Medscape reached out to Richard Stone, MD, a CML expert at Dana-Farber Cancer Institute in Boston, to find out more about these developments.
Medscape: What criteria are generally used to determine if a patient can try for treatment-free remission?
Dr Richard Stone
Dr Stone: There are potential “requirements,” but we commonly select patients who have been on a tyrosine kinase inhibitor (TKI) for a minimum of at least 3 to 5 years and who have achieved a deep molecular remission of MR 4-4.5 or about 0.002% or less on the international scale for the most recent 2-year period. Thus, the more prolonged and profound the remission on the TKI, the better chance to achieve a successful treatment-free remission. Those are the most important clinical predictors.
After discontinuation, success is defined as not having to restart the TKI. A 2-year duration of molecular negativity is a harbinger for a much more successful treatment-free interval.
Restarting the TKI is generally only done if major molecular response is lost. In other words, you want to be below 0.002% on the international scale before you stop, and you don’t need to restart until the polymerase chain reaction (PCR) for BCR-ABL1 exceeds 1% on the international scale. However, some physicians suggest restarting at a lower level of disease. For example, if you go from 0.002% to 0.02%, with the latter finding confirmed on repeat testing a month or so later, the patient has a high likelihood of going above 0.1%.
Are there other available biomarkers that can reliably predict treatment-free remission in CML?
There are no lab tests other than those related to the PCR itself (including the transcript type) that predict treatment-free remission. The factors are clinical, such as how long the patient has been on the drug, if the patient has had any signs of resistance to the TKI, if the patient has been at a low PCR level for a long time before stopping the drug, and if the patient’s PCR level at the time of stopping is very, very low.
Those are all good things. Those are used clinically to predict treatment-free remission. When you are counseling a patient, you take those factors into consideration.
What are the key results from the recent study by Irani and colleagues?
The main finding is that you can predict who is likely to have a successful treatment-free interval, defined as a prolonged time off a TKI, by measuring immune effector cells status.
Specifically, they derived a relatively complicated algorithm for predicting who is going to be able to stay off a TKI, which was termed the effector-suppressor score. This score is based on the NK cell number for the effector part. The more NK cells, presumptively, the more the immune system can control wayward CML clones. If T-reg cells and monocytic myeloid-derived suppressor cell counts were low, this would indicate an immune system relatively less capable of controlling the anti-CML effect. The idea of lots of attack cells and diminished anti-attack cells is simple, but the effector-suppressor score itself is complicated.
Can you comment on the practical aspects of using this effector-suppressor score in patients with CML in clinical practice?
The effector-suppressor score involves a complicated mathematical equation, and it’s not going to be easily adopted by clinicians. The NK cells, T-regs, and monocytic myeloid-derived suppressor cells aren’t routinely measured in the clinic, so clinical labs capable of readily performing these assays would be required.
Having said that, this study uncovers some highly relevant biology confirming that the immune system and TKIs work together to control CML. Moreover, could the immune system be manipulated to allow more patients to have a successful treatment-free remission?
However, near-term, common use of the effector-suppressor score outside of a research setting is not likely, especially in view of the relative ease of using clinical parameters to determine who should stop their TKI.
If it were used, how would the effector-suppressor score improve clinical practice and patient outcomes?
Clinicians could more accurately counsel a patient concerning their likelihood of being able to stay off a TKI. You could then decrease anxiety in your patient who has enjoyed stability on their TKI for years, [assuring them] that it is very safe to stop. Secondly, with more-accurate predictors of success, the frequency of post-discontinuation monitoring could be potentially reduced.
Do we know anything about the cost of using this effector-suppressor score?
It is difficult to determine what the cost of this approach might be. At the moment, the main cost of TKI discontinuation is that it’s associated with more-frequent PCR monitoring (with the exception of the obvious savings of not paying for the TKI). Better prediction of who could achieve a prolonged treatment-free remission could be cost-effective if monitoring costs were decreased.
In 2019, a study by Claudiani and colleagues introduced another predictive score for the successful treatment of CML. How does this score work?
The score involves several variables at the clinician’s fingertips, including duration of MR4, previous TKI resistance, age at diagnosis, and transcript type. After noting that these parameters were each independently predictive, they developed a predictive score, which was able to identify a good-risk population, an intermediate-risk population, and a poor-risk population for treatment-free remission.
Without knowing it, clinicians use an “intrinsic variant” of this score to decide who can reasonably stop their TKI. It’s a much easier score to use than the one recently proposed by Irani and colleagues. Although the parameters are straightforward and available, a complex equation is nonetheless required.
How do these separate scoring systems compare, in terms of their clinical applicability and overall potential?
From the clinician’s standpoint, the Claudiani score requires available variables, which makes it preferable to the Irani effector-suppressor score. On the other hand, the Irani score being based on immunology could be biologically relevant and even suggest interventions to improve long-term outcomes. Because of the ease of just stopping the TKI in a patient with a recent long and deep remission — and restarting if major molecular response is lost — the Claudiani score is rarely used now.
How often do patients with CML achieve treatment-free remission?
About 40%-50% of the time, overall.
What drugs are associated with achievement of treatment-free remission in CML?
All 5 TKIs are used for CML. Imatinib has been around the longest time. The three second-generation TKIs are nilotinib, dasatinib, and bosutinib. The third-generation TKI is ponatinib. Because patients who go on ponatinib generally have few other options and have advanced disease, treatment-free remission after use of this agent would be very common.
Stone has disclosed no relevant financial relationships.
Kate O’Rourke is a freelance writer in Portland, Maine. She has covered the field of oncology for over 10 years.
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