title: Predicting clinical outcome in CLL: how and why.
abstract: The clinical course of patients with chronic lymphocytic leukemia (CLL) is heterogeneous, with some patients experiencing rapid disease progression and others living for decades without requiring treatment. Clinical features and molecular/biologic factors such as ZAP-70, immunoglobulin heavy chain (IGHV) gene mutation status, and cytogenetic abnormalities on fluorescent in situ hybridization (FISH) have been found to be robust predictors of treatment-free survival and overall survival among newly diagnosed patients. Beyond their widely recognized value for providing insight into disease biology and utility for stratifying patient risk in clinical trials, these prognostic tools play an important role in the current counseling and management of patients with CLL. Recent studies have focused on how to combine the results of multiple prognostic assays into an integrated risk stratification system and explored how these characteristics influence response to treatment. This chapter reviews the available tools to stratify patient risk and discusses how these tools can be used in routine clinical practice to individualize patient counseling, guide the frequency of follow-up, and inform treatment selection.
authors.affiliation: Department of Internal Medicine, Division of Hematology, Mayo Clinic, Rochester, MN 55905, USA. shanafelt.tait@mayo.edu
authors.forename: Tait D
authors.initials: TD
authors.lastname: Shanafelt
mesh_terms: D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D001294:Attitude to Health; D014408:Biomarkers, Tumor / Q000097:blood; D018450:Disease Progression; D042241:Early Diagnosis; D006801:Humans; D016130:Immunophenotyping; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000175:diagnosis / Q000188:drug therapy / Q000235:genetics / Q000401:mortality* / Q000473:pathology / Q000523:psychology; D025202:Molecular Diagnostic Techniques; D009363:Neoplasm Proteins / Q000235:genetics; D009367:Neoplasm Staging; D011379:Prognosis; D018570:Risk Assessment; D016019:Survival Analysis; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins