Q: How do you currently individualize multiple myeloma therapy based on disease stage and risk factors?

Cytogenetics and fluorescence in situ hybridization continue to be important for individualized risk assessment and monitoring, and these tests should generally be performed at each bone marrow evaluation. The genetic instability in multiple myeloma is unparalleled in my view. Whole genome sequencing reveals that, at the time that a patient with multiple myeloma is seen, there can be approximately 5000 mutations, and, after remission induction therapy, high-dose melphalan, and transplant followed by maintenance, we have seen more than 12,000 mutations at the time of relapsed disease. The scope of mutagenic thrust was enormous. However, until specific abnormalities are matched with specific therapies that are effective for them, we have a challenge. In that regard, t(11;14) has been an exception and a potential major breakthrough, since data show that targeted investigational therapy with venetoclax has anti-myeloma activity in relapsed/refractory patients with t(11;14). Additionally, in my experience, 17p deletion (del[17p]) has poor prognostic significance regardless of the abnormalities that accompany it. So, when I see a patient with del(17p), I consider being more proactive by adding another therapeutic layer, such as an antibody and/or a proteasome inhibitor (PI) or other agent. Other cytogenetic information, such as 1q amplification, which is quite common in multiple myeloma, can also be helpful. 1q amplification is associated with MCL-1—and we know that MCL-1 is important in proteasome inhibition; thus, I may more aggressively optimize the delivery of the PI in that context. Finally, it is important to recognize the value of imaging in assessing the individual patient’s disease. When we test a patient who has had biochemical relapse—however early—additional imaging (ie, positron emission tomography [PET]–computed tomography [CT]) can be quite useful and may reveal a greater extent of disease than was anticipated, based on biomarkers alone. Genetic testing can be helpful, but, in my opinion, it is not the be-all and end-all in multiple myeloma risk stratification just yet. Thus, we must still take many other factors into consideration as we risk-adapt and tailor therapy.

With regard to the individualized treatment of multiple myeloma, I agree that we are just beginning to see the first real differentiation now with t(11;14), which formerly was known as BCL-1 and we now know as cyclin-D1. It has been shown in clinical trials for multiple myeloma that t(11;14) is associated with a high response rate to venetoclax. Although the presence of t(11;14) does seem to predict response quite well, venetoclax also appears to be effective in patients without t(11;14)—but not quite as effective. Aside from that example, individualizing treatment for multiple myeloma is really more of an art than a science at this point, in part because our tools to risk-stratify patients for specific therapies are limited. We know that certain agents are effective in overcoming resistance, such as the PIs, but I generally use these agents anyway. In our practice, we reserve bone marrow tests for diagnosis, to understand bone marrow dysfunction, or to secure a patient’s place in a clinical trial. Soluble B-cell maturation antigen is useful in following patients who do not have significant levels of paraprotein, which is often lost during the course of disease. But, in terms of assessing clinical status, we find bone marrow of minimal use because of the heterogeneity of the bone marrow involvement in patients with multiple myeloma. Other aspects of individualization include prior treatment, response to and tolerability of prior agents, and cost and convenience issues. Most patients prefer pill-based treatment, but this type of treatment often carries the potential for adherence issues, especially in older patients. Ultimately, many factors come into play in the individualization of treatment, not just markers of high-risk disease.

As Dr Berenson outlined, our ability to individualize treatment still relies primarily on patient preferences and clinical factors rather than on our ability to target and modify disease risk factors. We have an understanding of disease risk, but we do not have sufficiently robust data to support individualized treatment based on that risk. Further, although we have the ability to identify high-risk patients, we do not yet have the data to tell us that a given therapy is clearly superior to another in that patient population. As indicated earlier, emerging data support the use of venetoclax in patients with t(11;14); these are likely the most robust data we have favoring the use of 1 specific agent in the presence of a specific cytogenetic abnormality. Patients with del(17p) have a poor prognosis, and the data indicate that PIs are helpful in this population; however, these patients still have a poor prognosis, despite the use of PIs. PET-CT (or whole-body magnetic resonance imaging) is a definite advance over our prior skeletal imaging, and such imaging helps to identify disease when paraprotein levels are only slightly elevated. The new markers are provocative and interesting, but we are still in the research phase and are not yet able to dial back therapy based on clinical trial data. Hopefully, over time, we will be able to better understand disease features.