That’s definitely another area of inquiry. So I’m a physician-scientist based in Tübingen and we, of course, as all hematologists, so in acute myeloid leukemia, this is really a different setting from the high-grade B-cell lymphoma because this is a disease that really has a high burden on patients, the outcomes are still not good and we have seen advancements but there is still a very major unmet need to have better options...
That’s definitely another area of inquiry. So I’m a physician-scientist based in Tübingen and we, of course, as all hematologists, so in acute myeloid leukemia, this is really a different setting from the high-grade B-cell lymphoma because this is a disease that really has a high burden on patients, the outcomes are still not good and we have seen advancements but there is still a very major unmet need to have better options. So half of AML patients still go on to receive allogeneic transplant, which really exacts a high toll on these patients. And so one focus is really to optimize the question, which patients and at what time point they should receive this transplant, how many patients could be possibly spared transplant and how to optimally guide the transplant and also post-transplant monitoring.
And one option to do this is of course, measurable residual disease. For many types of AML, there are not very well-validated markers. So we have flow MRD, NGS MRD, but there are problems with inter-institutional validation. But for patients with NPM1-mutant AML, we have qPCR-based MRD, which is very, very sensitive, 10 to the power of minus 5 or minus 7, and has a very high predictive value.
Now, one thing that we noticed when we started to think about this is there are very good data sets on pre-transplant MRD, there are good data sets on post-induction MRD to decide which patients should or which patients might derive a benefit from transplant, but when it comes to actually the prognosis after transplant based on the pre-transplant and the early post-transplant MRD measurements, there’s also really a scarcity of data.
So the setting is basically you have a patient who just received a transplant for refractory leukemia or high-risk leukemia. You have them at day 30 post-transplant, maybe in a bad condition in the clinic, and then you do an MRD measurement. And in a considerable amount of patients, this measurement will be positive at day 30. This is actually what we see at our center. And many published cohorts include many trial patients that were actually transplanted in first complete remission which is not the really clinical situation that you have for most of these patients. Most will be transplanted at a later time point and not in complete remission also. So many patients will be MRD positive and then the question is what do you do? On day 30, these patients have a long journey, a lot of toxicity potentially. Do you tell them the disease is still there, we need to do something, do you tell them we can just watch and wait?
And the interesting thing that we see in our data in Tübingen, which represents only one center, but is already as large a cohort as the largest that is published so far, especially when it comes to annotation of this time point, we see that at the early time point positivity is not the best indicator of impending relapse, but actually a numerical threshold. So actually, it’s not patients that are positive that are at the highest risk, but only patients that are positive above a certain threshold in the allelic ratio.
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