarkers may facilitate early diagnosis of RA. Even though many disease-modifying anti-rheumatic drugs (DMARDs) are available for RA treatment, biological DMARDs (bDMARDs) offer expanding therapeutic options and good outcomes in patients with RA who do not have a sufficient response to conventional synthetic DMARDs. However, high costs of bDMARDs have limited patient access to optimised disease management and increased the cost burden for healthcare systems. The advent of biosimilars led to significant cost savings driven by price competition among the reference products, which could be beneficial for healthcare systems. Healthcare provider (HCP)–patient communication and informed shared decision-making are crucial to prevent the occurrence of a nocebo effect, which results from negative perceptions that patients may have and could lead to less effective outcomes. Research has demonstrated that effective communication between HCPs and patients utilising positive framing can improve acceptance by patients to be initiated on or switched to a biosimilar and can help to integrate biosimilars into routine clinical practice to maximise benefits for patients with RA.

Predicting Response to Tocilizumab Monotherapy in Rheumatoid Arthritis: A Real-world Data Analysis Using Machine Learning

OBJECTIVE

Tocilizumab (TCZ) has shown similar efficacy when used as monotherapy as in combination with other treatments for rheumatoid arthritis (RA) in randomized controlled trials (RCTs). We derived a remission prediction score for TCZ monotherapy (TCZm) using RCT data and performed an external validation of the prediction score using real-world data (RWD).

METHODS

We identified patients in the Corrona RA registry who used TCZm (n = 452), and matched the design and patients from 4 RCTs used in previous work (n = 853). Patients were followed to determine remission status at 24 weeks. We compared the performance of remission prediction models in RWD, first based on variables determined in our prior work in RCTs, and then using an extended variable set, comparing logistic regression and random forest models. We included patients on other biologic disease-modifying antirheumatic drug monotherapies (bDMARDm) to improve prediction.

RESULTS

The fraction of patients observed reaching remission on TCZm by their follow-up visit was 12% (n = 53) in RWD vs 15% (n = 127) in RCTs. Discrimination was good in RWD for the risk score developed in RCTs, with area under the receiver-operating characteristic curve (AUROC) of 0.69 (95% CI 0.62-0.75). Fitting the same logistic regression model to all bDMARDm patients in the RWD improved the AUROC on held-out TCZm patients to 0.72 (95% CI 0.63-0.81). Extending the variable set and adding regularization further increased it to 0.76 (95% CI 0.67-0.84).

CONCLUSION

The remission prediction scores, derived in RCTs, discriminated patients in RWD about as well as in RCTs. Discrimination was further improved by retraining models on RWD.

Economic considerations on the usage of biologics in the allergy clinic

The advent of biologic therapies has transformed care for severe atopic disorders but their high cost poses new challenges with regard to long-term sustainability and fair allocation of resources. This article covers the basic concepts of cost-utility analyses and reviews the available literature on cost utility of biologic drugs in atopic disorders. When used within their limits as part of a multi-dimensional assessment, economic analyses can be extremely useful to guide decision-making and prioritization of care. Despite the good quality of most cost-utility analyses conducted for the use of biologics in asthma and other atopic diseases, their conclusions regarding cost-effectiveness are extremely variable. This is mainly due to the use of inconsistent estimates of health utility benefit with therapy. Development of reliable and validated instruments to measure disutility in atopic disorders and measure of indirect costs in atopic disease are identified as a priority for future research.