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.

International prognostic score for asymptomatic early-stage chronic lymphocytic leukemia

“…There are several prognostic models that can be used to separate patients with different outcome within the whole population of subjects with CLL. 14,18,19,[35][36][37][38][39][40] However, in most of these models, the outcome of patients with early-stage CLL is either not analyzed nor investigated as a unique subgroup, and asymptomatic patients are not separately investigated. Moreover, in most such models, overall survival is the main end point.…”

Lymphocyte doubling time in chronic lymphocytic leukemia modern era: a real-life study in 848 unselected patients

“…Due to this, the management of patients with CLL highly relies on prognostic factors (which estimate overall survival) and predictive factors (which anticipate response to a given treatment). Age, clinical stage (i.e., Rai or Binet), serum B2M, IGHV mutational status, cytogenetic features (e.g., del(17p)/TP53 mutations, del(11q)) are considered the most relevant outcome biomarkers 11,12 In the last decade, progress in the understanding of the biology and therapy of CLL has led to the identification of a huge number of potential biomarkers, although most of them have not been incorporated into daily clinical practice due their complexity, limited availability, lack of validation, or arguable clinical usefulness. In this regard, it is important to underline that biomarkers should be easily obtained, reproducible, and biologically and clinically meaningful 12 In 1966, in a seminal study, David Galton scrutinized a large series of CLL patients with a long follow-up and observed several "blood lymphocyte trends" (from stable to rapidly increasing) which correlated with the clinical course of CLL, from a benign to an aggressive disorder 13 .…”

Lymphocyte Doubling Time As A Key Prognostic Factor To Predict Time To First Treatment In Early-Stage Chronic Lymphocytic Leukemia

“…The breakthrough of novel biologic variables has led to several prognostic indexes to weigh TTFT in early-stage (Binet A) CLL patients (1,2,(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51)(52). Indeed, over the past few years, there has been a great effort to use novel molecular markers in prognostic modeling.…”