CoMMpass Study data helps identify “Double-Hit “ patients, a possible new classification of high-risk myeloma.

Researchers have long known that the early identification of high-risk myeloma patients is important in improving outcomes for this patient group. Early identification, at the time of diagnosis, would mean high risk patients could be more closely monitored, and may indicate a different standard of care treatment is needed up front, compared to low or intermediate risk patients. The problem facing researchers is exactly how to easily and accurately identify high-risk patients. This past month, researchers published a paper identifying potential new high-risk markers for myeloma patients, and CoMMpass data played a prominent role in this discovery.

This effort, led by researchers from the Dana Farber Cancer Institute, Celgene Corp., and University of Arkansas for Medical Sciences, examined and compared the gene sequences and clinical characteristics of 784 newly diagnosed myeloma patients (553 of them from the CoMMpass study), what their treatment regimens were, and their outcomes. They found that patients who had both 1q amplification as well as deletion of 17p (del17p), a population that they termed Double-Hit MM, exhibited very poor prognosis despite receiving the most modern standard of care at diagnosis. This Double-Hit group accounted for 6.1% of the total MM patient population studied.

This finding is important because this population was not previously identified as high risk. If these results are borne out by further research, analysis of all newly diagnosed MM patient samples for these 2 easily detectable markers could earmark this Double-Hit population to receive novel therapeutic approaches, based on their poor prognosis when receiving the usual standard of care.

Discoveries of this type can only be made by analyzing large, freely available patient data sets such as the one collected in the CoMMpass study.  As we continue to collect patient data in CoMMpass over the next 5 years, we look forward to researchers using this data to fuel even more exciting discoveries, and accelerating new and more precise therapies into the clinic for myeloma patients.

https://www.nature.com/articles/s41375-018-0196-8