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| Dr. Joan Merrill |
When new treatments are tested in clinical trials, the FDA and the drug companies know about these issues, but the challenge is to come up with a simple protocol that can be tested on all kinds of different patients around the world and can answer two simple questions. Is the treatment reasonably safe and does it work better if you do give it than if you don’t give it? If these two conditions are met, the regulatory agencies can consider approving it for use in the clinic.
Think about this question, though: Does a treatment work better if you do give it than if you didn’t give it? To answer this question you just need more people to get better in a group who get the drug than in a group that receives placebo (or dummy treatment). So to answer this question it doesn’t matter if up to half the people participating in a clinical trial were never going to benefit from this treatment in the first place. In fact less than half of the people around the world who took Benlysta in the large international Phase III trials actually met the criteria for improvement. Still it did well enough to be approved, now, in a growing number of countries worldwide.
Here are the important questions that have not been answered by that simple question: Which patients are more likely to benefit from Benlysta? How can the dose be optimized for an individual patient? How can we tell, in patients for whom it is not working whether it will never work for them (in which case it should be stopped) or whether it might be of significant benefit if the amount of dose, timing of the dose, or combinations with other medications could be optimally adjusted? The answers to all of these things needs to be worked out and the fact that the FDA has approved Benlysta at only one dose to be given only at rigid monthly intervals is not helping matters.
But even if doctors in clinic were given more flexibility to practice the art of medicine in treating patients with new expensive biologics, it would be difficult to address these important questions about how best to treat individual patients using information from the clinical trials. Remember that a wide range of patients from all over the world, with disparate individual differences in their immune system were treated with Benlysta while still taking various additional lupus treatments, all of which are already at work changing the immune system of each of these patients in different ways. This superimposes a whole lot of treatment influences onto what we already know are different background immune disorders in the patients. In trying to figure out who is more likely to get benefit from Benlysta or how best to treat those individuals it will be difficult to sort all of this out.
How will we sort all of this out? I want to tell you about our recent study that a large team of doctors and scientists have recently completed as a collaboration between the Oklahoma Medical Research Foundation and Pfizer Pharmaceuticals. The name of the study is BOLD which stands for Biomarkers of Lupus Disease. Biomarkers are detailed bits of biological information that can be picked up from a simple blood test which can be used to sort out very complex questions about individual differences that perturb the balance of the immune system. Some biomarkers that are active in some patients might suggest a disorder that Benlysta could fix. Others might suggest that different types of treatments would be better. Importantly, it has been hard to figure out in any previous studies what the impact of all the various lupus treatments are on these biomarkers which might really confuse a doctor if they were trying to pick out a treatment to either add on or switch a patient to. The BOLD study was designed to begin looking at this very question. Patients who agreed to be in the study were considered qualified to participate if they had active disease, but at the start of the study they could be on various background treatments. A blood sample was taken. After that, unlike most clinical trials, the strong background immune suppressants were stopped. Everyone received a short course of steroids. More blood was sampled when the participants were better. The steroid was allowed to wear off. The patients were followed closely with serial blood donations and they were instructed to return to clinic within three days if their symptoms came back. When a “flare” visit occurred, blood was drawn once more and then the patient was immediately treated.
Before this, almost everything known about biomarkers in lupus has been based on random samples of blood from biologically diverse patients on a cacophony of background medications. Now there is a freezer full of samples donated by patients where we can address biologic diversity by comparing the same patient with active disease on azathioprine (or the other immune suppressants) to themselves when they flare up without that treatment on board. This is how we can learn what the real impact of these agents on lupus is and how some of them, when they are allowed to be used during trials, could be interfering with certain drugs we are trying to study. In the past two years some preliminary data from the BOLD study has already been presented at the American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) meetings. Now that the study is completed, the full reports will be out in the next year.
It is well known that lupus patients can be sorted into two major groups, those with inflammation that seems strongly influenced by interferon alpha and those with a much lower interferon influence. The preliminary abstracts that have already been released from the BOLD study are suggesting that many other factors that distinguish one patient from another, including the impact of immune suppressants, might be better understood by appreciating that they have different impacts on the interferon low and high groups. A better understanding of how to sort lupus into biologically meaningful subsets, and the biologic influence of background treatments on each of these groups may help to better design and interpret clinical trials as well as to inform better and more precise medical care for individual people in the future...not just for 50% of the people.
