A few weeks ago, the FDA approved edoxaban, the fourth to market new oral anticoagulant (NOAC), with a Black Box Warning that the drug is contraindicated for patients with a creatinine clearance ≥ 95. Since the FDA Advisory Panel in December, there have been many questions as to whether the FDA would approve an untested higher dose based on an exposure model, which lead to the contraindication. This is the first time that a higher untested dose has been approved by the FDA, and the first time that physicians will not be able to use an agent in their healthier patients.
The FDA ruling brings up a number of questions. First, the data suggest that this population (those with a creatinine clearance ≥ 95) is actually very limited among patients with atrial fibrillation (AF). The condition is typically associated with elderly patients who usually present with a creatinine clearance of less than 95. But the FDA’s action is puzzling in light of the fact that edoxaban also has an indication for DVT and PE, both of which have no Black Box warning for this population. Edoxaban was reviewed by two separate arms of the FDA which is the reason for the difference n the way the drug is labeled for AF and DVE/PE. However, doctors are unsure of what to do. While many of the physicians who see DVT and PE patients do not see AF patients, there will be some overlap.
Second, why is the issue of creatinine clearance not a class effect? The three agents on the market (dabigatran, rivaroxaban, and apixaban) did not receive the same Black Box Warning, but many physicians are already asking if the FDA will go back to the three agents for similar data. All signs in the edoxaban data point to the fact this is a class effect and that the other agents’ trials should be investigated to see their effect in this population.
Finally, the question with greatest impact to the pharmaceutical industry at large is whether the FDA reliance on exposure data should outweigh the clinical data that is included in the trial outcomes. The exposure data is often based on modeling, which does not always consider both safety and efficacy. Basing approvals on only half of the information could have serious ramifications as outcomes are evaluated in a real world setting. Is modeling able to reveal potential negative impacts on individual patients? If the FDA continues a reliance on models, then time will tell.