Telomere analysis to predict chronic lymphocytic leukemia outcome: a STELA test to change clinical practice?

Abstract

Defining the prognosis of individual chronic lymphocytic leukemia patients remains a significant clinical challenge. Consequently, there is a need to identify tests that can provide reliable personalized risk assessments. Here we discuss the problems associated with the currently used prognostic markers and emphasize the potential for using high-resolution telomere length analysis (STELA) for the accurate prediction of clinical outcome. Given the development of targeted, less toxic therapeutics in chronic lymphocytic leukemia, it is crucial to accurately identify those patients who might benefit from early treatment and equally those who may not require treatment at all. In this context, there is also a clear need for dependable predictive markers of response to drugs so that optimal treatment decisions can be made for individual patients.