title: B-cell count and survival: differentiating chronic lymphocytic leukemia from monoclonal B-cell lymphocytosis based on clinical outcome.
abstract: The diagnosis of chronic lymphocytic leukemia (CLL) in asymptomatic patients has historically been based on documenting a characteristic lymphocyte clone and the presence of lymphocytosis. There are minimal data regarding which lymphocyte parameter (absolute lymphocyte count [ALC] or B-cell count) and what threshold should be used for diagnosis. We analyzed the relationship of ALC and B-cell count with clinical outcome in 459 patients with a clonal population of CLL phenotype to determine (1) whether the CLL diagnosis should be based on ALC or B-cell count, (2) what lymphocyte threshold should be used for diagnosis, and (3) whether any lymphocyte count has independent prognostic value after accounting for biologic/molecular prognostic markers. B-cell count and ALC had similar value for predicting treatment-free survival (TFS) and overall survival as continuous variables, but as binary factors, a B-cell threshold of 11 x 10(9)/L best predicted survival. B-cell count remained an independent predictor of TFS after controlling for ZAP-70, IGHV, CD38, or fluorescence in situ hybridization (FISH) results (all P < .001). These analyses support basing the diagnosis of CLL on B-cell count and retaining the size of the B-cell count in the diagnostic criteria. Using clinically relevant criteria to distinguish between monoclonal B-cell lymphocytosis (MBL) and CLL could minimize patient distress caused by labeling asymptomatic people at low risk for adverse clinical consequences as having CLL.
authors.affiliation: Mayo Clinic, Rochester, MN, USA. shanafelt.tait@mayo.edu
authors.forename: Tait D
authors.initials: TD
authors.lastname: Shanafelt
authors.forename: Neil E
authors.initials: NE
authors.lastname: Kay
authors.forename: Greg
authors.initials: G
authors.lastname: Jenkins
authors.forename: Timothy G
authors.initials: TG
authors.lastname: Call
authors.forename: Clive S
authors.initials: CS
authors.lastname: Zent
authors.forename: Diane F
authors.initials: DF
authors.lastname: Jelinek
authors.forename: William G
authors.initials: WG
authors.lastname: Morice
authors.forename: Justin
authors.initials: J
authors.lastname: Boysen
authors.forename: Liam
authors.initials: L
authors.lastname: Zakko
authors.forename: Susan
authors.initials: S
authors.lastname: Schwager
authors.forename: Susan L
authors.initials: SL
authors.lastname: Slager
authors.forename: Curtis A
authors.initials: CA
authors.lastname: Hanson
mesh_terms: D000368:Aged; D001402:B-Lymphocytes / Q000473:pathology*; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism; D003937:Diagnosis, Differential; D005260:Female; D005434:Flow Cytometry; D006801:Humans; D007143:Immunoglobulin Heavy Chains / Q000235:genetics; D017404:In Situ Hybridization, Fluorescence; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000175:diagnosis* / Q000401:mortality* / Q000628:therapy; D018655:Lymphocyte Count; D008218:Lymphocytosis / Q000175:diagnosis* / Q000401:mortality* / Q000628:therapy; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D020133:Reverse Transcriptase Polymerase Chain Reaction; D015996:Survival Rate; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor; D007143:Immunoglobulin Heavy Chains