Faculty Collaboration Database

Prognostic Score and Cytogenetic Risk Classification for Chronic Lymphocytic Leukemia Patients: Center for International Blood and Marrow Transplant Research Report. Clin Cancer Res 2019 Aug 15;25(16):5143-5155

Date

06/30/2019

Pubmed ID

31253630

Pubmed Central ID

PMC6697588

DOI

10.1158/1078-0432.CCR-18-3988

Scopus ID

2-s2.0-85070674030 (requires institutional sign-in at Scopus site)   12 Citations

Abstract

PURPOSE: To develop a prognostic model and cytogenetic risk classification for previously treated patients with chronic lymphocytic leukemia (CLL) undergoing reduced intensity conditioning (RIC) allogeneic hematopoietic cell transplantation (HCT).

EXPERIMENTAL DESIGN: We performed a retrospective analysis of outcomes of 606 patients with CLL who underwent RIC allogeneic HCT between 2008 and 2014 reported to the Center for International Blood and Marrow Transplant Research.

RESULTS: On the basis of multivariable models, disease status, comorbidity index, lymphocyte count, and white blood cell count at HCT were selected for the development of prognostic model. Using the prognostic score, we stratified patients into low-, intermediate-, high-, and very-high-risk [4-year progression-free survival (PFS) 58%, 42%, 33%, and 25%, respectively, P < 0.0001; 4-year overall survival (OS) 70%, 57%, 54%, and 38%, respectively, P < 0.0001]. We also evaluated karyotypic abnormalities together with del(17p) and found that del(17p) or ≥5 abnormalities showed inferior PFS. Using a multivariable model, we classified cytogenetic risk into low, intermediate, and high (P < 0.0001). When the prognostic score and cytogenetic risk were combined, patients with low prognostic score and low cytogenetic risk had prolonged PFS (61% at 4 years) and OS (75% at 4 years).

CONCLUSIONS: In this large cohort of patients with previously treated CLL who underwent RIC HCT, we developed a robust prognostic scoring system of HCT outcomes and a novel cytogenetic-based risk stratification system. These prognostic models can be used for counseling patients, comparing data across studies, and providing a benchmark for future interventions. For future study, we will further validate these models for patients receiving targeted therapies prior to HCT.

Author List

Kim HT, Ahn KW, Hu ZH, Davids MS, Volpe VO, Antin JH, Sorror ML, Shadman M, Press O, Pidala J, Hogan W, Negrin R, Devine S, Uberti J, Agura E, Nash R, Mehta J, McGuirk J, Forman S, Langston A, Giralt SA, Perales MA, Battiwalla M, Hale GA, Gale RP, Marks DI, Hamadani M, Ganguly S, Bacher U, Lazarus H, Reshef R, Hildebrandt GC, Inamoto Y, Cahn JY, Solh M, Kharfan-Dabaja MA, Ghosh N, Saad A, Aljurf M, Schouten HC, Hill BT, Pawarode A, Kindwall-Keller T, Saba N, Copelan EA, Nathan S, Beitinjaneh A, Savani BN, Cerny J, Grunwald MR, Yared J, Wirk BM, Nishihori T, Chhabra S, Olsson RF, Bashey A, Gergis U, Popat U, Sobecks R, Alyea E, Saber W, Brown JR

Authors

Kwang Woo Ahn PhD Director, Professor in the Data Science Institute department at Medical College of Wisconsin
Mehdi H. Hamadani MD Professor in the Medicine department at Medical College of Wisconsin
Wael Saber MD, MS Professor in the Medicine department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Adult
Aged
Aged, 80 and over
Biomarkers
Chromosome Aberrations
Comorbidity
Female
Hematopoietic Stem Cell Transplantation
Humans
Leukemia, Lymphocytic, Chronic, B-Cell
Leukocyte Count
Male
Middle Aged
Prognosis
Risk Assessment
Survival Analysis
Transplantation Conditioning
Transplantation, Homologous
Young Adult