Waiting for JAK inhibitor safety data

The US Food and Drug Administration (FDA) has recently added a new 'black box warning' on all currently approved Janus kinase (JAK) inhibitors indicated for the treatment of arthritis and other inflammatory conditions based on results from the ORAL Surveillance study of tofacitinib versus tumour necrosis factor alpha inhibitors in rheumatoid arthritis. This is a warning difficult to ignore because the data, being from a randomised controlled trial, are of high fidelity and hard to reproach. It is especially problematic because safety data for all the other JAK inhibitors will be pending for several years. So how might we proceed, without being bound by our stasis? The lack of absolute certainty seems to require a pragmatic approach to the routine care use of JAK inhibitors. The patients who were at greatest risk were older and had other risk factors for the corresponding adverse events, in keeping with effect modification. This highlights the need to focus on risk stratification when tailoring therapy. In this viewpoint, we propose a simple illustration to guide clinical decision-making. First, identify general risk factors for venous thromboembolic event (VTE), major adverse cardiac event (MACE) and cancer (age>65 years and smoking) and whether there is a previous history of VTE, MACE or cancer. Then, evaluate risk based on the number of other risk factors for VTE and the number of other risk factors for MACE. Ultimately, 'treat-to-target' will in the end always be 'treat-to-agreement'. As we have done in the past, and will do in the future, the optimal treatment strategy will have to be tailored based on individual patient risk factors and preferences in a shared-decision process.

Automated summary

This article discusses the recent addition of a 'black box warning' on Janus kinase (JAK) inhibitors used in the treatment of arthritis and other inflammatory conditions by the US FDA. The article highlights the importance of risk stratification and tailored therapy based on individual patient risk factors, proposing a simple illustration to guide clinical decision-making.