Predicting the outcome of patients with chronic lymphocytic leukemia: Progress and uncertainty

Abstract

Because chronic lymphocytic leukemia is a heterogeneous disease, there are considerable efforts underway to develop increasingly accurate and precise analytics with which to estimate the probability of future events such as the need for and probability of response to therapy, progression-free survival, and survival. These analytics typically are constructed from clinical and laboratory variables. These variables often are combined into scores or staging systems, some of which are prognostic (therapy-independent), whereas others are predictive (therapy-dependent). Predictive variables differ with different therapies. Because response to therapy is a necessary condition for the improvement of survival, predictive biomarkers are extremely important. However, despite some progress to identify new predictive biomarkers, del(17p)/TP53 mutation remains the only widely accepted variable used to guide therapy. New laboratory techniques and analytical tools may contribute to improvements in the precision and accuracy of outcome indicators. However, there are inherent limitations when applying cohort-based estimates to individuals within the cohort. The accuracy and precision of prediction also are limited by measurement error and chance. Ultimately, estimating outcomes requires a careful balance between clinical experience, imperfect prediction, and uncertainty.