If the prognosis for patients with chronic lymphocytic leukemia (CLL) could be identified at the time of diagnosis, oncologists would have better opportunities to adjust patients’ therapeutic and follow-up strategies. A new correlation discovered between specific molecular features of the disease and subgroups of patients with different prognoses could make this possible.
Chronic lymphocytic leukemia is an incurable tumor disease that can progress very differently in different patients. Some patients require therapy relatively soon after diagnosis whereas others can live for a long time with their disease, even without treatment. Thus, it is important to identify features of the disease that can be associated with a good or poor prognosis. Ideally, these features would be present at diagnosis and remain stable throughout the evolution of the disease.
In this study, published in Lancet Haematology (2014; doi:10.1016/S2352-3026(14)00005-2), researchers analyzed samples from more than 8,500 patients with CLL. These were classified into subsets based on the expression of very similar B-cell receptors in the white blood cells that grow uncontrolled in CLL. When they studied the disease course for patients in the different subsets they found a clear correlation.
“It was evident that patients within a specific subset followed the same clinical course and that this was different from patients in other subsets. For example, patients in subset #2 showed an aggressive disease course, with an average time to first treatment of only 2 years. On the other hand, subset #4 patients had an indolent disease that did not require treatment until after, on average, 11 years,” said Panagiotis Baliakas, MD, PhD student at the Department of Immunology, Genetics, and Pathology at Uppsala University in Sweden, and one of the coordinators of the study.
Integrating the classification based on similar B-cell receptors with other prognostic markers will also refine the prognostication of patients with CLL and increase the possibilities to identify patients that are already at high risk at the time of diagnosis.
“But it is also important, both for medical and psychosocial reasons, to be able to identify patients with the lowest probability of requiring treatment, especially considering that these subsets are enriched for young patients who could be reassured about the indolent nature of their disease,” said Baliakas.